Summary: The analysis of genetic data often requires a combination of several approaches using different and sometimes incompatible programs. In order to facilitate data exchange and file conversions between population genetics programs, we introduce PGDSpider, a Java program that can read 27 different file formats and export data into 29, partially overlapping, other file formats. The PGDSpider package includes both an intuitive graphical user interface and a command-line version allowing its integration in complex data analysis pipelines. Availability: PGDSpider is freely available under the BSD 3-Clause license on http://cmpg.unibe.ch/software/PGDSpider/ Contact: heidi.lischer@iee.unibe.ch Supplementary information: Supplementary data are available at Bioinformatics onlin

Excoffier, L.

Lischer, H. E. L.

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[17:47 20/12/2011 Bioinformatics-btr642.tex] Page: 298 298–299BIOINFORMATICS APPLICATIONS NOTE Vol. 28 no. 2 2012, pages 298–299doi:10.1093/bioinformatics/btr642Data and text mining Advance Access publication November 21, 2011PGDSpider: an automated data conversion tool for connectingpopulation genetics and genomics programsH. E. L. Lischer1,2,∗ and L. Excofﬁer1,21Computational and Molecular Population Genetics (CMPG) laboratory, Institute of Ecology and Evolution, Universityof Berne, Baltzerstrasse 6, 3012 Berne and 2Swiss Institute of Bioinformatics, 1015 Lausanne, SwitzerlandAssociate Editor: Janet KelsoABSTRACTSummary: The analysis of genetic data often requires a combinationof several approaches using different and sometimes incompatibleprograms. In order to facilitate data exchange and ﬁle conversionsbetween population genetics programs, we introduce PGDSpider,a Java program that can read 27 different ﬁle formats and exportdata into 29, partially overlapping, other ﬁle formats. The PGDSpiderpackage includes both an intuitive graphical user interface anda command-line version allowing its integration in complex dataanalysis pipelines.Availability: PGDSpider is freely available under the BSD 3-Clauselicense on http://cmpg.unibe.ch/software/PGDSpider/Contact: heidi.lischer@iee.unibe.chSupplementary information: Supplementary data are available atBioinformatics online.Received on August 4, 2011; revised on November 14, 2011;accepted on November 15, 20111 INTRODUCTIONIn the last few years, high-throughput sequencing made it possibleto sequence a huge amount of DNA at a rapidly decreasing cost,allowing for budget-tight studies to produce large sequencing andpopulation genetics datasets (Gompert et al., 2010; Hohenlohe et al.,2010; Metzker, 2010). A proper analysis of these data requires acombination of several approaches, beginning with those describingbasic properties of the data, followed by more specialized andoften computer intensive analyses (Excoffier and Heckel, 2006).Most of the times, it requires the use of several population geneticprograms and different input formats, which necessitate numerousfile conversions. However, data format conversion can be tediousand error prone if not fully automatized, especially when dealingwith large amounts of data.To our knowledge, only three programs are available totransfer populations genetics data between programs: CONVERT(Glaubitz, 2004), FORMATOMATIC (Manoukis, 2007) andCREATE (Coombs et al., 2008). Whereas these programs cansometimes bridge many population genetics program (CREATEreads 12 input formats and outputs 62 formats; CONVERT reads2 and outputs 7, whereas FORMATOMATICS reads 4 and outputs13), these programs have some limitations. For instance, CREATEand CONVERT only handle codominant diploid genotypic data,∗To whom correspondence should be addressed.Fig. 1. Connectivity between population genetics programs and formats.Red (reading and writing) and green (reading or writing) arrows indicateconversion possibilities between PGDSpider and other programs. Greyarrows show connections between programs that are not mediated byPGDSpider. Programs are shown as blue ellipses, general data formats ingreen and conversion programs in orange.CREATE focuses mainly on parentage analysis programs andFORMATOMATICS only deals with microsatellite data.To improve data exchange between programs for a vast range ofdata types (Fig. 1), we introduce here PGDSpider, an automated dataconversion tool for population genetics and population genomics.2 SUPPORTED DATA FORMATSOur data conversion program PGDSpider is able to deal with diversetypes of data like DNA, RNA, NGS (next-generation sequencingdata), microsatellite, SNP, RFLP, AFLP, multiallelic data, allelefrequency and genetic distances, and this either in diploid or haploidformats. Currently, on top of its own Population Genetics Data(PGD) format, PGDSpider can read 27 and export 29 differentdata formats, like: e.g. ARLEQUIN (Excoffier and Lischer, 2010)or MEGA (Tamura et al., 2011), but see the complete list ofsupported formats in the Supplementary Table S1. With the abilityto convert various kinds of data types and data formats, PGDSpidergreatly enhances and complements exchange possibilities betweenpopulation genetics programs as shown in Figure 1.In addition to conventional population genetics formats,PGDSpider integrates four population genomics data formats298 © The Author 2011. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com[17:47 20/12/2011 Bioinformatics-btr642.tex] Page: 299 298–299PGDSpidercommonly used for storing and handling NGS data like thoseof the 1000 genomes project (Altshuler et al., 2010): these arethe sequencing alignment (SAM) format and the variant callformat (VCF), as well as their binary versions (BAM and BCF,respectively). Note that PGDSpider calls the program SAMtools(Li et al., 2009) during the conversion of these formats. SAMtoolsthus needs to be downloaded separately. Currently, PGDSpider isnot meant to convert very large NGS files as it loads into memorythe whole input file, the size of which may exceed available RAM.However, since PGDSpider can convert specific subsets of largeBAM, SAM, BCF and VCF files into any other format, one coulduse this feature to calculate parameters or statistics for specificchromosome segments, and thus use a sliding window approachto analyse large genomic regions.3 PGD FORMATPGDSpider uses a newly developed PGD format as an intermediatestep in the conversion process. PGD is a file format designed tostore various kinds of population genetics data, including differentdata types (e.g. DNA sequences, microsatellites, AFLP or SNPs)and ploidy levels (haploid, diploid, or higher ploidy levels). PGDis based on the XML (eXtensible Markup Language) format andis therefore independent of any particular computer system andextensible for future needs. The XML file uses an ordered labelledtree-like structure that can easily be processed. PGD is structuredin the following blocks: (i) the ‘header’ block contains a generaldescription of the data. It is possible to give information aboutthe organism, the number of populations, the ploidy level, thecharacters encoding missing values and gaps. Additionally, it allowsone to specify if the gametic phase is known and if the data arerecessive. The second block (ii) ‘dataDescription’ embeds locus-specific information and makes it possible to store the followinginformation for each locus: data type, location in the genome, if itis in genic regions or not, its length and some additional commentsor links. (iii) The ‘population’ blocks contain information about thepopulations, their member individuals and the actual genetic data. Itallows one to specify the geographic coordinates of the populationand/or the individuals, as well as the ploidy level, locus namesor identifiers and multilocus haplotype frequencies. Note that forNGS data, it is also possible to store sequence read quality scores.(iv) An optional ‘structure’block gives information about the geneticstructure of the populations (i.e. which population samples belongto which groups). The last block (v) ‘distanceMatrix’ is optional andcontains information about genetic distances among haplotypes.Full details on the PGD format can be found in the PGDSpideruser manual together with example files. The block structure and thehierarchical structure of stored information make the PGD formatvery modular and extensible for future needs. Additionally, it ispossible to nicely visualize data contained in the PGD files by usingany web browser supporting XML stylesheets. The PGD formatcould be seen as a first step towards the creation of a generic andunified population genetic data format, which could greatly improvecommunication between programs and thus facilitate data analyses.4 PROGRAM INTERFACE AND AVAILABILITYThe PGDSpider program is written in Java, a fully virtualizedand platform-independent programming language. The program isuser friendly in the sense that it provides an intuitive graphicaluser interface (GUI). The GUI and the menus are available infour different languages: English, French, German and Italian.PGDSpider allows users to store their preferred conversion settingsfor repeated conversions of similar input formats. A command-lineversion of PGDSpider is also provided, making it possible to embedPGDSpider in complex data analysis pipelines.The PGDSpider program and its user manual can be downloadedfrom http://cmpg.unibe.ch/software/PGDSpider/ under the BSD3-Clause License. The user manual provides detailed informationon how to use the program (GUI and command-line version) aswell as a short file description of each supported data formats. Italso includes an extensive description of the new PGD format andexample files.ACKNOWLEDGEMENTSWe thank Matthieu Foll, Mathias Beysard and the whole CMPGteam for comments and testing the program, as well as PascalTschanz for his help in solving programming issues.Funding: Swiss National Science Foundation (grant No 3100A0-126074 to L.E.).Conflict of Interest: none declared.REFERENCESAltshuler,D.L. et al. (2010) A map of human genome variation from population-scalesequencing. Nature, 467, 1061–1073.Coombs,J.A. et al. (2008) CREATE: a software to create input files from diploidgenotypic data for 52 genetic software programs. Mol. Ecol. Resour., 8, 578–580.Excoffier,L. and Heckel,G. (2006) Computer programs for population genetics dataanalysis: a survival guide. Nat. Rev. Genet., 7, 745–758.Excoffier,L. and Lischer,H.E.L. (2010) Arlequin suite ver 3.5: a new series of programsto perform population genetics analyses under Linux and Windows. Mol. Ecol.Resour., 10, 564–567.Glaubitz,J.C. (2004) CONVERT: a user-friendly program to reformat diploid genotypicdata for commonly used population genetic software packages. Mol. Ecol. Notes,4, 309–310.Gompert,Z. et al. (2010) Bayesian analysis of molecular variance in pyrosequencesquantifies population genetic structure across the genome of Lycaeides butterflies.Mol. Ecol., 19, 2455–2473.Hohenlohe,P.A. et al. (2010) Population genomics of parallel adaptation in threespinestickleback using sequenced RAD tags. Plos Genet., 6, e1000862.Li,H. et al. (2009) The Sequence Alignment/Map format and SAMtools. Bioinformatics,25, 2078–2079.Manoukis,N.C. (2007) FORMATOMATIC: a program for converting diploid allelicdata between common formats for population genetic analysis. Mol. Ecol. Notes,7, 592–593.Metzker,M.L. (2010) Applications of next-generation sequencing sequencingtechnologies - the next generation. Nat. Rev. Genet., 11, 31–46.Tamura,K. et al. (2011) MEGA5: molecular evolutionary genetics analysis usingmaximum likelihood, evolutionary distance, and maximum parsimony methods.Mol. Biol. Evol., 28, 2731–2739.299

PGDSpider: an automated data conversion tool for connecting population genetics and genomics programs

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