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STR Data Analysis & Interpretation for Forensic Analysts

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1. 3 User Guide no 4338775C rev C Hartzell B K Graham and B McCord 2003 Response of short tandem repeat systems to temperature and sizing methods Forensic Sci Int 133 3 228 34 4 Klein S B J M Wallin and M R Buoncristiani 2003 Addressing ambient temperature variation 2 effects on sizing precision of AmpFISTR Profiler Plus alleles detected on the ABI Prism 310 Genetic Analyzer Forensic Science Communications 5 1 http wWww fbi gov hg lab fsc backissu jan2003 klein htm Applied Biosystems 200 ABI PRISM GeneScan Analysis Software for the Windows NT Operating System User Bulletin 6 Applied Biosystems 2004 GeneMapper ID Software Installation Procedures and New Features for Js GeneMapper ID Software v3 2 User Bulletin part 4352543 rev A Applied Biosystems 2004 GeneMapper ID Software Versions 3 1 and 3 2 Human Identification Analysis Tutorial part 4357520 rev A Online Links e GMID Software Tutorial http www appliedbiosystems com Works Cited amp Online Links 56 57 J Applied Biosystems 1988 AmpF STR Profiler Plus PCR Amplification Kit user s manual Walsh P S N J Fildes and R Reynolds 1996 Sequence analysis and characterization of stutter products at the tetranucleotide repeat locus vW A Nucleic Acids Res 24 14 2807 12 Clark J M 1988 Novel non templated nucleotide addition reactions catalyzed by procary
2. Label category peaks with the category s name Following Step is Sample Allele Stutter Filter Remove labels from peaks followed by a 809 higher labeled peak within 3 25 to 4 75 bp Find all Oladder in sample info in blue dye lanes Label category peaks with the category s name Remove labels from peaks whose height is less than 20 of the highest peak in a categoryOs range Select all categories Unmark selected categories Select category vWA Mark selected categories Select blue lanes Label category peaks with the category s name Following Step is Sample Allele Stutter Filter Remove labels from peaks followed by a 809 higher labeled peak within 3 25 to 4 75 bp 46 57 STR Data Analysis and Interpretation for Forensic Analysts Find all Oladder in sample info in blue dye lanes Label category peaks with the category s name Remove labels from peaks whose height is less than 25 of the highest peak in a categoryOs range Select all categories Unmark selected categories Select category FGA Mark selected categories Select blue lanes Label category peaks with the category s name Following Step is Sample Allele Stutter Filter Remove labels from peaks followed by a 809 higher labeled peak within 3 25 to 4 75 bp Find all Oladder in sample info in blue dye lanes Label category peaks with the category s name Remove labels from peaks whose height is less than 30 of the highest peak in a categoryOs range Select all c
3. Peak Detection Threshold 50 Peak Detection Min Half width 2 Palynamial Degree 3 Peak Wrin 15 4B Julie Mx Low Temp 160ct2003 06 42B diluted 1 1 02 fsa 4Y Julie Vfx Low Temp 160ct2003 06 42B diluted 1 1 02 fsa 2B Julie Mx Low Temp 160ct2003 207 10B diluted 1 1 01 fz3 E52 ON 2 Y L LI 2Y Juie Mix Low Temp 160c12003 207 10B diluted 1 1 01 fs3 X B Analyzed 7 51 53 AM Fri Mar 10 2006 Standard OGS S00 Al zzs Dye Std F Size Method Local Southem Method Size Range 75 400 bps Std Peak Det Threshold 50 Baseline Window Size 51 Slope Threshold for Pk Start 0 0 End 0 0 G Analyzed 7 51 53 AM Fri Mar 10 2006 Standard OGS 500 Al szs Dye Std F Size Method Local Southem bethod Size Range 75 400 bps Std Peak Det Threshold 50 Baseline Window Sire 51 Slope Threshold for Pk Start 0 0 End 0 0 Y Analyzed 7 51 54 AM Fri Mar 10 2006 R Analyzed 7 51 54 AM Fri Mar 10 2006 HE 46 Juse Mix Low Temp 160ct2003 06 428 diluted 1 1 02 fsa BE 4R Juse Mix Low Temp 160ct2003 06 428 diluted 1 1 02 fsa YT I UNBIGEKCENSSSNUSENTSNUNUUSU 2G Julie Mx Low Temp 160612003 407 10B diluted 1 1 01 fsa BE 2R Juie Mix Low Temp 160c12003 207 10B diluted 1 1 01 fsa Peak Totals Found In Sample 25 Dye Std 11 Std Defined 10 Std Matched 9 Peak Totals Found In Sample 93 Dye Std 11 Std Defined 10 Std Matched 9 Wi GeneScan 3 7 u
4. Q4 A microvariant represents an incomplete repeat for a given allele For instance at D18S51 a 15 allele designation means that there are 15 AGAA s along the fragment However a 14 2 allele designation means that there are 14 AGAA repeats along the fragment and an additional 2 bases AG Microvariants are reported as the number of complete repeat units and are designated as an integer e g 14 Any partial repeat is designated as a decimal followed by the number of bases in the partial repeat e g 2 Many microvariants are represented in allelic ladders or have virtual allele categories within the software program those that do not have established categories are designated as off ladder alleles While off ladder alleles have been well documented with forensic STR testing some may not have been previously characterized The National Institute of Standards and Technology NIST website has a listing of off ladder alleles and can be used as a reference in these instances If it is determined that an allele has not been characterized it may be advisable to rerun the sample to confirm the type The most common approach for reporting alleles that size higher or lower than the allelic ladder range is as follows e Alleles that are less than the lowest allele on the specific ladder are reported as less than X F Yrw T rrTyrrT rpwremvywreTwireTYTTRWYTTUWVTyETYrwT WTVTUT rrr lan 103 1G H hi 125 122 123 ran ras LAQ
5. Substrate Controls 34 57 STR Data Analysis and Interpretation for Forensic Analysts Some laboratories may include substrate controls in the process These controls aid in troubleshooting inhibition arising from the substrate In addition substrate controls may show background DNA associated with the source of the biological stain being tested and therefore assist in mixture interpretation Evaluation and interpretation of data obtained from substrate controls is assessed on a case by case basis Read more about Substrates in the DNA Esctaction amp Quantitation PDF file Step 2 Extraneous Peaks The second step is to assess each sample to determine if there are any extraneous peaks and if they interfere with the interpretation process Extra peaks within an allele range should be assessed following laboratory procedures Read more about Extraneous Peaks eslewhere in this PDF file Artifacts Various artifacts can complicate and or interfere with the interpretation process Prior to interpreting allele designations the analyst should evaluate each sample to determine if artifacts are present All samples to include controls and ladders should be assessed for the following e Stutter e 3 A nucleotide addition e Spurious peaks spikes blobs noise e Pull up If any of these artifacts are present the analyst should follow the procedures established by the laboratory Step 3 Data Evaluation The thir
6. establish interpretation guidelines The following are interpretation parameters that validation studies establish e Sensitivity e Reproducibility e Precision e Heterozygosity e Mixture assessment Before analyzing and troubleshooting STR data the analyst must understand the methods and the issues inherent to the analysis process The ability to differentiate spurious peaks and artifacts from alleles is imperative Thresholds When the quantity of DNA being analyzed is very low it may be difficult to distinguish true low level peaks from technical artifacts including noise Consequently most forensic laboratories have established peak height thresholds for scoring alleles Only if the peak height expressed in relative fluorescence unit RFU exceeds a standard value will it be accepted There are no firm rules for establishing threshold values Each laboratory must set its own as part of its validation procedure The threshold may be determined experimentally on the basis of observed signal to noise ratios or may be arbitrarily set to a level established by manufacturers or published data Applied Biosystems Inc ABI which sells the most widely used systems for STR typing has recommended a peak height threshold of 150 RFU saying that peaks below this level must be interpreted with caution However many crime laboratories that use the ABI system have set lower thresholds based on their own studies typically 50 to 100 RFU
7. to 4 75 bp Find all Oladder in sample info in green dye lanes Label category peaks with the category s name Remove labels from peaks whose height is less than 20 of the highest peak in a categoryOs range Select all categories Unmark selected categories Select category D8S1179 Mark selected categories 48 5 STR Data Analysis and Interpretation for Forensic Analysts Select green lanes Label category peaks with the category s name Following Step is Sample Allele Stutter Filter Remove labels from peaks followed by a 73396 higher labeled peak within 3 25 to 4 75 bp Find all Oladder in sample info in green dye lanes Label category peaks with the category s name Remove labels from peaks whose height is less than 30 of the highest peak in a categoryOs range Select all categories Unmark selected categories Select category D5S818 Mark selected categories Select yellow lanes Label category peaks with the category s name Following Step is Sample Allele Stutter Filter Remove labels from peaks followed by a 90096 higher labeled peak within 3 25 to 4 75 bp Find all Oladder in sample info in yellow dye lanes Label category peaks with the category s name Remove labels from peaks whose height is less than 25 of the highest peak in a categoryOs range Select all categories Unmark selected categories Select category D13S317 Mark selected categories Select yellow lanes Label category peaks with the category s nam
8. using this mixture interpretation approach e The sample must be of suitable quality and quantity to ensure a balanced amplification Degraded and low level samples are prone to unbalanced amplification which could prevent an analyst from reliably using this approach Laboratories should conduct validation studies on low level degraded samples to include mixtures e The staff understands and recognizes how the multiplex behaves with these sample types 37 57 STR Data Analysis and Interpretation for Forensic Analysts Mixtures with Major Minor Contributors The presence of major and minor contributor s is distinguishable when samples display alleles that have distinct contrast in signal intensities All loci should be used for this evaluation and laboratories should follow established procedures that are based upon validation studies View an animation about major and minor contributors to a sample The calculations of peak height area percentages and percent contribution of donors can be used to support the declaration or a major and or minor contributor In these instances the DNA profile of the major source may be easily determined at unambiguous loci In general determining the DNA profile of the major contributor is easier than determining that of the minor source as NEAN zn S s BOM au zgi Above is an electropherogram demonstrating a mixture The set of peaks on the right FGA locus represent a clear
9. 245 03 569 RJ Ladder 032206 PP3 23 05 4 02 PM fsa 246 17 461 R7 Ladder 032206 PP3 23 08 7 36 PM fsa 246 18 588 R7 Ladder_032206_PP3 23 06 8 06 PM fsa 245 25 577 In the clas SIC mode S1ZC RJ Pos 032108 PP3 23 06 12 59 PM fsa 246 1 533 R7 Pos 032108 PP3 23 05 4 33 PM fsa I fo 246 2 547 calling is performed by matching the actual size standard fragments of the sample with a defined size standard that must be accurately labeled it utilizes scan number to assign sizes e In the advanced mode size calling is performed using a function known as ratio matching Ratio matching uses an algorithm to determine the distance between the size fragments based on the entry of a set of size fragment values where it uses the relative distance between the neighboring peaks to size The following excerpts from the Applied Biosystems User Bulletin on Size Parameters explain these differences 05 ize wee p f xeu pure xr s BH i XO Hy Ls xS ee Ron Sun cat 12 57 STR Data Analysis and Interpretation for Forensic Analysts There are similarities between GMID and GS GT software However GMID offers additional features added flexibility and efficiency through the combining of the programs The expert system potential inherent in the software will continue to develop as new versions are released Note To become familiar with the use of GMID 3 2 it is recommended that analysts read through the User s Manual for v3 1 and Us
10. 7 225 75 x 100 75 contribution from the major donor This can also be represented as a ratio by summing the peak heights of the two minor alleles and dividing them by the sum of the peak heights from the two major alleles e 250 225 674 717 34 ora ratio of approximately 1 to 3 A second check of this hypothesis is evaluation of the peak height percentages In this case the peak height percentage for genotype 1 19 25 is 90 and genotype 2 20 23 1s 94 These values are within the acceptable range of peak height percentage for balanced heterozygotes 39 57 STR Data Analysis and Interpretation for Forensic Analysts This evaluation can be done at any locus with no shared alleles to estimate the proportion from each contributor Once the estimate 1s established loci with two or three alleles can be evaluated Note Genotype 1 Genotype 2 A B C D A C B D A D B C C D A B B D A C B C A D In some cases major minor contributors cannot be established the calculations noted above can be performed for each combination to determine the percent contribution from each donor Two Person Mixture with Three Alleles at a Locus Consider the following information D3S1358 Allele Peak Height 14 1080 16 320 18 690 Visual minor alleles Assuming these results came from the same case as the FGA data in the first example above the FGA data can be used to estimate the mixture percentages This information can aid i
11. 74A at Coriell Institute The positive control should show the expected alleles If no peaks are seen this may indicate a problem with the amplification or injection In the event that the positive control does not yield the correct results analysts 31 57 STR Data Analysis and Interpretation for Forensic Analysts should troubleshoot the problem and follow the procedures established by the laboratory Note It is expected that injection issues would have been identified in the internal size standard evaluation step Known Extraction Control s Many laboratories include known extraction controls in the analysis process These controls aid in determining the overall performance of the entire process from extraction through typing The known extraction control should show the expected alleles If no peaks are seen this may indicate a problem with the amplification or injection In the event that the known extraction control does not yield the correct results analysts should troubleshoot the problem and follow the procedures established by the laboratory Note It is expected that injection issues would have been identified in the internal size standard evaluation step Negative Control s amp Reagent Blanks Reagent blanks are routinely processed with samples Laboratories include reagent blanks in the extraction quantitation and amplification processes to aid in monitoring potential contamination of reagents and or supplies These bla
12. D GeneMapper JD database stores the following Database data e Predefined and custom designed size standard definitions Notes The dacbace e Panel marker loci and allele bin definitions e Analysis methods e Table profiles for generating tabular reports e Saved projects with sizing and genotyping results e Matrix files 310 and 377 instruments only e Plot settings does not store individual sample files Automated concordance checks GeneMapper JD software compares genotype concordance between overlapping loci among different AmpFL STR kits for the same sample s or concordance of genotype calls from duplicate amplifications or duplicate injections of the same sample Positive and negative controls give the expected allele calls Export Combined Table format When exporting from the Samples view you can now export samples that do not pass sizing along with samples that pass sizing This feature combines columns from the sample table and the genotype table and exports them as a single table There are two display options when exporting samples one line per marker and one line per sample This is similar to the Make Allele table in the Genotyper Software Changes to the electropherogram displays The software now provides the option to display labeled peak assignments for all size standards The user can quickly identify peaks visually and perform a size precision test The labeled peak assignments a
13. GeneScan software sizes peaks using the internal size standard added to the sample prior to separation as shown below 3 57 STR Data Analysis and Interpretation for Forensic Analysts 350 300 349 400 internal Size Standard DNA fragment peaks are sized based on the sizing curve produced fram the points on the internal size standard 147 32 bp 139 HM Ow MP ee eee Pe TESILETEEI E SEG SS SRC SSP SSC RES SSR SSS SS a ii a m Data ONA fragment point peaks in sample 500 450 490 While samples are being processed by the genetic analyzer sample files fsa are generated during the data collection process These files are then analyzed by the GeneScan analysis software There are five vital pieces of information in the sample file that are used and displayed during GeneScan data analysis F GeneScan 3 7 A1Known_1t01_PP isa WD Fie Edi Prod Sample Selling View Wedow Heb AR o wo 1500 e Ept file EP Voltage Em 100 Laser Power ma mW 4 51 EP Current Run Temp mm HA C STR Data Analysis and Interpretation for Forensic Analysts Bak 18 x e Raw Data LLL cmn Lr NN CNN DRE N SeneScan 3 7 D8POS e x Fo Ele ER Project Senpi Ela x e Size calling curve Siza Callina Curve Local Southern Method 5 57 STR Data Analysis and Interpretation for Forensic Analysts 15 File Edit Projec
14. IO Fluorescence 777 Software Imaging System Size DNA FMBIO Analysis Fragments Software STaR Cail Genotype Genotyping OTR Alleles Solivar Perform Manually Data inspect Analysis the data FMBIO STaRCall STaRCall is the software program that genotypes gel electrophoresis data for the Hitachi FMBIO system Sizes from the FMBIO Analysis Software are imported into STaRCall similar to the process used on GS GT software on the capillary electrophoresis platform This program is similar in process to Genotyper Allelic ladders are used to size the fragments from adjacent lanes the closer the ladders are to the samples being run the more precise the sizing Where Genotyper has a bin set associated with its macros STaRCall has STR look up tables maintained in Microsoft Excel Optical density units are used to quantitate the fragments as the data are reviewed 14 57 STR Data Analysis and Interpretation for Forensic Analysts An example of the spreadsheet a e vce yest roma mus us Wels Us PRE used to determine genotypes DSEBaSRY iem EMSS Cae EGET amp ta wa d Ch fa iz H 3 Ye Reply with Changes End Review q Data Troubleshooting Arial 0 B z u E EMH S BBE D O A G Introduction Cutoff ecus From To To FGA 0 20 z suus e Fog P uu nif a Short tandem repeat STR data analysis and interpretation in forensic DNA cas
15. OER Fira J Bh LADDER P E p pop psp qu sampe Pts 1 Bee Sample LP AE S i 3 i OPE LAQOER Fisa Ghia LADDER P DJi Sampe P123 J See Sampe 1P Degradation DNA degradation is a process by which DNA breaks down into smaller fragments Environmental factors such as sunlight heat and humidity can increase the rate of degradation DNA samples that are subjected to 22 57 STR Data Analysis and Interpretation for Forensic Analysts environmental factors that promote degradation can pose challenges for data interpretation As DNA molecules randomly break down into smaller fragments the STR regions of the DNA molecule can be fractured If the STRs do not stay intact amplification of these regions will not be successful Degradation is more likely to occur at a large STR locus before occurring in a smaller STR locus Generally degradation can be easily identified because the peak heights exhibit a downward slope across the electropherogram The process of degradation can reduce the height of some alleles making them too low to be distinguished from background noise in the data In severely degraded DNA samples no results will be obtained Two or more biological samples that make up a mixture may show different levels of degradation which can complicate the interpretation of these samples View an animation that further explains partial profiles Stochastic Effects Stochastically induced heter
16. Q5 it is important to develop a procedure to effectively deal with them in paternity cases Many researchers in the field suggest using a two locus exclusion for STR paternity testing 06 Since mutations are relatively rare for the core STR loci it is unlikely that two mutations would occur during meiosis at two different loci Somatic mutations have been known to occur at STR loci used in forensic testing A somatic mutation occurs within somatic cells and are not inherited For example a somatic mutation can occur in early embryonic development within an STR locus Although the embryo inherits an 8 allele at D7S820 from its mother and a 9 allele from its father the mutation results in an additional 10 allele Therefore the child will exhibit a tri allelic pattern at D7S820 A mutation of this type can look like a mixed DNA sample or a contamination event at that locus After a review of data from other loci these concerns can be dismissed It might be advisable to retest the sample or possibly other tissue types from the individual to confirm the DNA profile 24 5 STR Data Analysis and Interpretation for Forensic Analysts 222 224 226 228 230 232 234 236 238 bp 29 32 Mother L 29 3 1000 0 Child d en fs 29 An example of a mutation in the STR locus D21S11 of the father causing allele mismatch in the child Note the presence of allele 30 in the child and the peak height of all of the alleles of the mother the su
17. STR Data Analysis amp Interpretation for Forensic Analysts This course is provided free of charge and is part of a series designed to teach about DNA and forensic DNA use and analysis Find this course live online at http dna gov training strdata Updated October 8 2008 PRESIDENT S INITIATIVE www DNA gov About this Course This PDF file has been created from the free self paced online course Crime Scene and DNA Basics for Forensic Analysts To learn more and take this and other courses online go to http www dna gov training online training Most courses are free but you must first register at http register dna gov If you already are registered for any course on DNA gov you may login directly at the course URL e g http letraining dna gov or you can reach the courses by using the URL http www dna gov training and selecting the Login and view your courses link Questions If you have any questions about this file or any of the courses or content on DNA gov visit us online at http www dna gov more contactus Links in this File Most courses from DNA Gov contain animations videos downloadable documents and or links to other useful Web sites If you are using a printed paper version of this course you will not have access to those features If you are viewing the course as a PDF file online you may be able to use some of these features if you are connected to the Internet An
18. The same approach can be used to estimate the mixture percentages and interpret data in a two person mixture case with two alleles at a locus This information can aid in determining the most likely genotypes of the major and minor contributors The following scenarios are possible Possible Scenarios Scenario Genotype 1 Major Genotype 2 Minor I 99 9 11 2 9 11 9 11 3 9 9 11 11 4 9 11 11 11 5 9 11 9 9 6 11 11 9 9 7 11 11 9 11 e Scenario 1 This scenario is unlikely because a shared 9 allele would leave a very low percent contribution for Genotype 1 e Scenario 2 If it is assumed that the minor donor contributed 25 and the major donor contributed 75 based on FGA results The estimated peak height percentage would be Genotype 1 would be 198 300 x 100 66 Genotype 2 would be 596 901 x 100 66 e Scenario 3 The percent contribution would be Genotype 1 794 794 1201 x 100 40 Genotype 2 1201 794 1201 x 100 60 e Scenario 4 In this scenario 11 is a shared allele and it is assumed that the contribution is equal to that of the 9 42 5 STR Data Analysis and Interpretation for Forensic Analysts allele which is 794 RFUs Genotype 1 This would leave Genotype 2 contributing 407 RFUs The percent contribution would be Genotype 1 794 794 794 1201 x 100 80 Genotype 2 407 794 1201 x 100 20 e Scenario 5 This scenario unlikely since a shared 9 allele wo
19. Threshold exact value varies from lab to lab od od TUNER lie hate The lower threshold is a measure of the sensitivity of the procedure Most laboratories establish both lower and upper thresholds for data interpretation thereby establishing a window to interpret data A laboratory s threshold can be influenced by a variety of factors For example there are sensitivity differences between the types of instrumentation e g capillary electrophoresis CE instruments and slab gel instruments and within any one type of instrument e g between different ABI 310 instruments 16 57 STR Data Analysis and Interpretation for Forensic Analysts Many laboratories have noted the varying sensitivities of instruments which tend to be more sensitive and have better resolution than gel based systems Some laboratories have established thresholds within their laboratory that vary depending on the sensitivity of the specific instrument The upper threshold is crucial when reviewing data from high quantity DNA samples Samples with high quantities of amplified DNA will have high RFU values that can oversaturate the instrument s ability to detect the sample This can lead to difficulty in interpretation because an accurate measurement with respect to the peak heights and or areas may not be obtained This can be especially problematic when working with mixed samples Note The instrument s software analyzes and makes sizing determinat
20. ategories Unmark selected categories Select category AMEL Mark selected categories Select green lanes Label category peaks with the category s name Following Step is Sample Allele Stutter Filter Remove labels from peaks whose height is less than 3 of the highest peak in a categoryOs range Find all Oladder in sample info in green dye lanes Label category peaks with the category s name Remove labels from peaks whose height is less than 40 of the highest peak in a categoryOs range Select all categories 41 57 STR Data Analysis and Interpretation for Forensic Analysts Unmark selected categories Select category D18S51 Mark selected categories Select green lanes Label category peaks with the category s name Following Step is Sample Allele Stutter Filter Remove labels from peaks followed by a 525 higher labeled peak within 3 25 to 4 75 bp Find all Oladder in sample info in green dye lanes Label category peaks with the category s name Remove labels from peaks whose height is less than 10 of the highest peak in a categoryOs range then remove labels from peaks followed by a 222 higher labeled peak within 0 00 to 5 00 bp Select all categories Unmark selected categories Select category D21S11 Mark selected categories Select green lanes Label category peaks with the category s name Following Step is Sample Allele Stutter Filter Remove labels from peaks followed by a 669 higher labeled peak within 3 25
21. ave higher stutter In known single source samples stutter is identifiable by its size and position However with mixed samples stutter and alleles can overlap complicating interpretation Read more about interpretation elswhere in this PDF file The scientific community as well as individual forensic laboratories has conducted validation studies to determine the expected range of stutter percentages In general stutter percentages do not vary significantly There are two cases in which variability in the stutter percentages can be seen e Low level samples low RFUs e Samples exceeding the detection level of the instrument excess DNA 20 57 STR Data Analysis and Interpretation for Forensic Analysts Non Template Addition ng 160 d E A od n f me 1d i OS ee Ni titi If too much input DNA is added to an amplification reaction the polymerase may be unable to complete the extension for all amplicons 03 Non template addition results in a PCR Polymerase Chain Reaction product that is one base pair longer than the actual target sequence When the polymerase is unable to complete the adenine addition on all products this results in what is commonly referred to as split peaks A A peaks Q1 To minimize split peaks the extension phase of the PCR process is designed to drive the addition of adenine ensuring that all amplicons are the same length Kit manufacturers have also developed primer sequences that enc
22. d step in the interpretation process 1s to assess the data from each sample Laboratories take both qualitative and quantitative approaches to this assessment Laboratory procedures should be based upon validation studies and provide a scientific foundation for data interpretation and reporting After determining if extraneous peaks interfere with interpretation many laboratories assess the peak height percentages and determine the contribution from each donor in mixtures In order to use either of these estimations the following should be established e The laboratory should conduct validation studies to establish a relative fluorescence unit RFU range within which consistent peak height percentages are obtained with the method s used For example low level and or degraded DNA may produce data at or around the threshold established by the laboratory Many validation studies have demonstrated that consistent peak height percentages cannot be obtained at low RFUs e The laboratory should conduct validation studies to establish minimum donor contribution For example many laboratories have determined that for a two person mixture the minor donor must contribute at least 10 in order to be reliably assessed 35 57 STR Data Analysis and Interpretation for Forensic Analysts Peak Height Percentage Under optimum conditions sufficient quantity and quality of DNA heterozygous peaks within a locus should be similar in height or intensity to
23. e Following Step is Sample Allele Stutter Filter Remove labels from peaks followed by a 900 higher labeled peak within 3 25 to 4 75 bp 49 57 STR Data Analysis and Interpretation for Forensic Analysts Find all Oladder in sample info in yellow dye lanes Label category peaks with the category s name Remove labels from peaks whose height is less than 25 of the highest peak in a categoryOs range Select all categories Unmark selected categories Select category D7S820 Mark selected categories Select yellow lanes Label category peaks with the category s name Following Step is Sample Allele Stutter Filter Remove labels from peaks followed by a 1011 higher labeled peak within 3 25 to 4 75 bp Find all Oladder in sample info in yellow dye lanes Label category peaks with the category s name Remove labels from peaks whose height is less than 25 of the highest peak in a categoryOs range Select all categories Unmark selected categories Select categories D381358 vWA FGA AMEL D8S1179 D21S11 D18S51 D5S818 D13S317 D7S820 Mark selected categories Sort categories by 1 ascending dye color 2 ascending size or scan Sort dye lanes by 1 ascending lane number 2 ascending dye color Select blue lanes And select green lanes And select yellow lanes Unmark selected dye lanes Find OladderO in sample info in blue dye lanes Mark selected dye lanes 50 57 STR Data Analysis and Interpretation for Forensic Anal
24. e The results are averaged and the size of the allele is determined For a review of size calling methods 2 4 listed above reference the GeneMapper JD software version 3 1 7 57 STR Data Analysis and Interpretation for Forensic Analysts User s Guide 02 Below is a visual representation of the sizing process of the Local Southern method STR Allele Internal Size Standard X1 X2 Size of 2 STR Allele In variable temperature environments some studies have found that the Global Southern method rather than the Local Southern method may provide better sizing precision 03 04 One important issue concerning the sizing of AmpFSTR GS500 size standards ROX or LIZ is the de labeling of the 250 base pair fragment At a minimum the 250 fragment should not be labeled 04 Read more about delabeling eslewhere in this PDF file The size calling method is one component of the overall parameter settings that are configured prior to analyzing data Smoothing The purpose of smoothing 1s to reduce the number of false peaks detected by the software Prior to GeneMapper JD 3 2 the Macintosh GS software smoothed before the data were analyzed and the GS software for Windows NT smoothed after analysis This particular difference in the smoothing algorithm between Macintosh and Windows NT versions produced slightly different peak heights for the same sample files When working with an established threshold this could cause difference
25. each other In general heterozygous alleles have peak heights that are within 7096 of each other but laboratories should conduct validation studies to determine an appropriate peak height percentage for the method s used The peak height percentage for two heterozygous peaks is determined by dividing the peak height of the smaller peak by the peak height of the larger peak The result is then expressed as a percentage and is referred to as the peak height percentage EEI 21m Peak height ratio for 0351358 Peak height ratio Bid for vVWA T 573 666 383 383 Peak height ratio for FGA 100 0 270 354 ana 2 Many things can affect heterozygous peak height percentages Data from samples with low level and or degraded DNA may have peak height percentages much lower than 70 In addition the composition of the muliplex to inlcude the size of the multiplex can affect the percentage Laboratories should use their validation studies to determine an acceptable peak height percentage range for both single source and mixed DNA sample data interpretation Note The peak area can be used in place of peak height Single Source Profiles Profiles developed successfully from a single contributor will display one or two alleles at each locus excluding rare mutations The profiles will have peak height percentages consistent with the laboratory s interpretation procedures which were established through validation studie
26. er Bulletin for v3 2 focusing particular attention on the verification process and the software features and functions 07 FMBIO Analysis Software FMBIO Analysis Software is a program that is associated with slab gel electrophoresis This program uses the Macintosh operating system Before using the FMBIO Analysis Software the analyst must use the read image program to define the scan area and resolution It is similar to operating a desktop scanner Each image captured by the read image program is converted to a Tag Image File Format TIFF file 01 Following scanning the FMBIO Analysis Software is utilized to size the bands and quantitate peak height and area This functionality is equivalent to the GeneScan process discussed previously The FMBIO Analysis Software also uses algorithms to size and quantitate The software includes a band finding program to aid in the identification of possible DNA fragments but user review is required The following figure depicts the FMBIO procedure including the applicable software processes 01 13 57 STR Data Analysis and Interpretation for Forensic Analysts 7 Prepare samples Prepare samples denature cool and mix with loading dye denature cool and mix with loading dye D 7 Load Samples Load Samples fallelic ladder every 3 lane allelic ladder every 3 lane D T A M Electrophoresis Electrophoresis a Post Ele ctrophoresis wer SCAN GEL Readimage FMB
27. ework relies on an analyst s professional judgment and expertise Procedures for analysis and interpretation are based on validation studies published literature population studies and casework experience Laboratory interpretation procedures are not meant to cover every situation but rather to establish a minimum standard for the interpretation of analytical results Documented procedures contribute to objectivity and consistency and ensure that the conclusions drawn in casework are scientifically supported by analytical data A number of factors can introduce ambiguity into the analysis and interpretation process Analysts must be able to identify and troubleshoot these ambiguities and understand their implications Objectives Upon successful completion of this unit of instruction the student shall be able to e List commonly used STR data interpretation parameters 15 57 STR Data Analysis and Interpretation for Forensic Analysts e Explain thresholds spurious peaks pull up stutter microvariants degradation stochastic effects allele dropout mutations controls used in troubleshooting STR data Data Interpretation and Troubleshooting Interpretation of genotypes is based on a pattern of peaks or bands which are visual representations of DNA fragments Laboratories use data compiled from validation studies to establish procedures for data analysis and interpretation These validations studies provide data so that the laboratory can
28. exclusion or non match is reported when loci from which results are obtained are discordant between a questioned sample and a known 43 5 STR Data Analysis and Interpretation for Forensic Analysts View an explanation of a non match Inconclusive Uninterpretable There are occasions when an analyst cannot interpret data or the data is inconclusive Some mixtures may be too complex to render conclusions and will be reported as uninterpretable Low level and or degraded DNA samples may result in inconclusive results at some or all loci View an explanation of an inconclusive electropherogram No Results No results are reported when there is no discernable allelic activity observed at a locus View an explanation of an electropherogram that shows no results Read more about Reporting in the Communicating Results PDF file Author Steve O Dell Steve O Dell MSFS CCSA is the DNA Technical Manager and Crime Scene Response Section Supervisor for the Phoenix Police Department Author Russell Vossbrink Russell Vossbrink is the technical supervisor of the Regional FBI mtDNA lab at the Arizona Department of Public Safety Russell is a member of the American Academy of Forensic Sciences AAFS and he has been a regular member and invited guest of the Scientific Working Group for DNA Analysis Methods SWGDAM Russell has presented at Promega Combined DNA Index System CODIS AAFS California Association of Criminalists CAC Southwes
29. for Genotype 2 since the assumption was a 1 1 contribution from each allele 320 RFU The percent contributions would be e Major 690 760 1080 320 690 69 x 100 69 e Minor 320 320 1080 320 690 31 x 100 31 Scenario 2 Major 14 18 Minor 16 16 If the minor contributor is a homozygous 16 the estimated peak height percentage for Genotype 1 would be 64 690 1080 64 The percent contributions would be e Major 690 1080 1080 320 690 85 x 100 85 e Minor 320 1080 320 690 69 x 100 15 Scenario 3 Major 14 18 Minor 16 18 In this scenario 18 is a shared allele and it is assumed that the contribution is equal to that of the 16 allele which is 320 RFUs Genotype 2 This would leave Genotype 1 contributing 370 RFUs to the 18 690 320 370 The estimated peak height percentage for Genotype 1 would be 34 370 1080 34 The percent contributions would be 41 57 STR Data Analysis and Interpretation for Forensic Analysts e Major 1080 370 1080 320 690 69 x 100 69 e Minor 320 320 1080 320 690 31 x 100 31 Based on these estimations Scenario 1 is the best fit but Scenario 2 should be considered Scenario 3 has an estimated peak height percentage for Genotype 1 of 34 making this combination unlikely Two Person Mixture with Two Alleles at a Locus Consider the following information D5S818 Allele Peak Height 9 794 1 1201
30. hing profiles with the specifically for searching the Yfiler Yfiler Haplotype Haplotype Database for profile match Database estimation 11 57 STR Data Analysis and Interpretation for Forensic Analysts Genotyper had a feature that allowed review of the sizing standard for precision assessment This feature was not available in the first version of GMID v3 1 it is included in version 3 2 However it requires a work around to achieve the precision statistics on the 250 base pair fragment The size standards can be overlayed from all samples in the run The base pair sizes for the fragments can be displayed the table exported to Microsoft Excel and the Excel functions used to calculate the 250 base pair precision from a run Samples Plot At the right is a screen capture Of Fe edt vew Toot aes nen ampFLSTR Genotyping zA Paese zlii D en lei al US 1 EE d ndar rl ith th iind the size standard overlay with the T TETTE TREES sizing table beneath Sample Pma sqo sa Analysis Modes As previously mentioned there are two analysis modes classic Macintosh and advanced Windows NT modes The differences between these modes are found in the sizing method and the flexibility of peak sensitivity settings 143 Dye Sample Peak Sample File Name Marker Allele Sp ecifically the mode differences R7 Ladder 032206 PP3 23 05 10 04 AM fsa 245 79 550 are RB Ladder 032206 PP3 23 05 11 27 AM fsa
31. imations Audio and Video Throughout this course there may be links to animation audio or video files To listen to or view these files you need to be connected to the Internet and have the requisite plug in applications installed on your computer Links to other Web Sites To listen to or view any animation audio or video files you need to be connected to the Internet and have the requisite plug in applications installed on your computer Legal Policies and Disclaimers See Legal Policies and Disclaimers for information on Links to Other Web Sites Copyright Status and Citation and Disclaimer of Liability and Endorsement STR Data Analysis and Interpretation for Forensic Analysts STR Data Analysis and Interpretation for Forensic Analysts This course provides information in three lessons STR Short Tandem Repeat Data Analysis and Interpretation Software Learn the basics of data analysis software become familiar with the purpose of GeneScan and Genotyper software learn the difference between GeneScan and Genotyper software and GeneMapper ID software and become aware of the unique features of GeneMapper ID software and understand FMBIO Analysis software and STaRCall software as related to GeneScan and Genotyper software Data Troubleshooting Learn about commonly used STR data interpretation parameters and thresholds spurious peaks pull up stutter microvariants degradation stochastic effects allele dropout
32. in the interpretation of the sources of the mixture For example e It is common to find a mixture from sexual assault evidence e t is possible to find a mixture in a known blood sample from a deceased individual if that person was transfused prior to death e t is possible to find a mixture when intimate samples are analyzed Intimate samples are generally swabs collected from a person s body skin buccal vaginal swabs View an example of how mixtures might exist on a piece of evidence Mixtures can vary in their complexity and alternative approaches should be established for each of these categories e Mixtures with major and minor contributors e Mixtures with known contributor s e Mixtures with indistinguishable contributor s Many laboratories quantitatively assess the peak height or area in an effort to determine the proportion contribution of donors to a mixture 02 It is worth noting that mixtures can be fully interpreted only when all the alleles from the minor contributor are above the background noise 03 Using percent contribution of donors in a mixture is premised on the following e The amplification parameters of the multiplex must be established This can be accomplished through validation studies Data from these studies can be used to determine peak area peak height percentages of heterozygotes and stutter ranges for each locus Establishing these parameters and understanding how a multiplex performs is crucial when
33. indshield sidewalk wall floor weapon etc This category applies to mixtures that are not included in the two categories described above These mixtures are typically the most difficult category to interpret In general the interpretation of two person mixtures where each person donates half of the DNA will not be aided by estimating percent contribution or percent peak height ratios Applying statistical interpretation is more simplistic with one contributor e g single source samples or mixtures where a major component can be defined or inferred Statistical evaluation of complex mixtures involves the use of the likelihood ratio or probability of inclusion exclusion Read more about the likelihood ratio in the Population Genetics amp Statistics PDF file Read more about the probability of inclusion exclusion in the Population Genetics amp Statistics PDF file Example of Percent Contribution Consider the evaluation of the following FGA Allele Peak Height 19 250 20 674 23 717 237 225 Visual minor alleles There appears to be a major and a minor contributor Assuming only two donors the mixture proportions are estimated by summing the peak heights of the two major or minor alleles and dividing by the peak heights of all four alleles This is then multiplied by 100 to provide a percentage contribution e 250 225 250 674 717 225 25 x 100 25 contribution from the minor donor e 674 t 717 250 674 71
34. ions based on the lower threshold established by the laboratory Some laboratories have adopted a procedure to evaluate data below their RFU threshold in an attempt to interpret data for exclusionary purposes For instance a laboratory can have a lower threshold at 100 RFU If additional data is detected below that threshold e g 50 to 99 RFU it could be evaluated for exclusionary purposes Spurious Peaks Chemistry and instrument related issues can lead to spurious peaks Spurious peaks also referred to as artifacts include dye blobs spikes and noise they may be difficult to differentiate from alleles In general spurious peaks are not reproducible Samples can be reinjected to determine whether suspected artifacts are reproducible or analysts can rely on their professional experience to differentiate alleles from spurious peaks Dye Blobs Dye Blob Disassociated primer dyes more commonly referred to as dye blobs are fairly common in STR analysis While it isn t entirely understood why dye blobs occur evidence suggests that the fluorescent dye tags attached to the primers begin to break down over time 01 Disassociated primer dyes can show up in the sample analysis range and can mask true data Dye blobs are usually wider than real peaks and are typically only seen in one color When the manufacturer s specifications for storage of amplification kits are followed 17 57 STR Data Analysis and Interpretation for Forensic Analy
35. ly available repeat types for markers with tetranucleotide repeat motifs In GeneMapper ID Software v3 2 however allele calling parameters are available for four marker repeat types tri tetra penta and hexanucleotide The four allele calling parameters appear in the Allele tab of the Analysis Method Editor All related analysis values are entered directly into the Tri Tetra Penta or Hexa column fields which allows for viewing of all values New feature Plus stutter To aid in interpreting genotype profiles two filtering for the DYS392 new fields have been added to the Allele tab locus of the Analysis Method Editor specifically to filter out the DYS392 plus stutter e Plus Stutter Ratio e Plus Stutter Distance Procedure Workaround for Laboratories may choose to implement a the DYS19 locus 2bp work around for the DYS19 locus by using filtering the Minus A Ratio and Minus A Distance fields in the Allele tab of the Analysis Method Editor These fields can be used to filter out the 2 bp stutter that 1s observed at the DYS19 locus Procedure Creating HID Use the Analysis Method Editor in analysis methods for the GeneMapper ID Software v3 2 to set Yfiler kit analysis parameter values for analyzing the Yfiler kit data Procedure Creating a table Using the Table Setting Editor a table setting and uploading setting is created in GeneMapper ID exported haplotype s for Sortware v3 2 to export haplotypes searc
36. major and minor contributor there are two tall peaks and two short peaks The set of peaks on the left VW A locus represent an ambiguous minor contributor The major contributor appears to be a 17 18 It is unclear however whether the major contributor is or is not masking the minor contributor who could be a 16 16 a 16 17 ora 16 18 Mixtures with Known Contributor s It is common to obtain samples where one of the contributors e g the victim is known In these cases it may be possible to infer an unknown profile by subtracting the contribution of the known donor from the mixed profile 01 In general this approach is taken on intimate samples such as vaginal swabs fingernails breast swabs neck swabs and clothing items removed from a person s body in situations where it is likely that there are no more than two contributors It may be possible to infer unknown profiles from mixtures with more than two contributors but that would be considerably more complex An analyst can use percent mixture contribution and peak height percentages to aid in inferring profiles from mixtures with known contributors 38 57 STR Data Analysis and Interpretation for Forensic Analysts View an animation about how a known contributor sample can be used to infer the profile of an unknown contributor to a mixture Mixtures with Indistinguishable Contributor s Items falling into this category include non intimate samples such as swabs from a w
37. mutations and controls used in troubleshooting STR data Data Interpretation and Allele Calls Learn the factors that can influence the output from instruments used in DNA analysis learn about the controls and other techniques used to validate instrument output compare methods to evaluate data and recognize analysis artifacts and learn how to to analyze data from single source and mixed source samples STR Short Tandem Repeat Data Analysis amp Interpretation Software Introduction Following separation of amplified DNA products the information from the DNA separation must be converted into a common language that is standard from laboratory to laboratory Software programs provide the means to perform the necessary data analysis and standardize the output 1 57 STR Data Analysis and Interpretation for Forensic Analysts Objectives Upon successful completion of this unit of instruction the student shall be able to e Identify data analysis software e Be familiar with the purpose of GeneScan and Genotyper software e Differentiate between GeneScan and Genotyper software and GeneMapper ID software e Explain the unique features of GeneMapper D software e Understand FMBIO Analysis software and STaRCall software as related to GeneScan and Genotyper software Overview Data produced in the separation and characterization of amplified DNA is displayed as e Peaks ca
38. n determining the most likely genotype s of the major and minor contributors for a locus with three alleles There are numerous scenarios that may be possible However in many instances the analyst can easily dismiss some based on the available data Genotypes per Scenario Scenario Genotype 1 Major Genotype 2 Minor O 00 19 NM BW N e CO EN NO 40 57 14 18 14 18 14 18 14 14 16 16 18 18 14 16 16 18 14 16 14 16 16 18 16 18 14 16 16 16 16 18 16 18 14 18 14 16 14 18 14 18 16 18 18 18 14 16 14 14 STR Data Analysis and Interpretation for Forensic Analysts If it is assumed that the major contributor is approximately 75 the data only support scenarios 1 3 In this example the assignment of a genotype for the major contributor is straightforward When alleles are shared or possibly masked assigning a possible genotype of the minor contributor is more complex Use of the above example to assess these three scenarios will assume that there is a 1 1 RFU ratio for heterozygous alleles Scenario 1 Major 14 18 Minor 14 16 In this scenario 14 is a shared allele and it is assumed that the contribution is equal to that of the 16 allele which is 320 RFUs Genotype 2 This would leave Genotype 1 contributing 760 RFUs for the shared 14 1080 320 760 The estimated peak height percentage for Genotype 1 would be 91 690 760 91 note that no estimated peak height percentage is calculated
39. nalyst proceeds with the interpretation of the overall profile Click here to view Genotyper s macros window GeneMapper JD v3 2 Pala les gt oe i ite ek e e Pa T and ii LA samai eiei gren eil E j jia NINFEE 1 Le hood Fa Ek are eus GeneMapper ID GMID is an automated genotyping program that combines the functions of the GeneScan analysis software and Genotyper software into one package The software program designates peaks in electropherograms by sizing and makes allele calls through size comparisons to an allelic ladder GMID provides the flexibility to analyze data in either a Macintosh classic analysis mode or a PC advanced mode One difference for the advanced mode using the Windows NT format is in the smoothing algorithm both classic and advance modes smooth before the data are analyzed The unique features in the GMID v3 1 and v3 2 not previously present in the GS GT software combination are presented below Q2 06 Unique Features in the GMID v3 1 and v3 2 Unique Feature Description CODIS Export The software can export results ina CODIS recognized format cmf v1 0 and 3 0 Process The PQV system automatically assigns values to Component Based the quality of the data in respect to sizing and Quality Values PQV allele calling Poor quality samples are those below the user defined thresholds 9 57 STR Data Analysis and Interpretation for Forensic Analysts GeneMapper I
40. nding site regions or along the STR region can complicate interpretation The following are types of mutations that can occur Types of Mutations Mutation Description Insertion A base is inserted or added to the original DNA strand Deletion A base is deleted or removed from the original DNA strand Transition A transition between purine or pyrimidine bases occur in the original DNA strand e purine adenine guanine e pyrimidine cytosine thymine Transitions are more common than transversions Transversion A transversion between purine and pyrimidine bases occur in the original DNA strand e guanine cytosine e guanine thymine e adenine cytosine e adenine thymine Mutation amp Paternity Mutations occurring during meiosis can affect the interpretation of paternity tests A mutation during meiosis may result in discrepant results at a locus For instance a mother has a 14 15 type at D3S1358 The assumed biological father has a 17 18 type at D3S1358 The offspring has a 15 19 type When data at this one locus are compared it appears that the child s assumed biological father can be excluded because the male could not have passed the 19 allele on to the child During meiosis it is possible for an additional tetranucleotide repeat to be added to the DNA strand Therefore the male could have passed along a 19 allele even though he doesn t have that allele type if this mutation takes place Since mutations occur at known rates
41. nk samples should show no DNA pattern other than that of the internal size standard Negative controls or reagent blanks showing unexplained extraneous DNA could indicate contamination Analysts should closely evaluate blank samples including assessment of peaks under the established threshold If there is a discernable pattern of allelic activity that cannot be attributed to a spike pull up or other artifact the analyst should troubleshoot the problem and follow the procedures established by the laboratory Read more about detecting and preventing contamination in the DNA Amplification PDF file 32 57 STR Data Analysis and Interpretation for Forensic Analysts All mp Neg PP iva Amp Neg PP Pref ler Phus vi E geram Js 2n 130104 Sai Ang ALLAmp Neg PP iva Amp Neg PP 164 200 EL All amp mp Neg PP fsa Amp Neg PP Profiler Phe vl E tit E 90 mm 300 12004 3004 a0 Above can be seen the blue green and yellow electropherograms of a negative control The raw data below should also be evaluated the primer peaks at the beginning of the run verify that an actual negative control was run and not just an empty injection 33 57 STR Data Analysis and Interpretation for Forensic Analysts a GeneScan 3 7 AT MA M P EBLAHE 111005 PP Iza 1800 E 3400 3000 EJ 4800 000 p a EEUU EPI aT n F I Se a n ie n m i er Qn So ai iam EMT NN o Mie x yee l Mim Ramcena7 a0 oe
42. nterpretation are 1 Assess the internal size standards ISS allelic ladders and controls 2 Assess each sample for the presence of extraneous peaks and determine if they may interfere with the interpretation process 3 Assess the data from each sample Step 1 Internal Size Standards and Allelic Ladders Commercial kits for short tandem repeats STR typing include allelic ladders and internal size standards ISS that are added to each sample Read more about capillary electrophoresis in the Amplified DNA Product Separation PDF file e Each sample from a run or gel should be assessed to determine if the ISS peaks have been called correctly In general the peaks or bands from an ISS are uniform in size or intensity Lack of uniformity or miscalled peaks can indicate problems with the sample injection and or run Below are examples of good and bad internal size standards 30660 150 180 200 130 300 340 350 100 75 2068 10004 S000 3000 EO Above can be seen an example of a good internal size standard Compare this to a miscalled ISS below Note that the first peak has not been called and normal peak calls have begun with the second peak from the left 28 5 STR Data Analysis and Interpretation for Forensic Analysts 20680 E 160 10p 138 150 3nn ago 340 fh 20880 10004 lpoc aa Bedian iL n ui i mA n PE Tr e E METER AL ann 000 EX Bel
43. ntitled Display 4 S le x Fie Edit Project Sample Settings View Windows Help 8 x 150 200 250 300 E STR Data Analysis and Interpretation for Forensic Analysts A 6S500 nalysis gsp Analysis Range Size Call Range C Full Range C Full Range i This Rar 2 Data Points f This Range Base Fairs Start aun Min 5 Stop 6500 ha ax Bon Size Calling Method C 2nd Order Least Squares C 3rd Order Least Squares C Cubic Spline Interpolation Local Southern Method C Global Southern Method Data Processing Smooth Options C None Light Heavy Peak Detection Baselining Peak Amplitude Thresholds Baseline Window Size Auto Analysis Only Size Standard G5 500 All szs wr Min Feak Half Width Polynomial Degree Peak Window Size Slope Threshold for Peak Start Slope Threshold for Peak End Size Calling Methods The analyst selects one of four possible size calling methods in the analysis parameters utilized by GeneScan 1 Local Southern 2 2nd or 3rd Order Least Squares 3 Cubic Spline 4 Global Southern method The Local Southern method for size calling is the most commonly used algorithm in forensic DNA analysis It determines the sizes of fragments by using the reciprocal relationship between fragment length and mobility The unknown fragment is surrounded by two known sized fragments above and one below then two below and one abov
44. ok at 114 00 4 0 50 bp 2 74 in blue a 13 X Highest peak at 11 00 0 50 bp 2 67 in blue 14 X Highest peak at 122 00 0 50 bp 22 71 in blue f 15 X Highest peok at 126 00 2 0 50 bp 2 76 in blue 15 2 X Highest peak at 128 00 2 0 50 bp 2 7 amp in blue 16 X Highest peak at 130 00 0 50 bp 2 56 in blue Check GS5 0 Faz am 310 Make Table 37 7 Make Table Make Allele Table Hake CODIS Table cures Hake CODIS Mixture Table oe Kazam 20 filter 410 Hake 1377 Heke Wake Allele Table Cues Make CODIS Table Cul ps a ere Hake CODIS Hixture Table O7 Kazan 204 filter Diit ow Macro Kazam Find ladder in sample info in blue dye lanes Run macro OCalculate D3S1358 offsets Run macro OCalculate vWA Offsets Run macro OCalculate FGA Offsets Find Oladder in sample info in green dye lanes Run macro OCalculate AMEL Offsets Run macro OCalculate D8S1179 offsets 45 57 STR Data Analysis and Interpretation for Forensic Analysts Run macro OCalculate D21S11 Offsets Run macro OCalculate D18S51 offsets Find Oladder in sample info in yellow dye lanes Run macro OCalculate D5S818 OffsetsO Run macro OCalculate D13S317 Offsets Run macro OCalculate D7S820 Offsets Clear Labels Select all categories Unmark selected categories Select category D381358 Mark selected categories Select blue lanes
45. on should be reevaluated If this problem is not due to too much DNA it may be necessary to run a new matrix and apply it to the sample A signal from a locus labeled with blue dye for example might mistakenly be interpreted as a yellow or green signal thereby creating false peaks at the yellow or green loci Pull up can usually be identified through careful analysis of the position of peaks across the color spectrum but there is a danger that pull up will go unrecognized particularly when the result it produces is consistent with what the analyst expected or wanted to find Stutter Stutter Stutter is a by product of the amplification of STR loci whereby a minor product one repeat smaller than the primary allele is generated Sequence analysis of stutter products of STR loci has shown that the product is missing one core repeat unit relative to the main allele 02 Although the mechanism is not entirely understood stutter occurs in a reproducible and predictable fashion The proportion of the stutter product relative to the main allele percent stutter is measured by dividing the height or area of the stutter peak by the height or area of the main allele peak 01 Typically stutter is affected by e The repeat unit length 2 base pair repeats have higher stutter than 3 basepair etc e The degree of homogeneity of repeats the more homogenous the higher the sutter e The length of the allele within a locus the larger the alleles h
46. ory guidelines will evolve as the collective experience of the laboratory and the forensic science community grows Interpretation guidelines provide a framework for the objective and consistent interpretations of results Objectives Upon successful completion of this unit of instruction the student shall be able to e Describe the factors that can influence the output from instruments used in DNA analysis e Describe controls and other techniques used to validate instrument output e Compare methods used to evaluate data and recognize analysis artifacts e Explain methods used to analyze data from single source and mixed source samples Overview Interpretation of genotypes allele calls 1s based on a pattern of peaks or bands on an electropherogram or gel A peak or band is a visual representation of a DNA fragment e n capillary electrophoresis CE a peak on the electropherogram rises sharply from the baseline has smooth sides and is symmetrical in shape e For gel based systems a band on the gel or gel image is distinguishable from the background and defined within a gel lane Read more about capillary electrophoresis in the Amplified DNA Product Separation PDF file Gel based systems unlike CE allow analysts to visually compare alleles without a software program However most laboratories use software programs for both CE and gel based sizing 27 57 STR Data Analysis and Interpretation for Forensic Analysts The steps in data i
47. otic and eucaryotic DNA polymerases Nucleic Acids Res 16 20 9677 86 Butler John M and Dennis J Reeder 2006 NIST standard reference database SRD 130 Variant allele reports http www cstl nist gov div831 strbase var tab htm accessed August 30 2006 Butler John M and Dennis J Reeder 2006 NIST standard reference database SRD 130 Apparent mutations observed at STR loci in the course of paternity testing http www cstl nist gov div83 1 strbase mutation htm accessed August 30 2006 Chakraborty R and D N Stivers 1996 Paternity exclusion by DNA markers Effects of paternal mutations J Forensic Sci 41 4 671 77 Budowle B 2000 STR allele concordance between different primer sets A brief summary Profiles in DNA Promega publication 3 3 10 11 http www promega com profiles 303 ProfilesinDNA 303 10 pdf DNA Advisory Board 1998 Quality assurance standards for forensic DNA testing laboratories Forensic Science Communications 2 3 http www fbi gov hg lab codis forensic htm National Research Council Committee on DNA Technology in Forensic Science 1996 The evaluation of forensic DNA evidence An update Washington D C National Academy Press STR Data Analysis and Interpretation for Forensic Analysts Online Links e National Institute of Standards and Technology NIST http www cstl nist gov div831 strbase Works Cited amp Online Links 1 Scientific Working Gro
48. ourage adenine addition Read more about PCD in the Crime Scene and DNA Basics for Forensic Analysts PDF file Note Samples displaying A can be diluted with buffer and reextended in the thermal cycler Microvariants and OL Alleles Allelic ladders represent the most common alleles at each locus and were established through the evaluation of data from several hundred individuals Alleles within the STR loci are known to vary greatly between individuals and the kit ladders do not represent all possible types Alleles that size outside allele categories represented in the ladder are often referred to as off ladder OL alleles LAQOEAR Fira J Bh LADDER P p 3p e Tp up Tp T8 D sampe Pisa 7 Bee Sampie LP oLa t pE que gen In general proprietary sizing software is designed to designate allele types if the allele size is within one of the allele categories defined by the ladder The software designates an allele that falls outside of these allele categories as off ladder unless the manufacturer has established virtual allele categories Virtual alleles are 21 57 STR Data Analysis and Interpretation for Forensic Analysts alleles that have been previously characterized but are not present in the allelic ladder For all defined virtual alleles the software designates the allele type rather than designating it as an off ladder allele It is not unusual in forensic autosomal STR testing to see microvariants
49. ow is an example of a bad injection as evidenced by the imbalanced peaks on the ISS anon S000 2000 1000 4 75 100 139 450 160 200 300 340350 4D gi X m waar 2m aaron ioe IP TOME E NENNEN A Em anno S000 EDO The ISS is particularly useful in determining the precision of a capillary electrophoresis run For example using Applied Biosystems software the 250 peak is not assigned in the ISS and the size of this peak in each sample can be used to determine the in run precision Temperature fluctuations can cause the in run precision to exceed 1 base pair and evaluation of the ISS can assist analysts in identifying this issue 29 57 STR Data Analysis and Interpretation for Forensic Analysts A3DAF QEB PP fsa DAF QEB PP Prefiler Ptus vl E A3DAF QEB PPI fsa DAF QEB PP Profiler Phus vl m Bl amp mp POS CF fsa amp mp POS CF COfle vl Ir GeneScan 500 Size Standards are routinely used with Applied Biosystems methods The 250 base pair peak has been shown to have abnormal migration of double strands resulting from incomplete separation under denaturing conditions The 250 base pair peak is not defined for sizing purposes but can be evaluated to assess in run precision In order to accurately size fragments in run precision is expected to fall into a size window of one base pair Temperature fluctuations in the laboratory may cause precision to exceed a one base pair window e Allelic ladders
50. ozygote imbalance may be observed in STR analysis due to the effective low copy number of DNA templates in degraded DNA The amplification process can produce many copies from a relatively low quantity of DNA If too small a quantity of DNA is introduced at the beginning of amplification it is possible that heterozygous alleles may amplify differentially The first few cycles of the amplification process are extremely important if imbalanced amplification occurs it will result in stochastic effects An analyst can assess the data by calculating the heterozygosity of alleles If the heterozygosity is less than 70 this could indicate a mixture and or stochastic amplification View an animation that shows an example of the stochastic effect Allele Dropout Allele dropout occurs when a sample is typed and one or more alleles are not present This can be due to a variety of factors ij e The initial input quantity of DNA is too low resulting in the failure to amplify one or more alleles in the sample e A mutation in the primer binding site is present which causes a failure in the amplification of the allele e An allele sizes outside of the normal calling range for a particular locus and goes undetected 200 i15 250 zb A ae Decay curve 23 5 STR Data Analysis and Interpretation for Forensic Analysts Mutations A mutation occurs when DNA is damaged or changed anywhere along the DNA strand Mutations that occur in primer bi
51. pillary electrophoresis e Bands slab gel electrophoresis D3 1358 100 1200 S00 400 The DNA fragments are sized which includes an indirect assessment of quantity present peak area height or band density and genotypes are assigned The conversion of sized DNA fragments to genotypes is the standardization between all forensic DNA laboratories for comparing data and is essential for laboratories utilizing CODIS to compare profiles Read more about CODIS The steps for converting fluorescent data peaks into allele calls are shown below with the corresponding software noted to the right of the specific steps QL 2 57 STR Data Analysis and Interpretation for Forensic Analysts GeneScan or FMBIO T Analysis Internal sizing Ai software standard e g GeneMapper GS500 ROX ID software Allelic ladder gt Comparison to sample Y Allelic Ladder Genotyper T z STaR Call Genotype software Assignment to Alleles Data Review by Analyst Examiner Expert Systems Under Development Confirmation of eg True Allele IResults by Second Analyst Examiner View an animation about the basic components of an electropherogram GeneScan lt a Bisa GeneScan gt Ti LF ag ooo A Bader GeneScan is a sophisticated software program that converts raw data to analyzed data through the application of a size standard a matrix file and specific parameter settings
52. re printable When switching from the align by base pair to the align by data point views for the x axis the labels associated with the peaks are now retained in both views Allelic Ladder Genemapper ID uses the average sizes of the alleles between multiple run allelic ladders to determine the allelic bin offsets whereas Genotyper uses a single run ladder sample An important feature of this software which is unique to the first release and carried through to subsequent versions is the use of PQVs process quality values The PQV system is the first step in the direction of expert systems analysis User defined process quality values generate notifications to help provide confidence in allele calls and to aid in troubleshooting It is important for analysts to read about and understand their 10 57 STR Data Analysis and Interpretation for Forensic Analysts purpose and function in the user s manual Analysts should experiment with settings to ensure that notifications correspond with laboratory procedures Prior to implementation laboratories must conduct proper validation 02 06 Features and Procedures Yfiler Kit Features have been added in GeneMapper JD Software v3 2 to facilitate analysis of the AmpF STR Yfiler PCR Amplification Kit Features and Procedures v3 2 Feature Procedure Description New feature Allele calling In GeneMapper D Software v3 1 parameters for new marker allele calling parameters were on
53. s All loci should be evaluated in interpreting profiles View an animation about how profiles are derived from electropherograms In general a homozygous locus will show a single peak that is approximately twice the height of alleles seen at a heterozygous locus within the same dye color This is due to the doubling of the signal from two alleles of the same size If the peak height is not approximately twice that of alleles seen at a heterozygous locus this may indicate a null allele or a primer binding site mutation at this locus 36 57 STR Data Analysis and Interpretation for Forensic Analysts The peak height percentages may vary from locus to locus and should be assessed based on the laboratory s interpretation procedures Low peak height percentages may indicate a mixed DNA sample or mutation at a specific locus Mixtures The interpretation of mixtures can be a complicated process Laboratories should conduct sufficient validation studies and provide thorough training to ensure that conclusions are supported by data The following may indicate a mixture e The presence of more than two alleles at any one locus e A peak in a stutter position that has a higher RFU than what would be expected based upon the established stutter percentage for that locus e mbalanced and or unexpected peak height percentages Once the determination of a mixture has been made it may be helpful to use the case information and or sample type to aid
54. s in allele designations The algorithm used for GS 3 7 1 for Windows NT the updater also tends to increase baseline noise but operating with GS 3 7 for Windows NT gave similar results for peak height as that of the Macintosh version A thorough discussion of each of the parameter settings shown above can be found in the User Bulletin of the Windows NT software for GeneScan 05 Genotyper BS slbsystems Genotyper converts GeneScan sized peaks into genotype calls using predefined macros providing defined results Genotyper uses the tabular data from GeneScan to make allele calls using the first ladder 8 57 STR Data Analysis and Interpretation for Forensic Analysts recognized by the program The two main manufacturer macros for the proprietary kits are Kazam for analysis of AmpFSTR amplification kits and PowerTyper for Promega products These macros do three things e Calculate the bin offsets alleles based on the tabular data for sizing e Filter stutter as defined in the macro e Assign the number s that represent the genotypes for the profile based on the ladder used for the sample set The macro is simply a step list of actions that are performed sequentially as defined when a particular template is launched Macros are used to check the size standard by attaching the labeled sizes for confirmation others can be written to label peaks and to set up Genotyper tables After assignment of allele labels the a
55. should be assessed to ensure that all peaks have been called correctly Ladder peaks that have not been called or have been miscalled can indicate a problem with the ladder sample injection and or run Profiler Plus allelic ladder loci D3S1358 vWA FGA 30 57 STR Data Analysis and Interpretation for Forensic Analysts WU ln Tm s s i to be mus Li om i mr EEEEE P Mr en Controls Controls are used to assess the analytical methods In general analyses include positive and negative amplification controls reagent blanks and in some instances known extraction controls and substrate controls Laboratories must develop criteria to evaluate controls In addition procedures must be in place for interpretation and documentation of control results that do not perform as expected Positive Control s Positive controls are included in most commercial DNA analysis kits used for quantitation or STR typing Applied Biosystems and Promega STR kits both include 9947A control DNA for use as a positive amplification control The control is usually amplified with each batch of samples and aids in determining the overall performance of the amplification and typing procedures 99474 is a female cell line from a 31 year old Caucasian female The cell type is B lymphocyte from a blood sample This cell line is used as a positive control in forensic DNA analysis Positive Control 9947A Profiler Plus Read more about 99
56. spicious father and the child shown in the vertical scale A somatic mutation can occur after tissue differentiation begins in an embryo s development In this case for example it is possible for the DNA profile obtained from a buccal swab to be different from that obtained from a hair or blood sample If this mutation occurs early in the embryo s development then it is more likely to be the common type throughout all of the tissues Null Alleles A null allele is an allele that is present in a sample yet is not amplified A primer binding site mutation can inhibit amplification for that allele and result in a null allele If an individual 1s heterozygous and has a primer binding site mutation for one of the alleles the individual would type as a homozygote Note The manufacturers of various STR typing kits use different primer sets If a DNA sample has a mutation in a primer binding region specific to kit A but no mutation in the primer binding region specific to kit B a rare discordance in allele calls can occur when comparing typing results produced by these two manufacturers kits 07 When comparing DNA typing results from different kits null alleles due to primer binding site mutations can result in discrepant DNA types at a particular locus It is important to understand that although null alleles are rare they must be considered when interpreting potential matches Controls Incorporating controls in STR DNA analysis is an e
57. ssential and required part of the testing process 08 09 Introducing controls at each step of the DNA process allows the analyst to identify and troubleshoot possible 25 5 STR Data Analysis and Interpretation for Forensic Analysts issues and ensure that the methods used produce accurate and reliable results Extraction An extraction blank is included in the extraction process to assist the analyst in determining if the reagents and or techniques used may have introduced contamination The extraction blank should be treated in exactly the same manner as the other samples During the amplification process two controls are used A positive control is a known DNA sample that has been previously typed and is added to the sample set The positive control verifies that the analysis processes are functioning properly Manufacturers provide positive control samples in STR kits e A negative control is included in the amplification process to assist the analyst in determining if the reagents and or techniques used may have introduced contamination The negative control should be treated in exactly the same manner as the other samples Capillary Electrophoresis Samples are typed using capillary electrophoresis Internal sizing standards ISS must be added to each sample Read more about capillary electrophoresis in the Amplified DNA Product Separation PDF file Internal size standards ISS serve two purposes e Sizes of all fragmen
58. sts problems with disassociated primer dyes can be avoided If problems persist the sample can be reamplified or a filter unit clean up step e g link to Microcon 100 can be performed Amplified fragments of DNA will attach to the membrane while the disassociated primer dyes pass through the membrane and are filtered out of the sample Spikes Spike 242 93 Spikes are narrow peaks usually attributed to fluctuation in voltage or the presence of minute air bubbles in the capillary Spikes can also be caused by crystals in the polymer and or fluorescent material in the polymer or formamide Spikes unlike other artifacts are generally seen in the same position in all colors However it is possible to detect spikes in a single color Analysts should view both the raw and analyzed data for each sample The raw data produce a non filtered view of the sample run while analyzed data can obscure detection of a spike Frequently spikes are more readily detected in raw data versus analyzed data The analyzed data provide an exact data point and base pair size for each peak Spikes that are not obscured in the analyzed data can be assigned an exact data point for each color displayed The occurrence of spikes can be minimized by following the instrument manufacturer s procedures for reagent and sample handling If spikes persist analysts may need to contact the manufacturer Frequent electronic spiking can occur due to poorly functioning ins
59. t Sample Settings View Windows Help e Sample file information e Analyzed data Analysis Parameters Analysis parameters for the GeneScan 3 7 for Windows NT are configured prior to analyzing data Two fields that are commonly altered are Analysis Range and Peak Detection 6 57 Sample File Infarmatian V Run Information User Name rooooness Eun Date Instrument ABI PRISh 310 Data Call Version ABI PRISM 310 Collection 3 0 0 Tube 0 7 Data Collection Settings Module File GS STR POP4 1 mL F md4 Matrix File CAS_hitris_O30806_310Amt Parameters GSS00 Analysis gsp Size Standard GS S00 All ses F Gel Information Total Points G46 Eun Voltage Inj Voltage Inj Duration Temperature Laser Power Gel Type Lat Murnber Thu har 09 2006 Start Time 10 48 14 Phi Eun Duration 30 bins 34 Secs volts volts Seconds E row atts Length To Detector Bea em X Sample Information Expiration Date Sample Hame F ns PP Oye Sample Info Comment p POS PP T 0 1 G RogPR Of v PEP O 0 0 0n 00 R PEP 0 0n 0 nho Analysis Records Parameters Analysis Range 3500 54805 pts Eazelined Yes Multi Coriponented Yes Data Smoothing Light Peak Detection Threshold 30 Peak Detection Min Half width 2 Palynamial Degree 3 Peak Wrin 15 Parameters Analysis Range 3500 6405 pts Baselined Yes Multi Conponented Yes Data Smoothing Light
60. tern Association of Forensic Scientists SWAFS California Association of Crime Laboratory Directors CACLD and the Bode Technology Workshop Author Debbie Figarelli Debbie Figarelli serves as DNA Technical Leader at the National Forensic Science Technology Center Debbie assists with the development of DNA training programs and participates in compliance audits of DNA laboratories Below is a screen shot of Genotyperij 2 focusing on the macro window Click on the macro labeled Kazam to view the steps of the macro as they appear in text format 44 5 STR Data Analysis and Interpretation for Forensic Analysts E Gonstypes L7 PROFILER_PLUS_ 1 gta SI Be Edt amp nsysm Categery Tobie Views Macro Window Heb Amplification Blan M f Blue Amplification Blank Amplification Blan M Green Amplification Blank Amplification Blan M Anplification Blank Amplification Blan Anplification Blank Amplification Blan Amplification Blank Reagent Blank4 10 2 Blu reagent Blank E mi T h i ie k mm PEN a m Thu E Trib T 0 D ts SS FS Fe Te s d mh je jm ies DE a F P m LH 2 40 w w 100 120 140 100 180 200 220 240 200 230 300 220 340 380 380 400 420 440 460 480 500 520 540 560 f 0351353 OL Allele All peaks tren 100 00 te 3148 00 bp 2 74 11 X Highest pesk at 110 00 0 50 bp f 2 74 in blue 12 X Highest po
61. tions The 250 base pair peak is not defined for sizing purposes but can be evaluated to assess in run precision In order to accurately size fragments in run precision is expected to fall into a size window of one base pair Temperature fluctuations in the laboratory may cause precision to exceed a one base pair window 53 57 All mp Neg PPfsa 130104 Sai ang Allamp Neg PP iva Allimp Her PP isa 1200 UH p 2 STR Data Analysis and Interpretation for Forensic Analysts Amp Neg PP Pref ler Phus vi E geram Js 2n 1680 00 m ide 206 si Above can be seen the blue green and yellow electropherograms of a negative control The raw data below should also be evaluated the primer peaks at the beginning of the run verify that an actual negative control was run and not just an empty injection 54 57 STR Data Analysis and Interpretation for Forensic Analysts a GeneScan 3 7 ATOAMP BLAHF 111005 PP fza tio i z F E P PP e ee EET il ML n mae a v INNEN EBENIS GeneScan 3 7 A10 Works Cited amp Online Links 1 Butler John M 2005 Forensic DNA typing Biology technology and genetics of STR markers 2nd ed Burlington MA Elsevier Academic Press 55 57 STR Data Analysis and Interpretation for Forensic Analysts 2 Applied Biosystems 2003 GeneMapper M ID Software Version 3 1 Human Identification Analysis
62. truments 18 57 STR Data Analysis and Interpretation for Forensic Analysts Noise Noise describes a series of non reproducible background peaks that occur along the baseline in all samples A wide variety of factors including amplified current fluctuations within the electronic circuitry air bubbles urea crystals and sample contamination can create noise If large enough close to the laboratory threshold they may be confused with an allele or mask alleles Analysts may confuse actual alleles with noise and vice versa they should be familiar with the signal to noise ratio of the instrument and or the specific data Data interpretation should include viewing both raw and analyzed data to assess the signal to noise ratio and distinguish real data from noise Noise is not reproducible one way to differentiate alleles from noise is to rerun the sample 100 200 Sieh Pull up sometimes referred to as bleed through represents a failure of the analysis software to discriminate between the different dye colors used during the generation of the data Oversaturated data can also cause the dyes to bleed over or pullup into another color If pull up occurs the analyst can inject less of the sample or re amplify the sample with less input DNA 19 57 STR Data Analysis and Interpretation for Forensic Analysts Reoccurring pull up due to too much DNA may indicate that the quantitation method or the amount of DNA used for amplificati
63. ts are established for a sample relative fragment units This is accomplished by using the ISS to establish a correlation coefficient which is used to determine the size of sample fragments e The ISS serves as an effective control and provides information about instrument run conditions For instance if all of the peaks for the sizing standard are not present it suggests a temperature run time or injection problem Laboratory temperatures can vary and fluctuations occurring during a run can affect electrophoresis Including allelic ladders with each run corrects for this issue Allelic ladders must be included in all instrument runs for the instrument s software to properly type the sized fragments for each sample Note If a laboratory experiences relatively severe temperature variation within a run it may be advisable to run several allelic ladders so that the run can be broken into smaller sizing projects Data Interpretation amp Allele Calls 26 57 STR Data Analysis and Interpretation for Forensic Analysts The interpretation of results in casework can be one of the most difficult aspects of forensic DNA analysis and is a matter of professional judgment and expertise Q1 It is not possible or practical to develop interpretation criteria that cover every circumstance Laboratories should develop interpretation guidelines that are based on validation studies literature methodology and experience It is expected that laborat
64. uld leave a very low percent contribution for Genotype 2 e Scenario 6 See scenario 3 as this 1s the reverse The percent contribution would be Genotype 1 1201 794 1201 x 100 60 Genotype 2 794 794 1201 x 100 40 e Scenario 7 See scenario 4 as this is the reverse In this scenario 11 is a shared allele and it is assumed that the contribution is equal to that of the 9 allele which is 794 RFUs Genotype 2 This would leave Genotype 1 contributing 407 RFUs The percent contribution would be Genotype 1 407 794 1201 x 100 20 Genotype 2 794 794 794 1201 x 100 80 Based on these seven scenarios e Scenarios 2 4 and 7 are possible e Scenarios 3 and 6 are less likely e Scenarios and 5 are not likely Reporting Guidelines A report contains the conclusions that an analyst has made based on the scientific data and established interpretation procedures An inclusion or match is reported when all the loci from which a result is obtained match between a questioned sample and a known sample With the exception of paternity testing if the result for even one locus does not match and is discordant an exclusion is declared A minimum of a two locus exclusion is needed in order to declare an exclusion for paternity Read more about the rules for parentage and relatedness in the Population Genetics amp Statistics PDF file View an explanation of a match Exclusion Non match An
65. up on DNA Analysis Methods SWGDAM 2000 Short tandem repeat STR interpretation guidelines Forensic Science Communications 2 3 http www fbi gov hg lab fsc backissu july2000 strig htm 2 Gill P 2002 Role of short tandem repeat DNA in forensic casework in the UK Past present and future perspectives Biotechniques 32 2 366 8 370 372 passim 3 Buckleton John Christopher M Triggs and Simon J Walsh eds 2005 Forensic DNA evidence interpretation Boca Raton FL CRC Press Online Links e 9974A http ccr coriell org nigms nigms cgi display cgi GM09947 57 57
66. ysts Find Oladder in sample info in green dye lanes Mark selected dye lanes Find Oladder in sample info in yellow dye lanes Mark selected dye lanes Select blue lanes Show the plot window e 34g 390 ay 100 75 2000 10004 Ee ee V o a A Meneame Te VT d ania salg Zii Above can be seen an example of a good internal size standard Compare this to a miscalled ISS below Note that the first peak has not been called and normal peak calls have begun with the second peak from the left 51 57 STR Data Analysis and Interpretation for Forensic Analysts 206004 150 160 100 13B ang 30g 340 E fh 20690 4 eee i l T ttd bm E sad m NE ee eee maiis P UM i ano 000 Ex Below is an example of a bad injection as evidenced by the imbalanced peaks on the ISS 4000 SOU 4 anon AOU a 100 139 150 160 200 300 340350 4p db EL LA LIU A Ll NENNEN UNE 4000 50 PTT 52 57 STR Data Analysis and Interpretation for Forensic Analysts A3DAF QEB PP fsa DAF QEB PP Prefiler Ptus vl E A3DAF QEB PPI fsa DAF QEB PP Profiler Phus vl m Bl amp mp FOS CF fsa Amp POS CF tOfile vl E GeneScan 500 Size Standards are routinely used with Applied Biosystems methods The 250 base pair peak has been shown to have abnormal migration of double strands resulting from incomplete separation under denaturing condi

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