Statistical Viewer: a tool to upload and integrate linkage and
Contents
1. We have developed software to enhance the Ensembl open source software package as a private laboratory bio informatics infrastructure to assist in the identification of candidate complex human disease susceptibility genes We have improved the upload server thereby empowering laboratory personnel to add project specific data to the local DAS database for display in the context of the human genome using the Ensembl genome browser s contig view By creating an additional panel in EnsembIl s Contig View and Cyto View called Statistic View we are able to display statistical results from gene mapping experiments in the context of human genome sequence annotation Statistic View displays a plot of linkage and association statistics directly above the Overview Statistic View is fully and seamlessly integrated into the Ensembl genome browser The user can navigate the chromosome by mousing over a selection box outlined in red that directly corresponds to the one drawn by the Ensembl Page 10 of 14 page number not for citation purposes BMC Bioinformatics 2005 6 95 software in the ideogram of the chromosome This capa bility facilitates the selection of regions of the chromo some in linkage disequilibrium for easily visualization of features mapped therein that are displayed in data tracts below in the Overview This capability allows rapid screening of regions of interest to a particular study to identify genes that deserve further screeni2. fornia at Santa Cruz s Golden Path Genome Browser 9 10 All are easily queried and capable of visually pre senting overviews of the large regions of the genome while allowing the user to zoom in on an area of interest reveal ing detailed information on the numerous features mapped within Each of these has become invaluable tools in the arsenal of genetic researchers Genomic convergence We and others have embraced a multi faceted integrated approach to identify and prioritize candidate genes for complex human diseases that we call genomic conver gence 11 This approach combines the list of genes obtained two or more distinctly different methods e g gene expression and linkage analysis to obtain a list of top candidate genes Theoretically including genes iden tified by other independent yet biologically relevant lines of evidence could increase the sensitivity of the approach as well as the specificity when the genes identi fied by several approaches are giving higher priority Rationale To increase the efficiency and accuracy of the identifica tion and prioritization of candidate genes for genotyping we needed to facilitate the identification and extraction of genomic features of interest that are within linkage regions as well as fully exploit the public databases and the human genome assembly and annotation projects A strategy relying on the assignment somewhat arbitrary fitness thresholds to reduce the number of c
3. 20 as a next resort In a preprocessing step markers that may have erroneous map positions and or show inconsistent ordering when compared to other maps are flagged removed from our verified database and saved elsewhere for reference The confirmed genomic position and other information including its genetic location s is then used to populate the statistical results table in the database illustrated Figure 3 Then to facilitate the inter conversion of map locations from pre existing genetic maps and analysis into the human genome nucleotide position we have developed a web based tool called Get Map for uploading a file containing marker locations as well as their position as provided by the user This tool also exists in a stand alone version for processing batch Page 3 of 14 page number not for citation purposes BMC Bioinformatics 2005 6 95 http www biomedcentral com 1471 2105 6 95 A Linkage Table User Table Field Type Field Type linkage id int 10 unsigned user id int 10 unsigned study varchar 20 tury varchar 20 analysis varchar 20 user varchar 20 chrname varchar 0 link point varchar 20 chr start int 10 chr_end int 10 score decimal 5 3 decode decimal 6 3 marshfield decimal 6 3 link type varchar 20 B Linkage Data Sample linkage_id study analysis chr_name link_point chr_start chr end Lod HetLod decode Link_type CODFID Model A 3 D352367 1025117 1028305 0 860 1 050 2 240 dot 2
4. 4 98 08 Tatusova TA Karsch Mizrachi Ostell JA Complete genomes in WWW Entrez data representation and analysis Bioinformat ics 1999 15 536 543 NCBI Map Viewer http www ncbi nim nih gov mapview Hubbard T Barker D Birney E Cameron G Chen Y Clark L Cox T Cuff J Curwen V Down T Durbin R Eyras E Gilbert J Hammond M Huminiecki L Kasprzyk A Lehvaslaiho H Lijnzaad P Melsopp C Mongin E Pettett R Pocock M Potter S Rust A Schmidt E Searle S Slater G Smith J Spooner W Stabenau A Stalker J Stupka E Ureta Vidal A Vastrik Clamp M The Ensembl genome database project Nucleic Acids Res 2002 30 38 41 Project Ensembl Genome Browser http www ensembl org Kent WJ Sugnet CW Furey TS Roskin KM Pringle TH Zahler AM Haussler D The human genome browser at UCSC Genome Res 2002 12 996 1006 UCSC Genome Bioinformatics http genome cse ucsc edu Hauser MA Li YJ Takeuchi S Walters R Noureddine M Maready M Darden T Hulette C Martin E Hauser E Xu H Schmechel D Stenger JE Dietrich F Vance J Genomic convergence identifying candi date genes for Parkinson s disease by combining serial anal ysis of gene expression and genetic linkage Hum Mol Genet 2003 12 671 677 Kong A Gudbjartsson DF Sainz J Jonsdottir GM Gudjonsson SA Richardsson B Sigurdardottir S Barnard J Hallbeck B Masson G Shl ien A Palsson ST Frigge ML Thorgeirsson TE Gulcher JR Stefansson K A high resolution r
5. CODFID Model B a D353050 3286595 3258595 0 300 0 400 10 310 point 3 CODFID Model 3 D351 304 6911262 6911262 0 250 0 360 19 610 line User Data Sample user_ID study user 1 CGDFID Axu 2 CODFIO jstenger a CGODFIO bhauser Figure 3 Table structures for the linkage object and the user access database Part A of the figure shows that the study field serves as the key relating the User Data to the Linkage Data Also shown are examples part B of three data records that define plot coordinates along with other attributes User databases are created to allow restricted access for uploading data files and is described in the Get Map documentation file provided as supplementary material Software for viewing statistical data as 2 dimensional plots within the context of Ensembl The drawing program consists of four basic Bioperl mod ules that build on the Ensembl open source software and genome annotation system to display a linkage plot of sta tistical results that are easily uploaded by laboratory per sonnel using the upload server we devised in the context of the annotated human genome sequence These mod ules add an additional display panel Statistic View that appears automatically when the Contig View see Figure 1 and the Detailed View in CytoView see Figure 2 pages are opened However if no statistical data for any studies has been uploaded into the mySQL db for a chromosome of interest no plots are drawn but a compressed pan
6. author provided cause for action contrib uted ideas and requirements and funding Additional material Additional File 1 The source code for Bio EnsEMBL DBSQL LinkageAdaptor Click here for file http www biomedcentral com content supplementary 147 1 2105 6 95 S1 ttf Additional File 2 The source code for Bio EnsEMBL Linkage Click here for file http www biomedcentral com content supplementary 147 1 2105 6 95 S2 rtf Page 11 of 14 page number not for citation purposes BMC Bioinformatics 2005 6 95 Additional File 3 The source code for Bio EnsEMBL GlyphSet LodPlot Click here for file http www biomedcentral com content supplementary 147 1 2105 6 95 S3 rtf Additional File 4 The source code for WebUserConfig chrplot BioPerl module Click here for file http www biomedcentral com content supplementary 147 1 2105 6 95 S4 rtf Additional File 5 The source code for Bio EnsEMBL GlyphSet FineLODplot BioPerl module Click here for file http www biomedcentral com content supplementary 147 1 2105 6 95 S5 rtf Additional File 6 The executable BioPerl modules and documentation can be decompressed with either the GNU Free Software Foundation unzip command 36 in UNIX or the WinZip Windows archive utility WinZip Computing Inc 37 in an MS Windows OS Please see the respective web sites that are referenced for additional details on acquiring and using these com pression util
7. defines the region from which linkage data will be retrieved and returns the records from the linkage objects that are mapped to the chromosome between the coordinates within the bound ary of the red box that are displayed in the detailed view below Finally the plot image was scored into the Ensembl Contig View and Cyto View by modifying the Contig and Cyto view code so that the linkage plot is displayed into the Ensembl Contig View Figure 1 is a screen shot of the Ensembl Contig View web browser running off of our local server that illustrates the Statistic View panel with a plot comparing lod and hetlod scores against their corresponding genomic location Fig ure 2 similarly illustrates the incorporation of Statistic View into Ensembl s CytoView Note how the graph in Figure 1 features data points interconnected by dotted lines while that in Figure 2 shows solid lines The database table provides a field called link_type that allows a statis tical analyst to specify the display to quickly allow one type of analysis such as single point from another such as multi point when a convention is adhered to Although Statistic View is an invaluable tool for surveying chromosomes for interesting genomic features in linkage peaks derived from a genomic screen it is of limited use in fine mapping and association studies due to insuffi cient resolution at the chromosomal level to see the desired features as the density of markers increases T
8. ht LTGMS NM_o24s25 cPxM LGNRH2LC20orf194 LGFRA4LOSN1YG LTGMSL NOLSA CMRPS26 LATRN ADANSS LRNF24 LcNRPB EBFS LOST LSLC4A11 Lon Le2tort29 tmc2 c20orfi i LYS52_HUMAN LHSPA126 LFTLL1 L IDH3E Laup Lagecz1i LOSHH34 LRN37_HUMAN C20orf27 Le20or s1 C200rf 116 Lc20orf28 Lupsis ITPA LCENPB LPseudogen LeDC256 LNM_020746 LPANK2 Di11718 Dil1720 Tetraidis0 HexaSi77 Dili xa 185 ONACcontigs n l Ensembl Genes Lenox LPDYN LADRALD LSTK35 Tri9402 Tetraltis Tri9416 Tetraiti92 HexaS172 Di11723 Tri9417 Tetrai4195 Uninterrupted ARMs Hexa173 Di1i724 Triseis Hexad183 Hexadi174 Di11725 Hexad180 Tetralti96 Tri9419 4 00 Mb Tri94 08 Stat Score MLOD Caucasian MLOD African American 5 00 Mb l Tetral4i93 Tetralt19s LPRNP LPRND LNM LRASSF2 LSLC23A1 LPseudogene MLOD North AmericantALL Di11737 Tetrai 208 Hexadi93 Tetral42id Tetralt203 Tri9423 Di11739 Tetralt213 l l Hexad 188 Tetrai 207 Dili740 Dili743 Tetrai42is Tetral 202 Tetral4206 Hexad192 Tetrai 211 Tetrai 2i Tetral 201 Di11738 Hexadi91 Di11742 Tetral4212 I 1 Lc2dor 30 LOSNSRE NH_152504 4C200r 42 LPCNA LUBE2D3 KES4 _HUMAN CHGB NOVEL cos2 GPR73L1 NH_015939 LOSN2B6 Lycns Pseudogene Lc2tor 155 Lo2torf 75 177549 l Di11732 Hexad190 Di1i741 Di
9. in the linkage plot The boundaries of the region selected in Statistic View directly correspond to the selection box in the ideogram and the physical map position that is denoted in bps in the Detailed View The selection box also correctly corresponds with the enlarged box that is dynamically drawn in the overview As with the corresponding selection box in EnsembIl s other display panels in Contig and Cyto View the width of the selec tion box in Statistic View can be altered with a mouse or a similar input devise to select either a larger or a nar rower region of interest to dynamically alter the other dis play panels Likewise changing bp coordinates in the Detailed View or altering the size or location of any of the sliding selection boxes in the other panels has the appro priate effect on the selection box in the Statistic View panel Discussion Following the much anticipated first release of the draft sequence of the human genome by the international con sortium 23 and the Celera Corporation 24 in February 2001 human geneticists were eager to apply this resource data to use to map and identify disease susceptibility genes Even in its incomplete and unverified state the data represented a tremendously powerful resource to help resolve the inconsistencies that confounded the use of independently derived genetic and radiation hybrid maps Because of the computational complexity of deal ing with large and incomplete human
10. pedigrees 25 the production of these maps was a significant accomplish ment The deCODE Corporation immediately incorpo rated the draft sequence data in constructing a new meiotic map 12 that represented a significant improve ment over the Marshfield 26 and Genethon maps 27 It was also immediately obvious that a tremendous amount of work remains to translate this data into knowl edge that will eventually improve the overall health of the public and that the processes of analyzing and interpret ing this data presents many challenges in itself In spite of the exponential growth of biomedical data the task of mining data is less daunting than it was just a few years ago Via the World Wide Web WWW geneticists have at their disposal three distinct high quality well annotated genome repositories that provide free access to the most recent genome assemblies for humans as well as an increasing diverse assortment of model organisms Each of these public genome browsers NCBI UCSC and EBI Sanger s Ensembl employ their own annotation http www biomedcentral com 1471 2105 6 95 pipeline but should contain the same nucleotide sequence from the latest or at least the second most recent release of the NCBI assembly As is the case with the NCBI and UCSC genome browsers the public Ensembl site contains genomic sequences and a plethora of useful features extending well beyond known and pre dicted genes microsatellite markers an
11. 11733 l Di11734 Di11735 011736 5 00 Mb MLOD North American ALL Length Gene legend mmm ENSEMBL PREDICTED GENES KNOWN mmm ENSEMBL PSEUDOGENES Date Tue Nov 23 02 00 26 2004 Figure 2 Mmmm ENSENBL PREDICTED GENES NOVEL There are currently 48 tracks switched off use the menus above the image to turn these on Dump 1MB Dump clones amp As HTML C csv C clone set genes in region Dump all of Imb cloneset Help Desk Suggestions Cyto View featuring Statistic View A screen shot of private data hosted at primer duhs duke edu illustrating the integra tion of Statistic View in the Ensembl CytoView page Page 6 of 14 page number not for citation purposes BMC Bioinformatics 2005 6 95 User Request Contig View or Cyto View User fail authentication succeed Linkage Adaptor Retrieve linkage object from database LOD score plot Draw Statistic View Panel Contig or Cyto View Figure 4 Flow chart illustrating the flow of data in Statistic View A security feature is built in so that the process aborts if the user is not authenticated described below that is drawn beneath the Detailed View panel in Ensembl s Cyto and Contig View pages The source code for each of these is provided as rich text files see Additional file 1 through 5 respectively Also docu mentation and executables are provided within a com pressed archive file Addition
12. 6 AC092810 2 1 173917 E Chromosome 20 Cre Er A e 2 a A 411 25 BlastSearch amp MartSearch amp http www biomedcentral com 1471 2105 6 95 The Wellcome Trust gt Sanger Institiite DUKE tezie e HUMAN GENETICS mit Export Data amp Disease Browser 412 qi3 12 413 13 913 2 EP Cer CGH View Statistic view CGDFID 4 Sstigh 10 Legend MLOD African El Detailed view Jump to region 20 bp 4385258 to a lt lt 2 Mb lt 1Mb A Window Length Substantia nigra Kidney spec Cardiovas spec O CHG AGENDA top gene CO CHG AMD O CHG Age on set O CHG AlzD O CHG Autism O CHG PD O cHe scp X Cardiovas spec Uninterrupted ARMs Alu ARMs E Human proteins DNACcontigs Repeats BIB CO interrupted ARMs Alu ARMs i O Sanger annotation O Spinal cord x Substantia nigra O UniGene X Uninterrupted ARMs Uninterrupted ARMs Cardiovas spec Kidney spec Substantia nigra Length Manage sources Upload data URL based data Tilepath Server directory Stat Score Legend MLOD ALL MLOD Caucasian MLOD Group_B Refresh Select a study CGDFID M AGENDA Gene Adrian Agenda SNP CGCFID Linkage CGDFID CGDFID_assoc_68 60MB GENECARD Physical location Cin Mb MLOD North American ALL American 5385256 4 70 Mb 4 50 Mb 4 90 Mb 1000 00 Kb No Substantia nigra features in this region 5 00 Mb N
13. BMC Bioinformatics onana Software Statistical Viewer a tool to upload and integrate linkage and association data as plots displayed within the Ensembl genome browser Judith E Stenger 2 Hong Xu 2 Carol Haynes 2 Elizabeth R Hauser 2 Margaret Pericak Vance 2 Pascal J Goldschmidt Clermont and Jeffery M Vance 2 Address The Duke Center for Human Genetics Duke University Medical Center Durham North Carolina 27710 USA and 2Department of Medicine Duke University Medical Center Durham NC 27710 USA Email Judith E Stenger judy stenger duke edu Hong Xu hxu chg duhs duke edu Carol Haynes carol chg duhs duke edu Elizabeth R Hauser ehauser chg duhs duke edu Margaret Pericak Vance mpv chg duhs duke edu Pascal J Goldschmidt Clermont pascal goldschmidt duke edu Jeffery M Vance jeff chg duhs duke edu Corresponding author Published 12 April 2005 Received 15 December 2004 BMC Bioinformatics 2005 6 95 doi 10 1186 1471 2105 6 95 el a This article is available from http www biomedcentral com 471 2105 6 95 2005 Stenger et al licensee BioMed Central Ltd This is an Open Access article distributed under the terms of the Creative Commons Attribution License http creativecommons org licenses by 2 0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited Abstract Background To facilitate efficient selection and the prioritization of c
14. Martin ER Stenger JE Hulette C Scherzer CR Hauser MA Scott WK Small GW Nance MA Watts RL Hubble JP Koller WC Pahwa R Stern MB Hiner BC Jankovic J Goetz CG Mastaglia F Middleton LT Roses AD Saunders AM Welsh Bohmer KA Schmechel DE Gullans SR Haines JL Gilbert JR Vance JM Peri cak Vance MA Glutathione S transferase omega modifies age at onset of Alzheimer disease and Parkinson disease Hum Mol Genet 2004 13 573 Lobachev KS Stenger JE Kozyreva OG Jurka J Gordenin DA Res nick MA Inverted Alu repeats unstable in yeast are excluded from the human genome EMBO J 2000 19 3822 3830 Page 13 of 14 page number not for citation purposes BMC Bioinformatics 2005 6 95 31 32 33 34 35 36 37 Stenger JE Lobachev KS Gordenin D Darden TA Jurka J Resnick MA Biased distribution of inverted and direct Alus in the human genome implications for insertion exclusion and genome stability Genome Res 2001 I 1 12 27 Duke Center for Human Genetics Software Repository http wwwchg duhs duke edu software index html Download Ensembl Wiki web URL http www ensembl org Docs wiki html Ensemb IDocs DownloadEnsembI html Ensembl Anonymous FTP site ftp ftp ensembl org pub Ensembl installation instructions pdf file http www ensembl org Docs linked_docs Ensemblinstall_29 pdf GZIP http www gzip org WinZip Windows Archive Utility http www winzip com http www biomedcentral co
15. R Suh E Thomas R Tint NN Tse S Vech C Wang G Wetter J Williams S Williams M Windsor S Winn Deen E Wolfe K Zaveri J Zaveri K Abril JF Guigo R Campbell MJ Sjolander KV Karlak B Kejariwal A Mi H Lazareva B Hatton T Narechania A Diemer Muruganujan A Guo N Sato S Bafna V Istrail S Lippert R Schwartz R Walenz B Yooseph S Allen D Basu A Baxendale J Blick L Cam inha M Carnes Stine J Caulk P Chiang YH Coyne M Dahlke C Mays A Dombroski M Donnelly M Ely D Esparham S Fosler C Gire H Glanowski S Glasser K Glodek A Gorokhov M Graham K Grop man B Harris M Heil J Henderson S Hoover J Jennings D Jordan C Jordan J Kasha J Kagan L Kraft C Levitsky A Lewis M Liu X Lopez J Ma D Majoros W McDaniel J Murphy S Newman M Nguyen T Nguyen N Nodell M The sequence of the human genome Sci ence 2001 291 1304 1351 Lander ES Green P Construction of multi locus genetic link age maps in humans Proc Natl Acad Sci USA 1987 84 2363 2367 Marshfield Medical Center Genetics http research marshfield clinic org genetics Dib C Faure S Fizames C Samson D Drouot N Vignal A Millasseau P Marc S Hazan J Seboun E Lathrop M Gyapay G Morissette J Weissenbach j A comprehensive genetic map of the human genome based on _ 5 264 microsatellites Nature 1996 380 152 4 Galperin MY The molecular biology database collection 2005 update Nucleic Acids Res 2005 D5 24 Li YJ Oliveira SA Xu P
16. al file 6 Briefly the Linkage pm module features a constructor to create the linkage object essentially a table that encapsu lates the record for a single linkage point allowing for linkage data to be added populating the database The database table Linkage_Table contains up to eleven fields shown in figure 3A This information can be viewed http www biomedcentral com 1471 2105 6 95 in the Ensembl Contig and Cyto View browser pages within a pop up box when moving the cursor over mousing over the point in the plot as shown in figurel below the Detailed View The GlyphSet lodplot pm module is next implemented This module contains all the information for drawing the graph of the statistical data This module served as the basis for the FineLODplot pm that displays a graph of sta tistical data below the Detail View Panel that corresponds to the same range from the slice of the chromosome selected when the user slides the red box in either the ide ogram or the Statistic View panel of the Detailed View Panel The WebUserConfig chrplot pm module is then added to configure the lod plot so that it is displayed in the Statistic View panel in CytoView and ContigView The LinkageAdaptor object module LinkageAdaptor pm provides the functionality for accessing linkage data from the DAS database Linkage adaptor creates a slice object corresponding to the sliding red box that the view uses to select a region The slice object
17. andidate genes for follow up analysis poses the risk of excluding the causative gene from the list of candidates if the thresh olds are too stringent For this reason a tool capable of dis playing quantitative and positional data within a single integrated browser view that would facilitate the synthesis and interpretation of disparate data types is superior to the more simplistic approach using the intersection of sets of genes so that the thresholds are set empirically Customizing Ensembl to incorporate two dimensional linkage and association data plots For reasons discussed later in this paper we opted to use a local implementation of Ensembl as the basis of our internal bioinformatics infrastructure To fully meet our Page 2 of 14 page number not for citation purposes BMC Bioinformatics 2005 6 95 needs for integrating linkage and association data we developed software to customize Ensembl as an analytical tool for genomic convergence approaches to identify potential disease susceptibility genes for follow up analy sis For this purpose we have developed software modules that add functionality to the Ensembl genome annotation systems so that the browser will display quantitative data points plotted against chromosome position e g statisti cal results from genomic screens fine mapping and asso ciation studies and expression levels which are seamlessly integrated into the Contig View and Cyto View web pages The new pane
18. andidate complex disease susceptibility genes for association analysis increasingly comprehensive annotation tools are essential to integrate visualize and analyze vast quantities of disparate data generated by genomic screens public human genome sequence annotation and ancillary biological databases We have developed a plug in package for Ensembl called Statistical Viewer that facilitates the analysis of genomic features and annotation in the regions of interest defined by linkage analysis Results Statistical Viewer is an add on package to the open source Ensembl Genome Browser and Annotation System that displays disease study specific linkage and or association data as 2 dimensional plots in new panels in the context of Ensembl s Contig View and Cyto View pages An enhanced upload server facilitates the upload of statistical data as well as additional feature annotation to be displayed in DAS tracts in the form of Excel Files The Statistical View panel drawn directly under the ideogram illustrates lod score values for markers from a study of interest that are plotted against their position in base pairs A module called Get Map easily converts the genetic locations of markers to genomic coordinates The graph is placed under the corresponding ideogram features a synchronized vertical sliding selection box that is seamlessly integrated into Ensembl s Contig and Cyto View pages to choose the region to be displayed in Ensembl s Overview and D
19. arker coordinates from a data base when available Otherwise the linear interpolation algorithm is activated using the closest markers flanking markers with known coordinates to approximate the posi tion as accurately as possible The algorithm is based on that described in by Kong et al 12 To convert the map units from centimorgans into their chromosome sequence coordinates in base pairs it is nec essary to map the markers used as probes to the physical sequence of the human genome The most recent version of the human genome assembly currently NCBI build 35 can be downloaded from the UCSC genome site 10 and the most recent version of the Ensembl annotation system 8 The first step in converting the genetic location of a marker into its position in base pairs is the creation of a database of unique reliable and valid markers typically microsatellites based on the NCBI UniSTS database 13 14 an integrated non redundant database of markers sequence tagged sites STSs 15 as a starting point UniSTS integrates mapping information gathered from various resources primary sources and is the source of marker probe sequence information The markers their aliases sequences and available locations on genetic maps are retrieved via the NCBI ftp server 16 Once the most recent version of the human genome assembly and UniSTS has been uploaded onto our local servers we re map the positions of STSs by using e PCR 17 19 or BLAT
20. d SNPs that are linked to their corresponding records hosted at their respective primary sources see 28 for a review of current molecular biology databases We have chosen Ensembl as the system to underlie Statis tic View for several reasons 1 the horizontal presentation of the genome annotation makes it amenable to displaying a linkage map 2 Ensembl has stably incorpo rated DAS for displaying customized data from sources outside of the Ensembl annotation pipeline mapped to the genome as tracts for several years 3 the developers have intended from the start that the project would be open source and thus have taken great care in document ing its source code and 4 Ensembl s EnsMart genome data retrieval tool is a very sophisticated and flexible data mining tool containing extensive filters and several good output options Thus for the purpose of integrating link age data as well as other types of internal data we believe Ensembl currently provides the best architecture to serve as the basis of an data integration infrastructure for use by a genetics laboratory in an academic setting A local implementation of the Ensembl genome annota tion databases and software system is ideal for integrating third party annotation features with public human genome sequence annotation and serves as the founda tion of our bioinformatics infrastructure to assist in the identification and prioritization of candidate genes in dis ease fine mappin
21. deau J McKusick VA Zinder N Levine AJ Roberts RJ Simon M Slayman C Hunkapiller M Bolanos R Delcher A Dew I Fasulo D Flanigan M Florea L Halpern A Hannenhalli S Kravitz S Levy S Mobarry C Reinert K Remington K Abu Threideh J Beasley E Biddick K Bonazzi V Brandon R Cargill M Chandramouliswaran l Charlab R Chaturvedi K Deng Z Di FV Dunn P Eilbeck K Evangelista C Gabrielian AE Gan W Ge W Gong F Gu Z Guan P Heiman TJ Higgins ME Ji RR Ke Z Ketchum KA Lai Z Lei Y Li Z LiJ Liang Y Lin X Lu F Merkulov GV Milshina N Moore HM Naik AK Narayan VA Neelam B Nusskern D Rusch DB Salzberg S Shao W Shue B Sun J Wang Z Wang A Wang X Wang J Wei M Wides R Xiao C Yan C Yao A Ye J Zhan M Zhang W Zhang H Zhao Q Zheng L Zhong F Zhong W Zhu S Zhao S Gilbert D Baumhueter S Spier G Carter C Cravchik A Woodage T Ali F An H Awe A Baldwin D Baden H Barnstead M Barrow l Beeson K Busam D Carver A Center A Cheng ML Curry L Dana her S Davenport L Desilets R Dietz S Dodson K Doup L Ferriera S Garg N Gluecksmann A Hart B Haynes J Haynes C Heiner C Hladun S Hostin D Houck J Howland T Ibegwam C Johnson J Kalush F Kline L Koduru S Love A Mann F May D McCawley S Mclntosh T McMullen Moy M Moy L Murphy B Nelson K Pfann koch C Pratts E Puri V Qureshi H Reardon M Rodriguez R Rogers YH Romblad D Ruhfel B Scott R Sitter C Smallwood M Stewart E Strong
22. derlund C Scott CE Bentley DR Schuler G Chen HC Jang W Green ED Idol JR Maduro VV Montgomery KT Lee E Miller A Emerling S Kucherlapati Gibbs R Scherer S Gorrell JH Soder http ftp ftp ncbi nlm nih gov repository 24 25 26 27 28 29 30 http www biomedcentral com 1471 2105 6 95 gren E Clerc Blankenburg K Tabor P Naylor S Garcia D De Jong PJ Catanese J Nowak N Osoegawa K Qin S Rowen L Madan A Dors M Hood L Trask B Friedman C Massa H Cheung VG Kirsch IR Reid T Yonescu R Weissenbach J Bruls T Heilig R Branscomb E Olsen A Doggett N Cheng JF Hawkins T Myers RM Shang J Ram irez L Schmutz J Velasquez O Dixon K Stone NE Cox DR Haussler D Kent WJ Furey T Rogic S Kennedy S Jones S Rosenthal A Wen G Schilhabel M Gloeckner G Nyakatura G Siebert R Schlegelberger B Korenberg J Chen XN Fujiyama A Hattori M Toyoda A Yada T Park HS Sakaki Y Shimizu N Asakawa S Kawasaki K Sasaki T Shin tani A Shimizu A Shibuya K Kudoh J Minoshima S Ramser J Seranski P Hoff C Poustka A Reinhardt R Lehrach H A physical map of the human genome Nature 2001 409 934 941 Venter JC Adams MD Myers EW Li PW Mural RJ Sutton GG Smith HO Yandell M Evans CA Holt RA Gocayne JD Amanatides P Ballew RM Huson DH Wortman JR Zhang Q Kodira CD Zheng XH Chen L Skupski M Subramanian G Thomas PD Zhang J Gabor Miklos GL Nelson C Broder S Clark AG Na
23. dual records to the DAS database without having to delete and recreate a new data set and its resulting tract displayed in the detailed view panel By improving the data upload procedure laboratory personnel who gener ate data can enter and maintain their data with minimal training To facilitate the upload of data we developed a utility that thus far represents significant improvements over the upload server provided with the Ensembl package Our tool works well for uploading data with base pair coordi nates that is to be displayed in tracks in Contig and Cyto View s Detailed View panel We have found that to have data entry proceed at the same rate as data generation it is best to provide laboratory researchers with the tools to add their own annotation when high throughput geno typing methods are being used although some labs may prefer to have a gatekeeper to manually curate data at the time of entry to ensure that data integrity is preserved Rec ognizing the need to minimize errors which are inevita bly propagated and faced with limited human resources to enter and curate data we in the process of developing greater functionality to our upload server by automating conversion to the proper physical location so that poten tial mapping errors are avoided This software is provided in its current level of development as Additional files 7 and 8and their respective user manuals are provided in Additional files 9 and 10 Conclusion
24. e package to display the chromosome linkage plot and the information for each linkage point xi Linkageview pm Format Perl Module The EnsEMBL Web UserConfig linkageview module xii Lodplot pm For mat Perl Module The Bio EnsEMBL GlyphSet LodPlot module xiii HTML pm Format Perl Module This file is the modified source code for the ContigView HTML package that includes the Duke Center for Human Genetics extension to add the LOD score plot panel Click here for file http www biomedcentral com content supplementary 147 1 2105 6 95 S6 gz http www biomedcentral com 1471 2105 6 95 Additional File 7 The source code for the CHG enhanced upload service for integrating local data as features for display in the Ensembl genome browser as DAS tracks Click here for file http www biomedcentral com content supplementary 147 1 2105 6 95 S7 rtf Additional File 8 The source code for the CHG enhanced upload service for integrating link age or other statistical data for display in plots graphs as a panel within the Ensembl genome browser Contig and Cyto View pages Click here for file http www biomedcentral com content supplementary 147 1 2105 6 95 S8 rtf Additional File 9 User manual for uploading Linkage or other statistical data to be plotted in a display panel called Statistic View within the Contig and Cyto view genome Browser pages of a local implementation of Ensembl Click here for file http www b
25. e genome for additional features that may be indicative of a gene war ranting further investigation Towards this end we are conducting research to identifier better predictors of suc cessful outcome We have mapped to the genome sequence DNA motifs that we predict are at risk for genome instability such as full length highly identical closely spaced inverted repeats such as Alu pairs 30 31 and long simple tandem repeats Stenger unpublished in coding sequences see detailed view in Figures 1 and 2 Displaying these features in DAS tracts in conjunction with linkage data has enabled us to hone in on a potential candidate gene even when the function of gene is unknown Although the number of genes of unknown function is dwindling with better recognition of pseudo genes they still represent a large enough portion of genome that it is prudent to not exclude from follow up sequencing and association studies However genes of unknown function frequently are overlooked since such genes are excluded from strategies based on biological plausibility and may not be represented on microarrays In addition we are in the process of mapping trans acting transcription factors to the genome Aberrantly expressed genes may not map to linkage regions but it is likely that co expressed genes are regulated by a common cis acting regulatory element The identification of proteins that may bind to these regulatory motifs may further inform our search f
26. e unraveled so that tests prevention new knowledge based therapeu tic approaches can eventually be devised Great strides have been made towards the federation of bioinformatics databases as a result of concerted efforts over the last few years by leading bioinformaticians to develop controlled vocabularies 1 2 common platforms and tools for integration 3 As a result despite the expo nential growth of bioinformatics data the number of individual web based resources that genetic researchers have to navigate has been substantially reduced from a multitude of disparate web sites on single chromosomes and individual physical and genetic maps to essentially three major on line resources that facilitate access analy sis and retrieval of data from the recently completed human genome http www biomedcentral com 1471 2105 6 95 The visual presentation of the immense quantities of incongruent data types however presents challenges in itself Effective integrated informatics tools must be capa ble of representing essential data of ever increasing com plexity in a format that is both comprehensive and easily synthesized by the human brain 4 Towards this end three well annotated web based public genome browsers with improved interfaces have been developed and are continually evolving These are 1 the NCBI Entrez map viewer 5 6 2 the EMBL EBI Sanger Institute collabora tive Ensembl project 7 8 and 3 the University of Cali
27. eb based upload service To facilitate the upload of statistical data as well as other types of private data we developed a customized upload server that allows members of a group with permissions to upload their own data Users may add new data to be plotted into Statistical View or data for annotation as DAS tracts Our improved DAS upload server allows users to append data into previously instantiated data tracks The web based interface is also user friendly so that for matting difficulties and failures and errors that typically ensue when cutting and pasting tab delimited text into the Ensembl web form are avoided Upload file format requirements The data must be in the form of a simple two dimensional table containing attributes columns and tuples rows The upload serves accepts either tab delimited text files or MS excel spreadsheet files as input using a browse feature to specify the directory When using an Excel file the top worksheet page must contain all the data to be uploaded and be devoid of any merged fields We have designed the upload server to require a minimum of eight essential fields that serve as column headings in a table although additional attributes such as the name of the researcher or technician entering the data the method or date are per mitted and encouraged These eight required fields attributes are http www biomedcentral com 1471 2105 6 95 1 Study The term defines the data set and is t
28. ecombination map of the human genome Nat Genet 2002 31 241 247 UniSTS integrated makers and maps www ncbi nlm nih gov entrez query fcgi db unists Schuler GD Pieces of the puzzle expressed sequence tags and the catalog of human genes Mol Med 1997 75 694 698 Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245 1434 5 NCBI UniSTS ftp site UniSTS Schuler GD Sequence mapping by electronic PCR Genome Res 1997 7 541 50 Rotmistrovsky K Jang W Schuler GD A web server for perform ing electronic PCR Nucleic Acids Res 2004 W 08 12 NCBI e PCR http www ncbi nlm nih gov genome sts epcr cgi Kent WJ BLAT the BLAST like alignment tool Genome Res 2002 12 656 664 Dowell RD Jokerst RM Day A Eddy SR Stein L The distributed annotation system BMC Bioinformatics 2001 2 7 Stajich JE Block D Boulez K Brenner SE Chervitz SA Dagdigian C Fuellen G Gilbert JG Korf l Lapp H Lehvaslaiho H Matsalla C Mun gall CJ Osborne BI Pocock MR Schattner P Senger M Stein LD Stupka E Wilkinson MD Birney E The Bioperl toolkit Perl mod ules for the life sciences Genome Res 2002 12 161 1 1618 McPherson JD Marra M Hillier L Waterston RH Chinwalla A Wallis J Sekhon M Wylie K Mardis ER Wilson RK Fulton R Kucaba TA Wagner McPherson C Barbazuk WB Gregory SG Humphray SJ French L Evans RS Bethel G Whittaker A Holden JL McCann OT Dunham A So
29. el appears displaying text indicating that there is no statisti cal data pertaining to any study available for this chromo some not shown Like other Ensembl panels to save space this panel can be compressed when not needed Once the data is uploaded into a local Distributed Anno tation System DAS 21 server researchers can use a pull down menu to select the plot for a particular study of interest that is then drawn in a panel placed between ide ogram of the chromosome and the Overview in both Cyto View and Contig View Description of BioPerl modules for embedding Statistic View panels in Ensembl Using the Perl programming language we developed BioPerl modules reviewed by Stajich et al 22 that draw a linkage or other plot using the data uploaded in the DAS server for the particular study which the researcher must provides the name of as a required field The data flow for the Statistic View module is illustrated in figure 4 The source code is provided as supplemental material The four basic BioPerl modules are 1 Bio EnsEMBL Link age pm 2 Bio EnsEMBL DBSQL LinkageAdaptor pm 3 Bio EnsEMBL GlyphSet lodplot pm and 4 WebUser Config chrplot pm and Bio EnsEMBL Glyph Set FineLODplot provides for a detailed statistical plot Page 4 of 14 page number not for citation purposes BMC Bioinformatics 2005 6 95 Ensembi e Human Contig View Home Human Find Sequence 7 e g AC007005 3 1 16777
30. ent Tool cM centimorgan a single map unit db database DAS Distributed Annotation System DNA deoxyribonucleic acid EMBLI European Molecular Biology Laboratory EBI European Bioinformatics Institute Mb megabase one million base pairs http www biomedcentral com 1471 2105 6 95 NCBI National Center for Biotechnology Information SAGE Serial Analysis of Gene Expression SNP single nucleotide polymorphism SQL structured query language STS sequence tagged sites markers Authors contributions J E S scientific director of CHG bioinformatics core headed bioinformatics database integration project contributed to concept implementation ideas helped formulate requirements and provided suggestions for improvements Secured funding for hardware H X gt senior implementation programmer responsible for C H member of database integration and post process ing groups contributed to concept and implementation ideas Helped design database tables helped formulate requirements and provided suggestions for improvements E R H Principal Investigator for CEGS bioinformatics Component headed post processing project contributed to concept implementation ideas and requirements M P V Director of CHG provided funding human resources and the impetus for the project P J G C Chairman of the Duke Department of Medicine provided funding and supported project development J M V senior
31. etailed View panels To resolve Association and Fine mapping data plots a Detailed Statistic View plot corresponding to the Detailed View may be displayed underneath Conclusion Features mapping to regions of linkage are accentuated when Statistic View is used in conjunction with the Distributed Annotation System DAS to display supplemental laboratory information such as differentially expressed disease genes in private data tracks Statistic View is a novel and powerful visual feature that enhances EnsembI s utility as valuable resource for integrative genomic based approaches to the identification of candidate disease susceptibility genes At present there are no other tools that provide for the visualization of 2 dimensional plots of quantitative data scores against genomic coordinates in the context of a primary public genome annotation browser Page 1 of 14 page number not for citation purposes BMC Bioinformatics 2005 6 95 Background The search for genes contributing to complex human diseases The availability of the complete DNA sequence of the human genome along with advances in gene expression proteomics metabolomics technology and bioinformat ics databases presents new opportunities for integrative approaches to identify candidate susceptibility genes for complex human diseases Complex diseases which include such diverse illnesses as Alzheimer disease Par kinson disease cardiovascular disease and asthma account
32. for the majority of chronic illnesses that plague our society today These non Mendelian diseases are attributable to inherited polymorphisms in perhaps sev eral risk associated or modifier genes that are triggered by exposure to environmental agent s Because of the mul titude of factors ultimately contributing to the disease phenotype and the numerous confounding variables pre sented in studying human diseases isolating the genetic components that confer an underlying predisposition to a complex disease is an inherently daunting undertaking The importance of data integration Thus to improve the odds of successfully identifying com plex disease susceptibility genes several diverse approaches each of which must capitalize on cutting edge technical informatics and analysis should be exploited The integration of disparate biological statistical and clin ical databases both public and private into whole genome annotation are of paramount importance to com prehend and efficiently interpret the vast quantities of DNA sequence data gene expression data proteomics and other omics data As genotyping is a costly endeavor ever more effective computational tools are needed to readily access organize and comprehend the massive quantities of data generated to identify and prior itize candidate genes for genotyping Only when a disease causing genetic mutation is confirmed can the underlying molecular mechanisms of complex diseases b
33. g and association studies The DAS sys tem has enabled us to display the location of markers used in a particular study as features in tracks displayed in Con tig and Cyto View Additionally we have mapped other features such as the location of differentially expressed genes from experiments using both microarray 29 and SAGE technology 11 These studies employed Statistic View and illustrate the utility of having such a tool for rap idly identifying and visualizing genomic features that are in regions of linkage We have found that the benefits of locally maintaining a mirror of the public human genome sequence along with the Ensembl genome browser software and a DAS server exceed the costs It was far more costly to maintain indi vidual databases with different formats across different projects This integrated system allows users to manually curate genomic computationally derived statistical genetic and experimental e g gene expression results Page 9 of 14 page number not for citation purposes BMC Bioinformatics 2005 6 95 for many projects Additionally sensitive data can be password protected Although the ability to map the location of microsatellite or SNP markers used in genomic screens and genotyping into DAS tracts in the Ensembl overview has proved to be very useful in genomic convergence or integrative genomic strategies thus far Statistic View will continue to enable us to efficiently screen regions of th
34. he case of a SNP 8 Link_type This attribute specifies the type of line used for connecting the Link_points in the plot for example dot denotes a dotted line that we use as a con vention two point analysis Line is solid line ____ and typically indicates a multi point analysis By placing the term point in this field Statistical View will draw a scatter plot without lines If a value is not supplied for this field a solid line the default will connect the link points Viewing integrated statical data in Ensembl The StatisticalView panel depicts a graph plotting the link age or association statistics along the ordinate and the length of the chromosome in megabases Mbs along the abscissa The length of the abscissa diametrically cor responds to the length of the ideogram that is illustrated directly above The program generates this panel which is capable of displaying two dimensional graphs plotting data for pertaining to a study of interest Refreshing the Page 8 of 14 page number not for citation purposes BMC Bioinformatics 2005 6 95 page following selection of another study or analysis method can bring up different plots This plot is seam lessly integrated into the Cyto View and the Contig View pages Like other panels in these web pages the Statistic View panel features a selection box a movable red rectan gle with adjustable width to highlight the boundaries of a region of interest
35. he human genome in its entirety as well as those who tirelessly worked to continuously improve public access to biological databases This work was supported in part by the Alzheimer s Association grant Identification of Novel Age at Onset Genes on Chromosome 10 in Alzheimer Disease as well as the following NIH grants NHLBI grant POI HL73042 01 P J G C E R H H X M P V J E S J M V NINDS grants ROI AGO21547 M P V POI NS26630 15 M P V ROI NS36768 07 M P V NIA grant ROIAGI9757 01 P50 NS39764 04 and its supplement P50 NS39764 04S1 J M V NIEHS Page 12 of 14 page number not for citation purposes BMC Bioinformatics 2005 6 95 ES11375 H X J E S is also supported in partby NIEHS K 22 grant ES00372 References 19 20 21 22 23 Ashburner M Ball CA Blake JA Botstein D Butler H Cherry JM Davis AP Dolinski K Dwight SS Eppig JT Harris MA Hill DP Issel Tarver L Kasarskis A Lewis S Matese JC Richardson JE Ringwald M Rubin GM Sherlock G Geneontology tool for the unification of biology The Gene Ontology Consortium Nat Genet 2000 25 25 29 Stein LD Integrating biological databases Nat Rev Genet 2003 4 337 345 Hubbard T Biological information making it accessible and integrated and trying to make sense of it Bioinformatics 2002 18 Suppl 2 S140 Heumann K Harris C Mewes HW A top down approach to whole genome visualization Proc Int Conf Intell Syst Mol Biol 1996
36. he title of the study The field is a string of characters giving the name of a disease project or a sub study One study can have data across multiple chromosomes or in several analysis groups Data from multiple studies can be combined into a single spreadsheet if the records are listed sequentially in tuples rows 2 Analysis This field enables representation of data sub categories from stratification within a study The character string can be different statistical analysis methods or the different populations etc Again several data categories can be included into the same spreadsheet The fields will be used to provide the key or legend for the points plotted on the Statistic View graph The units should be included in parenthesis 3 Link_point This field is typically the name of the marker for linkage study The value will be represented as a data point on the Statistic View graph that will display the name of the marker in a pop up window when the point is moused over 4 Score The statistical score for the Link_point The units may be indicated here as well the score for inclusion in pop up windows 5 Chr_name All human chromosome names 1 through 22 as well as X Y are acceptable character values 6 Chr_start The chromosome start location of the Link_point in base pairs 7 Chr_end The chromosome end location of the Link_point also in base pairs This position may be iden tical to the chr_start value in t
37. hus recognizing the utility of having the ability to display detailed information in a region selected for detailed asso ciation studies we have developed code provided within Additional file 5 to plot and display association data in a separate panel below the Detailed View in Contig and Page 7 of 14 page number not for citation purposes BMC Bioinformatics 2005 6 95 Cyto View Essentially this panel that we refer to as Detailed Statistic View is an enlargement of a region selected from either Statistic View or the Overview panel that will directly corresponds with the Detailed View out lined in red See figures 1 and 2 Results Here we describe the functionality of a program package called Statistical Viewer that was written for the purpose of integrating statistical genetic data with human genome sequence annotation The name Statistical Viewer refers to the name of the software package while Statistic View refers to the display panel that is labeled in Ensembl s Contig View and Cyto View pages Usage The first step in adding statistical data to Ensembl is for matting the data for upload As the abscissa must corre spond to genomic coordinates for integration into the human genome assembly the position of the linkage point for the microsatellite or other marker needs to be defined by the name of chromosome and chromosome start and end position in base pairs Simplified data entry via an improved w
38. iomedcentral com content supplementary 147 1 2105 6 95 S9 doc Additional File 10 The manual for using the Duke CHG enhanced upload server web inter face to import data into MySQL database so that the features can be dis played as DAS tracks showing annotation for experimental data within the context of the genome sequence assembly on a local implementation of Ensembl Click here for file http www biomedcentral com content supplementary 147 1 2105 6 95 S10 doc Additional File 11 Manual for using the Get Map tool for the interconversion of genomic and genetic positions for markers The algorithm is also described Click here for file http www biomedcentral com content supplementary 147 1 2105 6 95 S11 doc Acknowledgements Weare grateful to Jason Stajich for pioneering this endeavor at the DCHG We are indebted to the Ensembl team especially Tony Cox at Sanger for providing guidance in setting up our local DAS server and Ewan Birney for his provocative discussions encouragement and willingness to make Statis tic View available through the public site We would like to thank Richard Cornwell for assistance in developing some of the code We also acknowl edge CHG fellows students and technicians of the CHG for their helpful suggestions Also none of this would have been possible if not for dedicated researchers of the International Genome Consortium who collectively accomplished the remarkable feat of sequencing t
39. ities as well as the UNIX man pages for the tar command i Readme A text file the provides a description of modules and the path to the code in the Ensembl Server Root directory ii Support pm Format Perl Module Modified source code for the ContigView Support package that includes the Duke Center for Human Genetics extension to add the LOD score plot panel iii Chrplot pm Format Perl Module The WebUserConfig chrplot BioPerl module iv Contigview Format text file Modified source code for the configuration based version of the Ensembl Contig view package including the necessary additions to incor porate the LOD score or other statistical data plot v Cytoview Format text file Source code for the Ensembl Cyto view package including the modifications to incorporate the LOD score plot vi DBAdaptor pm For mat Perl Module The modified source code for the Bio EnsEMBL DBSQL DBAdaptor module that includes the Duke Center for Human Genetics extension to add the LOD score plot panel into the genome browser vii Linkage sql Format Structured Query Lan guage This file specifies the table structure for the linkage object viii Linkage pm Format Perl Module Bio EnsEMBL Linkage Ensembl BioPerl module ix LinkageAdaptor pm Format Perl Module Bio EnsEMBL DBSQL LinkageAdaptor BioPerl module This Module includes the POD documentation the main documents preceding the code x Linkageview Format BioPerl package This file provides th
40. ls fully support the functionality of the Ensembl system so genome regions corresponding selected by the user within the Statistic View will be dis played in the Overview and Detailed View panels and additional information on the statistical data points may be displayed in pop up views with hyper links to individ ual feature information pages The Statistical Viewer pack age includes software to facilitate the upload query storage integration display analysis and retrieval of pri vate quantitative data into a public open source genome browser so that all public annotation DAS sources and links can be fully exploited We have created a software package called Statistical View that includes an enhanced upload server that facil itates the upload query storage integration display analysis and retrieval of private quantitative data into a public genome browser to help geneticists make connec tion between the disease phenotype and the genetic fea tures that are associated with risk on a genomic scale From there an understanding of the molecular basis of disease can lead to testing prevention and perhaps ulti mately to pharmaceutical or alternative means of inter vention so that the hopes of translational medicine promised by the completion of the human genome sequencing project will eventually be realized Implementation Mapping genetic marker locations as genomic positions in the human genome assembly Linkage data is t
41. m 1471 2105 6 95 Publish with BioMed Central and every scientist can read your work free of charge BioMed Central will be the most significant development for disseminating the results of biomedical research in our lifetime Sir Paul Nurse Cancer Research UK Your research papers will be e available free of charge to the entire biomedical community e peer reviewed and published immediately upon acceptance e cited in PubMed and archived on PubMed Central e yours you keep the copyright Submit your manuscript here O BioMedcentral http www biomedcentral com info publishing_adv asp Page 14 of 14 page number not for citation purposes
42. ng Availability and requirements The source code is provided as supplementary material for this publication and will also be available from the Duke Center for Human Genetics public web pages 32 as well as through the public Ensembl site 8 Setting up a local implementation of Ensembl To use this software the Ensembl Genome Browser Soft ware Annotation System must be installed and running locally The Statistical View package runs on version 26 1 which can be accessed through the Download Ensembl Wiki web URL 33 Genome files and other database files can be access through the Ensembl ftp server 34 Ensembl requires a server with a UNIX or Linux type of operating system e g OS X SGI s IRIX and Sun s Solaris All software and the full complement of mySQL genome sequences and databases currently occupies 150 gigabytes of storage space and requires just as much swap space but may not be needed depending on your requirements as specified in the installation pdf file 35 We maintain a current local implementation of the Ensembl open source software system including the human genome sequence assembly and related databases running on a SunFire 12 K reference server in conjunction with a separate server a Sun Blade 2000 acting as an anno tation server to store and overlay public genome data with private laboratory data for integration using the Distrib uted Annotation System List of abbreviations BLAT BLAST Like Alignm
43. o Kidney spec features in this region No Cardiovas spec features in this region 0111737 l Tetrai4203 Hexad 1656 Hexad189 5 Tethaid2 Uninterrupted ARMs No Alu ARMs features in this region ID Tri9422 Tetrai 202 ha l Hexad187 114205 TYPE Uninterrupted ARMs METHOD repeat 96 2 1 148497 gt ii til paeaal No Alu ARMs features in this regionUninterruptedARMs 0 1 ou E MONT More info Di11732 Di11735 0111733 Di11736 Dili 3 No Cardiovas spec features in this region No Kidney spec features in this region No Substantia nigra features in this region Rites ee ee sSea feature D20S895 X Study CGCFID Linkage geen Comment a MLOD Group_A MLOD Group_C There are currently 76 tracks switched off use the menus above the image to turn these on Ensembl Homo_sapiens E Basepair view Figure 2024385258 5385256 Tue Dec 14 01 55 46 2004 Contig View featuring Statistic View Shown is a screen shot depicting a local implementation of Ensembl s contig view page hosted by the Duke Center for Human Genetics captured using Snaglt 7 0 The figure illustrates the appearance of the Statistic View panel and some of its features in the context of Contig View It also demonstrates how the selection of a peak can enable the researcher to easily see where linkage data and other features such as potentially unstable tri nucleotide repeats and gene e
44. or candidate genes in regions displayed in Sta tistic View We have also been using in silico subtractive hybridization methods to identify genes expressed uniquely in tissues that exhibit pathology in the diseases that are under investigation e g a DAS tract displaying the location of genes specific to the substantia nigra may help identify candidate genes for Parkinson Disease and have mapped these to the genome as DAS tracks It is worthwhile to mention that the upload of data into the DAS database using Ensembl s upload server can be problematic The upload server provided on the public server had a number of shortcomings 1 it is often diffi cult to properly format the data as text so that the desired output is generated 2 a full email address is required for the user ID at login and 3 each login results in data put into a separate track so that individual records could not easily be added to an existing data track To overcome this the user who initialized the track was required to delete http www biomedcentral com 1471 2105 6 95 the original data file and append the new data to a file and reload the entire data set These limitations detracted from the usefulness of our private Ensembl DAS system because data entry became a bottleneck in the analysis project with bioinformaticians serving as gatekeepers We extended the capabilities of the upload server so that researchers with appropriate permissions could easily add indivi
45. raditionally visually displayed as a graph in which Lod scores are plotted along the ordinate against the genetic location of the markers that were used in the genetic screen and the subsequent analysis The length of the abscissa represents the length of the chromosome in centimorgans cM a function of the recombination fre quency between two loci Recombination frequency is influenced by factors such as regional genetic content and gender so that one can only make a rough approximation between in the average number of base pairs that are in a single centimorgan map unit Therefore to incorporate a visual representation of statistical results into the Ensembl genome browser in a meaningful way it is imperative that the abscissa be expressed in base pairs so that the position http www biomedcentral com 1471 2105 6 95 of markers along the abscissa correctly align with and strictly correspond to the horizontal illustration of the ideogram that is displayed immediately above the linkage study graph in the Ensembl ContigView Towards this end we have developed a tool GetMap that uses linear inter polation relative to deCODE Genetics published map 12 to approximate the physical chromosomal coordi nates denoted in bps of markers that were a not mapped by the deCODE group and b we have insufficient infor mation for successful ePCR The algorithm first uses a binary search the divide and conquer paradigm to find and extract known m
46. xpression data converge to suggest priority gene for association and sequence analysis Page 5 of 14 page number not for citation purposes BMC Bioinformatics 2005 6 95 Address a http genominator2 duhs duke edu Homo_sapiens cytoview bottom 7Cmanaged_das_ALLtfs 34o0ff 7Cmanaged_das_CHGalu 34o0ff Cmanaged_das_TG http www biomedcentral com 1471 2105 6 95 Go Link The Wellcome Trust gt Sanger Institute Ensembi Human CytoView Export Data Find Sequence e g AP000462 RH9632 cancer E Chromosome 20 Lo ei BlastSearch amp MartSearch amp 4 Disease Browser pii 23 pii 21 See p12 2 pi2 1 DUKE cealer ur HUMAN GENETICS in CGH View El Statistic view CGDFID Select a study CGDFID Ft a ore Refresh gt dete fe Physical location Cin Mb MLOD Caucasian MLOD African American Jump to region 20 bp fig197615 to 69197605 ai ae Zoom A Window Mouse synteny Length 5 00 Mb Chr 20 band 3 00 Mb 4 00 Mb Kidney spec ENSG00000101405 Kidney spec Tetraid 1 5 ID ENSGO00001 01405 Tei TYPE TG_Kidney Hexa METHOD EST mining aa CATEGORY Tissue Specific etrai419 Tetral i75 Tetral i73 Tetral i7 Trid403 Tetral4i i Hexad 156 Tetral 1 S Tetrai 1s2 Uninterrupted ARMs ee oe l Tetrald i 3 Di11721 Hexad176 gene More infp Ww me i ees l ee ee E N ti i
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