grafgen User's Manual
Contents
1. 4b 107 00 TG 117 00 TG 12 00 CT 121 00 CT 41 00 TG Figure 1 A precision graphical genotype In order to draw the Precision Graphical Genotype of an individual grafgen scans the genome at equally spaced points and infers the genotypes of these points using information on e the genotypes of markers linked to the scanned point e the breeding scheme of the pedigree e the genotypes at markers of the individual s ancestors The computations performed by grafgen to infer the genotype of these scan points are obtained through the use of the core computation function of the program mdm Servin et al 2002 This User s Manual is aimed at describing the way grafgen works section 3 Com putations Principle how to make it work with your particular data section 4 How to Write Input Files what kind of representation you can obtain using grafgen section 5 Outputs and how to customize its behaviour section 6 Customizing graf gen behaviour 2 Technical Requirements and Installation 2 1 Getting Grafgen grafgen is freely available at http moulon inra fr fred grafgen You can either download the C source code in order to compile grafgen for your system or download an executable for your operating system Linux or Windows 2 2 System Requirements grafgen uses the GD Library version 2 http www boutell com gd which must be in stalled on the system in order to run the program The win2. When analysing a population of offspring grafgen can be run to obtain graphical representations of each individual However it is sometimes interesting to display data concerning the population as a whole This is for example the case when working on a segregating population for marker mapping and QTL detection By plotting the mean frequency of an allele in the population it is possible to assess graphically the regions of 10 the genome which show a distorsion of segregation This feature is useful for example in a population that has been selected on the basis of the phenotypes of the ancestors Indeed it is possible a posteriori to assess the genome regions that have been selected as they will present a distorsion of segregation with a highest frequency of the favorable allele in the population 9 00 umc109 6 20 npi253a 18 30 umc113a 22 00 sht 26 60 bz 46 80 umc105a 48 00 bnlg244 55 50 phi130 55 50 wxi 61 80 pepi 62 70 umcsl 77 80 82 90 sus umc95 115 70 csu93a 123 20 127 90 br l14 ass12 Figure T Threshold representation of genotype 0 0 red 0 1 green and 1 1 blue at a 0 8 cutoff The figure 6 represents the mean frequency of one of the segregating alleles in an F3 population derived from two inbred lines The offspring is composed of 60 individuals which genotypes at markers have been cho sen arbitrarily The chromosome shows zones of normal frequency orange zones zones of high a
3. for pedigrees involving two founders The codsys file contains the correspondence between OG and TG see 3 1 It allows to work with any genotype coding system used in a particular experiment The codsys file is of the form nball 0 to 1 Jo1 to2 Jo2 1 hilti Molti ven k teder ik2 jk2 a5 n in1 Jni tn2 Jna The first line of the file only contains the maximum number nball of alleles per locus that is the number of different founders in the pedigree The alleles are indexed from O to nball 1 The next lines define the OG codes used to describe individuals in the other input file Each OG is described by the list of its corresponding TGs Each of these lines contains first the OG code say k then the corresponding couples x jx 1 1 1 Nol A couple ix 1 jr list the maternal paternal allele defining the TG corresponding to the OG k N is the number of TG corresponding to the OG k For example an heterozygote for alleles 0 and 1 which gametic phase is unknown and arbitrarily coded 1 will be described by the line 1 1 0 0 1 Appendix I contains an annotated example of codsys file in a biallellic breeding scheme 4 2 Writing an infile The infile contains all the information related to the breeding scheme once the coding system is defined The file is composed of different sections which we describe in turn The structure of the file and the syntax of the lines must be matched exactly including line br
4. This input file describes a pedigree spanning three generations GENER 3 and pro ducing two offsprings OFFSPRING 2 The program will compute the probabilities of three genotypes along the genome EVALUATED GENOTYPES 3 The genotypes codes are provided in a file called codsys ex which is shown in Appendix I The first generation of the pedigree is an hybridation between two founders G1 hyb followed by two generations of selfing The two founders of the pedigree are inbred lines e the first founder is of genotype 0 at all markers column MAT1 and the second founder is of genotype 2 at all markers column PAT1 17 e the two founders are also of genotypes 0 and 2 respectively between the markers t e at any additional locus This is specified in the additional locus information at line 14G1 02 The additional locus information is only known for the founders and is missing at other generations genotype code 5 at generations 2 and 3 The program will compute the probabilities of genotypes 0 1 and 2 in the offsprings At generation 2 of the pedigree an F1 hybrid is obtained this individual is heterozygote at all loci column MAT2 This F1 is selfed to produce an F2 at generation 3 This F2 was not genotyped column MAT3 is filled with missing genotypes genotype code 5 Finally two F3 offsprings are obtained by selfing the F2 The genotypes at markers of the offsprings are indicated in columns OFF1 and OFF2 The markers ar
5. the codsys file in appendix I The t option is mandatory here to indicate the genotype to plot e Allele Dose grafgen T 3 t 0 produces on output chromosomes colored ac cording to the dose of allele 0 Note that in this case 0 does not mean the same thing as in the T 2 context OG vs allele index The t option is mandatory here to indicate the allele to plot e Allele Frequency grafgen T 4 t 0 will produce a single output file as shown in figure 6 representing the frequency of allele 0 in a population The t option is mandatory here to indicate the allele to plot e Zones of high probability grafgen T 5 t thresholds in will produce a rep resentation bringing out the zones of highest probabilities of given genotypes Using this option requires to create a simple input file see 5 2 4 for an example which name as to be given using the t option thresholds in here The t option is mandatory here to indicate the file to use Project Title P option The P option can be use to change the prefix used in the name of output files The command line is then grafgen P MyPrefix The name of output files will be prefixed with the supplied prefix The default prefix is pgg 13 References e Hospital F Dillmann C and Melchinger AE 1996 A general algorithm to compute multilocus genotype frequencies under various mating systems Comput Appl Biosc 12 455 462 e Servin B Dillmann C Decoux G
6. G at each generation are converted into all possible sets of corresponding TG Then the probabili ties of transition between all possible sets of TG are computed according to the recursion equations of Hospital et al 1996 Finally these probabilities are summed to provide the probability of the OG at the next generation 3 2 Breeding Scheme grafgen computes expected frequencies of offspring individuals issuing from a breeding scheme The breeding scheme is a succession of generations of mating between ancestors For each generation of the breeding scheme the input consists of e The genotypes of the ancestors possibly missing or unknown e The mating system used to mate ancestors grafgen can cope with different mating systems hybridization backcrossing selfing fullsib mating or doubled haploids It can cope with some particular case of random mating when all individuals in the population at a given generation are mated at random unconditional on their marker genotypes i e the corresponding ancestors genotypes for this generation are completely unknown 3 3 Scanned Point In order to infer the genotype at each scanned point grafgen needs to include an addi tional locus on the genome positionned on the scanned point grafgen first computes the expected probabilities of the genotype at marker loci m Fm Then grafgen includes the additional locus non marker locus X at the position of the scanned point This allows to o
7. and F Hospital 2002 MDM a program to compute fully informative genotype frequencies in complex breeding schemes J Hered 93 227 228 14 APPENDICES Appendix I Example of a codsys file for a biallellic breeding scheme 0 0 0 1 1 0 1 1 0 0 0 1 1 0 0 1 1 0 1 1 0 0 0 1 1 0 1 1 0 1 1 0 NOD PS WN Hr ON OG codes 0 and 2 correspond solely to genotypes homozygous for allele 0 and allele 1 respectively Code 1 corresponds to an heterozygous locus which gametic phase is unknown If the gametic phase is known the different heterozygous loci can be coded differently as exemplified by the codes 6 or 7 Using codes 6 or 7 increases the precision in the calculations when combining genotypes over all loci if the phase is known for example when the genotype is an F hybrid resulting from the cross between two completely homozygous parents Codes 3 and 4 correspond to the case of dominance of allele 0 or 1 respectively Finally code 5 corresponds to completely missing data 16 Appendix II Example of an infile GENER 3 OFFSPRING 2 EVALUATED GENOTYPES 3 CODING SYSTEM FILE codsys ex MATING SYSTEMS FOR EACH GENERATION G1 hyb G2 self G3 self ADDITIONAL LOCUS INFORMATION G1 02 G2 5 G3 5 0 012 GENETIC MAP AND MARKER GENOTYPES CHROM MK_NAME MK_POS MAT1 PAT1 MAT2 MAT3 OFF1 OFF2 1 mi 0 0 0 2 1 5 0 1 1 m2 50 0 0 2 1 5 0 2 1 m3 100 0 2 1 5 0 2 2 m4 0 0 0 2 1 5 2 0 2 m5 75 0 0 2 1 5 2 0
8. btain the joint expected probabilities of the genotype at markers plus the additional locus Fm x Finally the conditional probabilities P x where x is the position of the scanned point of genotypes at this additional locus given the genotype at markers are computed as F m X m It is possible to compute this probability for more than one genotype at the scanned point grafgen will allocate in turn the different possible genotypes to the additional locus and compute Fm x for each of those grafgen can use all the information on the breeding scheme to infer the probabilities of different genotypes at a scanned point When doing the genome scan grafgen will change the position of the additional locus according to the step defined see section 6 and compute the conditional probabilities on each of the scanned points Pala 4 How to write input files The examples of input files provided in the grafgen package can help you to write your own input files see the examples directory grafgen gathers information on the breeding scheme from two input files The first herein called codsys file is the file containing the coding system The second file herein called infile contains the detailed description of the breeding scheme 4 1 Writing a codsys file We explain below how to write your own codsys file but in most cases you can use the codsys file provided with the grafgen package i e the file codsys ex in the examples directory
9. can only a segment of a given chromosome for example in par ticularly interesting regions introgressions QTL locations This option is con ditionned on the previous declaration of a chromosome to scan c option The segment is defined by the beginning value b option and the ending value e op tion For example the command line grafgen c 2 b 10 e 40 will scan the chromosome 2 at locations ranging from 10 cM to 40 cM Computation Step x option By default grafgen will compute the conditional prob abilities of the different genotypes every centiMorgan This behaviour can be changed by using the x option to change the step used for the computations The step is given in centiMorgans Hence the command line grafgen x 10 will perform a scan every 10 cM This option allows to reduce the time needed for the computations if using a large step e g 10 centimorgans or to increase the precision on the genomic composition estimate if using a small step e g 0 2 cM Marker Information m option The program computes genotypes probabilities con ditional on marker information Generally the more markers are taken into account in these computations the more precise are the probabilities estimates The m option al lows to define the number of markers to be taken into account for the computations The argument given to this option is the number of markers to be taken into account on each side of the scanned position For exampl
10. dows library is provided in the grafgen package For linux this library is included in all major Linux distributions and must be installed prior to running grafgen 2 3 Installation Executables The executables pre compiled binaries are in the binaries directory in cluded in the grafgen package In this directory chose the sub directory correspond ing to your operating system and follow the instructions in the file INSTALL txt Compiling from source The source code of grafgen is distributed in the package In structions for compiling grafgen are given in the file COMPILING txt located in the source directory If you successfully install grafgen on your system we would be happy if you let us know by e mail to grafgen moulon inra fr 3 Computations Principle Before drawing the Precision Graphical Genotype of an individual grafgen infers the genotype at each scanned point on the genome This inference is based on the computation of the probabilities of all possible genotypes at the scanned point conditional on pedigree information i e genotype at markers breeding scheme and ancestors genotypes These probabilities are computed using the core computation function of the mdm program previously developped in our lab If you want to learn more about mdm you can visit the mdm web site at http moulon inra fr fred mdm This section is aimed at describing the way grafgen performs its computations Al though understanding how the pr
11. e located on two chromosomes 1 and 2 The first chromosome has three markers ml m2 and m3 at positions OcM 50cM and 100cM The second chromosome has two markers m4 and m5 at positions OcM and 75 cM 18
12. e the command grafgen m 1 will perform computations conditional on the genotype at flanking markers only one on each side of the scanned position this is the default behaviour Note however that increasing the number of markers to be taken into account will increase the computation process exponentially 12 6 2 Graphics The graphical options allow to define the representation that grafgen will produce Ouput Format f option The option f allows to define the type of format to be used for output described by two strings jpg or png Hence the command grafgen f jpg will produce a file in jpeg format The default format is png Information displayed T t options The T option is used to define the type of representation that grafgen will produce on output For some of these options a second argument is needed and must be given to the program using the t option e No Output grafgen T 0 leads to performing computations and exiting without producing any picture e Genetic Map grafgen T 1 leads to produce a picture of the genetic map This is the default behaviour Thus the command grafgen infile or grafgen T 1 infile provides a graphic representation of the genetic map in a file called pgg_map png In this case no computation is performed e Conditional Probability grafgen T 2 t 0 produces on output chromosomes colored according to the probability of being of genotype code 0 e g 0 0 as defined in
13. eaks and blank spaces If not the program will not work and return error messages Appendix II gives an example of infile corresponding to a simple breeding scheme leading to an F3 population with two offspring studied The codes used to describe individuals are the same as in the codsys file in Appendix I 4 2 1 General Parameters The first 4 lines of the infile describe the constant parameters of the breeding scheme the number of generations GENER the number of individuals in the final population OFFSPRING and the number of genotypes to allocate in turn to the additional locus in the offspring EVALUATED GENOTYPES i e the numbers of genotypes at the scanned point for which you want to compute P x Finally this section contains the name of the codsys file CODING SYSTEM FILE include its full path if the file is not in the working directory 4 2 2 Mating Systems The section MATING SYSTEM FOR EACH GENERATION of the infile allows to describe for each generation the mating system used to mate ancestors Each line is composed of the index of the generation noted Gn where n is the generation considered followed by the type of mating system The mating systems are described by keywords that grafgen can recognize hyb or bc are the keywords to be used for hybridization or backcross which are in fact identical self is the keyword to be used in case of selfing fs is the keyword to be used in case of full sib mati
14. first chromosome to the last locus of the last chromosome When these three columns are filled the genetic map is defined Each next column contains the genotype of an individual in the breeding scheme The columns whose headings begin with MAT contain the genotypes of maternal ancestors those whose headings begin with PAT contain the genotypes of paternal ancestors and those whose headings begin with OFF contain the genotypes of the offspring These columns must be ordered following three rules the ancestors are described before the offspring i e a column with a heading that begins with OFF is always after the columns whose headings begin with MAT or PAT the ancestors are described from the first generation to the last e g MAT1 is always before MAT2 the paternal ancestors are always described after the maternal ancestors e g PAT2 is always after MAT2 Note that only the beginning of the heading line is mandatory de CHROM The further column headers are used to keep tract more easily of the genotype data in the input file and are not used by the program 4 2 5 Important Note The breeding scheme should start from fully known genotypes including the additional locus so that all the allelic descents that follow have a common and unique starting point Otherwise all possible founders genotypes are considered equiprobable which is most likely not what you want 5 Outputs Once the input files are composed you may r
15. grafgen User s Manual May 15 2006 Contents 1 2 Introduction Technical Requirements and Installation 2 1 Getting Grafgen En WB en 2 2 System Requirements 2 2 2 2 2 3 Installation aoaaa aaa Computations Principle 3 1 Genotypes ten dy en AN a 3 2 Breeding Scheme 3 3 Scanned Point ws Em tt 84 4 0 How to write input files 4 1 Writing a codsys file 4 2 Writing an infile gt nutten a ee 4 2 1 General Parameters 4 2 2 Mating Systems 4 2 3 Case of the additional locus 4 2 4 Describing individuals 4 2 5 Important Note Outputs 5 1 Numerical Output actor 4er ats 5 2 Graphical Output 4 4 erk ze dede Bs df 5 2 1 Genotype Probability 5 2 2 Allele Dose 5 23 Allele Frequency in a Population 5 2 4 Zones of Highest Probability Customizing the Behaviour of grafgen 6 1 Computations tE ea a G2 62 AEDES ae hy ar an ek aber a _ NNNSNN PW N EN Herer eN oo a N 1 Introduction grafgen is a program aimed at representing individuals in populations issued from known pedigrees For each offspring of the pedigree grafgen uses information on mapped marker data in the whole pedigree to produce a Precision Graphical Genotype Figure 1 1a 2 3 4a 0 00 OP 3 08 zy 0 00 TG 0 00 CT 9 00 TG 16 00 TG 39 00 TG 55 00 CD 66 00 op 66 00 TG 40 10 TG 92 00 CT
16. he probability of genotype 0 0 is greater than 0 8 are to be colored in red and regions where the probability of genotype 0 1 is greater than 0 8 are to be colored in green Regions that do not match any of these criteria are to be colored in black An example of a resulting representation is given on figure 7 11 6 Customizing the Behaviour of grafgen 6 1 Computations In the examples above we have always presented figures of a single chromosome However grafgen can draw precision graphical genotypes of the complete genome or of chromosomal segments The precision on the computations of the genotype probabilities can be increased by increasing the density of the scanned points and or by increasing the amount of information taken into account to infer genotypes probabilities at a given scanned point The behaviour of grafgen can thus be customized with computation options that allow to define the range for which the Precision Graphical Genotype is to be plotted the step to use for the scan in cM and the amount of information to be taken into account Plotting Range c b e options By default grafgen will plot the Precision Graph ical Genotype on the whole genome This behaviour can be forced by using the g option It is possible to run the program on smaller segments of the genome e the c option allows to scan a single chromosome defined by its index e g grafgen c 2 will scan the chromosome 2 only e It is possible to s
17. is the list of genotypes to allocate in turn to the additional locus in the offspring in the final generation all on a single line The beginning of the line is 0 allowing to distinguish it easily from the preceding lines For each of these genotypes the program will compute the corresponding P x 4 2 4 Describing individuals The section GENETIC MAP AND MARKER GENOTYPES of the infile allows to describe the genetic map used to describe individuals the genotypes of the ancestors the genotypes of the offspring The first line capitalized words contains the columns headings Each following line describes a single marker locus The first column heading CHROM contains the indexes of the chromosomes to which belong the markers each index appearing as many times as there are mapped markers on IN B The genetic map used by grafgen is constant during the whole breeding scheme It is therefore assumed that recombination rates between loci are evaluated once either on the population studied or on another one e g if using a consensus or a joint map and that they are not re estimated during the breeding scheme the corresponding chromosome The second column heading MK_NAME contains the names of the markers The third column heading MK_POS contains the positions understood as the distance to the telomere in centiMorgans of the markers on the chromosomes The markers must be ordered from the first locus of the
18. llele frequency red zones and zones of low allele frequency yellow zones Note that in this case the color contrast around 0 5 is increased as mean allele frequencies are close to 0 5 This leads to a fastest saturation of colors toward high or low values 5 2 4 Zones of Highest Probability The graphical representation that we have presented so far are nearly con tinuous It can sometimes be useful to obtain a simpler representation of genotypes for example to sort individuals in a population according to their genotypes grafgen allows to discretize the values computed In this case the program will color in red green or blue the zones where three different genotypes have a probability higher than a given threshold The behaviour of grafgen is explicitely determined through the use of a very simple input file containing three columns On each line is given first the genotype to plot then the threshold for the probability and finally the color to allo cate to the zones where the probability of the genotype is higher than the threshold For example with this input file geno threshold color 0 0 8 red 1 0 8 green 2 0 8 blue The line beginning with a is understood as a comment by grafgen The genotype codes in the first column correspond to the codsys file in Appendix I With this input file the genome regions where an individual has a probability of being homozygote 1 1 greater than 0 8 are to be colored in blue regions where t
19. ng and random mating hd is the keyword to used in case of doubled haploids Any other word will not be understood by grafgen will bring an error message and stop the program 4 2 3 Case of the additional locus As we have seen in section 3 3 it is necessary to include a virtual additional locus positionned at the scanned point to infer the genotype of this scanned point The section ADDITIONAL LOCUS INFORMATION of the infile allows to define the genotype for the additional locus The genotype at the additional locus is typically only known for the founders of the pedigree For the ancestors generations this genotype is generally not known in which case it should be coded as complete missing data code 5 in the codsys file provided For each generation of ancestor a line is composed of the index of the generation noted Gn where n is the index of the generation as above the genotype of the maternal ancestor at the additional locus then the genotype of the paternal ancestor at the additional locus if exists Thus in the example of Appendix II as the mating system used at generation 1 is hybridization keyword hyb the line of this section of the infile contains the genotype of the maternal ancestor followed by the genotype of the paternal ancestor For generations 2 and 3 as the mating systems used is selfing each line contains only one genotype corresponding to the selfed parent Finally the last line
20. nlg244 48 00 bnlg244 phi130 55 50 phi130 55 50 7 phi130 wx 55 50 x 55 50 wxi pept 61 80 pept 61 80 pep umc81 62 70 umc81 62 70 unc81 sust 77 80 susi 77 80 sus1 umc95 82 90 umc95 82 90 umc95 115 70 csu93a 115 70 csu93a 115 70 csu93a 123 20 bn114 123 20 bn114 123 20 bnl14 127 90 asg12 127 90 asg12 127 30 asg12 61 80 77 80 62 70 82 90 Figure 4a P 0 0 Figure 4b P 0 1 Figure 4c P 1 1 Figure 4 Probabilities of 3 different genotypes in an F3 4b and Figure 4c 5 2 2 Allele Dose One way to summarize the information provided by the previous probabil 0 00 umetos ities is to plot a single graphical representation based on the dose of one 6 20 npi253a particular allele on the genome which depends on the probabilities of every genotypes TG that contains at least one copy of this allele The Figure 5 18 30 unc113a is the representation of the dose of allele q on the same data as Figures 4a 22 00 shi ae a 4b and 4c 5 2 3 Allele Frequency in a Population 46 50 umc1053 43 00 kbr lg244 0 00 umc109 55 50 phi130 on 6 20 npi 253a 61 80 pepi 62 70 umc81 18 30 umc113a 22 00 shi 77 80 sus1 26 60 bzi 82 90 umc95 46 80 Lmc 103a 48 00 bril 5244 55 50 phi130 55 50 wxi 115 70 csu93a 61 80 pep1 123 20 bnl44 62 70 coL 127 90 ass12 77 80 susi 82 90 umc95 Figure 5 Dose of allele q in an F3 individual 115 70 csu93a 123 20 bnl14 127 90 asg12 Figure 6 mean dose of one parental allele in an F3 population
21. ogram works is not necessary it can help you to write input files If you just want a description of the input files format jump to section 4 3 1 Genotypes grafgen considers individuals described by their genotypes at loci of known positions on chromosomes typically mapped marker loci In practice the genotyping of an individual produces an observation i e phenotype that poorly reflects its true genotype Indeed usually the marker phenotypes do not provide the gametic linkage phase of the chromo somes which allele originates from which parent for example in the case of a double or multiple heterozygote Furthermore genotyping data may not be fully informative because of missing or incomplete data e g in the case of dominant markers So the program distinguishes between observed genotypes OG allowing missing or incomplete genotyping data and true genotypes TG where all alleles at all loci as well as the gametic phase are assumed to be known The core computation function of grafgen uses the re cursion equation from Hospital et al 1996 which are implemented to compute frequencies of genotypes known without ambiguity i e TG However the user actually input geno types that may include missing or incomplete genotyping information i e OG Hence the program needs to know the relationships between OG and TG These relationships are given in the codsys file see section 4 1 According to the coding system O
22. raphical map as a skeleton grafgen will then paint the chromosomes 46 80 umc105a according to the information to be graphically displayed the color of a 48 0 bnlg244 point on a chromosome then depends only on the criterion used to described 55 5 phi130 the genotype at this scanned point In the next examples we show the pias oe possible ways to represent the genotype of an individual We will use the 2 umes map represented in Figure 2 as the skeleton for these representations oe ek Tip Runnning grafgen to produce a genetic map is a good way to zo test the format of your input files as no computations are performed If the program does not return any error then your input file should be correct You can also easily check that the map drawn matches ODD 115 70 csu93a 123 20 bnlid 127 90 ass12 5 2 1 Genotype Probability In some cases it is interesting to show the probability that an individual is Figure 2 Maize of a particular genotype at each position of the genome This is the case IBM Genetic for example in backross breeding where only two genotypes are possible Map of Chromo homozygous for the recipient parent allele genotype RR or heterozygous some 9 donor parent recipient parent genotype DR In this case plotting the probability of being of genotype RR allows to assess both the return to the recipient parent and the conservation of donor alleles in introgressed regions Figure 3 shows a chromosome of a BC individual carr
23. un grafgen in a terminal following the syntax grafgen options infile As the codsys file name is provided in the infile there is no need to give it in the command line The available options are described later in this manual see section 6 For a short description of these options you can type grafgen h in the terminal grafgen will then run and produce different output files which have to be read exter nally The default prefix used for ouput files is pgg but can be defined by the user with an option see below 5 1 Numerical Output grafgen writes the probabilities of all genotypes for each scanned point in a file called pgg dat or PREFIX dat This file is a CSV file and can be read with a spreadsheet program such as gnumeric or Excel or a mathematical program such as R or Splus T 5 2 Graphical Output The graphical ouput of grafgen is stored in a picture file in PNG or JPEG format A PNG file is generally of better quality but bigger than a JPEG 0 00 unc109 file Depending on the type of information you want to get from the grafgen 6 20 npi253a analysis of the data you may want to produce different type of graphical ouputs First of all grafgen can draw the genetic map of the genome 18 30 unc113a This sets the template of all other graphical representations As an example en Figure 2 gives the graphical representation of the IBM maize genetic map of chromosome 9 http www maizemap org produced by grafgen Using this g
24. ying a donor segment to be introgressed between markers bn1g244 position 48 cM and marker pep1 position 61 8 cM The figure 3 shows that as the markers umc109 npi253a and csu93a remain heterozygous DR the rest of the chromosome also remains heterozygous between the markers It can also be interesting to plot the conditional probabilities of genotypes on the genome of individuals in segregating populations used for QTL detection at each scanned position one way to perform QTL detection is to regress the phenotype of individuals on the probability of being of genotype qq qQ or QQ It can thus be useful to have a graphical representation of individuals based on their probability of being of any of these three genotypes Figure 4 shows three representations of the chromosome of a single individual colored according to the probabilities of being of genotype qq qQ and QQ respectively for Figure 4a Figure 0 00 umc109 6 20 npi253a 18 30 umc113a 22 00 shi 26 60 bzi 46 80 umc105a 48 00 bnlg244 55 50 phi130 55 50 wxi 61 80 pepi 62 70 umc81 77 80 sus1 82 90 umc95 115 70 csu93a 123 20 bnlid 127 90 asg12 Figure 3 Precision Graphical Genotype of a BC3 individual 18 30 46 80 48 00 0 00 0 00 umc109 6 20 22 00 26 60 55 50 55 50 unc109 0 00 umc109 npi253a 6 20 npi253a npi253a umc113a 18 30 unc113a 18 30 umc113a shi 22 00 sht 22 00 shi bzi 26 60 bei 26 60 bzi umc105a 46 80 ume105a 46 80 7 umc105a bnlg244 48 00 b
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