Skip to content


  • Introduction
  • Open Access

VarI-SIG 2014 - From SNPs to variants: interpreting different types of genetic variants

BMC Genomics201516(Suppl 8):I1

Published: 18 June 2015


The decreasing cost of high-throughput sequencing is still rapidly increasing the number of known genetic variants [1, 2]. For example, the size of the dbSNP database [3] has nearly doubled over the past years to 110 million human single nucleotide polymorphisms and short genomic variants. Unfortunately the characterization, annotation, and interpretation of these variants are still lagging. In particular, the interpretation of genetic variants and their implication in disease is one of the major challenges in personalized medicine [46].

The 4th edition of the Variant Interpretation Special Interest Group (VarI-SIG, formerly SNP-SIG) meeting [79] was held on July 12 at the ISMB 2014 in Boston (MA). The central meeting themes were "Annotation and prediction of structural/functional impacts of coding variants" and "Genetic variants as effectors of change: disease and evolution". The VarI-SIG is organized as a venue for the development of a research network of scientists, necessary for facilitating the exchange of ideas and establishing new collaborations. This year's meeting attracted over 100 participants, with seven research talks and five presentations from the leading scientists of the field.

Manuscript submission and review

This year we received 11 submissions to the VarI-SIG special issue. All submissions were by-invitation on the basis of talks/interactions that took place at the meeting. In addition to editorial evaluations, all manuscripts were assessed by at least two reviewers from a panel of 22 experts in the field (see Acknowledgements). To maintain reviewer anonymity, the four reviewers of submissions in which the editors are co-authors remain un-named. After 2 rounds of review 9 of the 11 manuscripts were accepted for publication in this special issue.

The articles presented in this SIG proceedings issue focus on annotating genomic variants in coding [10] and non-coding regions [11], identifying phenotypic impacts of genetic and epigenetic variations [1214], characterizing biological basis of Mendelian diseases [15] and interpreting the cancer genome [16], detecting positive selection in regulatory regions [17], and identifying geographical origins of individuals [18].

[The complete program of VarI-SIG meeting 2014 with presentation and poster abstracts is available at]

Further developments

This year we welcome to the VarI-SIG organizing committee Dr. Hannah Carter, Assistant Professor, Division of Medical Genetics, UCSD. Together, we are working on the organization of the next VarI-SIG meeting that will be held in the context of the ISMB/ECCB 2015 (Dublin, Ireland; July 11, 2015). Further information about the meeting is available on our website (

In collaboration with ISMB organizers, we are also promoting the formation of VarI-COSI (Variant Interpretation Community of Special Interest). VarI-COSI is community aimed at sharing relevant information, discussing ideas, and providing training and support networks in the field of genomic interpretation. We are still in the initial stages of setting up our COSI presence on the web and look forward to input and participation from the variation interpretation community.



We are grateful to Rachel Karchin (John Hopkins University, Baltimore, MD) for the organizing and chairing of the MD Corner and roundtable discussion. We thank Frank Schacherer and BIOBASE International for their financial support. We acknowledge Isobel Peters and the editorial staff of BioMed Central for their help with releasing this issue. We would like to extend special thanks for all help to the ISMB organizational committee and specifically Steven Leard and Jeremy Hennig.

We also thank the invited speakers: George Church (Harvard University, Cambrige, MA), Garry Cutting (John Hopkins, Baltimore, MD), Jan Korbel (EMBL, Heidelberg, Germany), James Potash (University of Iowa, Iowa City IA) and Benjamin Raphael (Brown University, Providence, RI).

Finally, we are very grateful for the patience and help of our colleagues around the world who reviewed the submitted manuscripts. The VarI-SIG 2014 special issue would has not be possible without them:

Francesc Calafell (Universitat Pompeu Fabra, Barcelona, Spain), Hannah Carter (University of California, San Diego, CA), Xavier de la Cruz (Vall d'Hebron Institute of Research, Barcelona, Spain), Paul Geeleher (University of Chicago, Chicago, IL) Christian Gilissen (Radboud University, Nijmegen, Netherland), Alexandra Graf (FH Campus, Wien, Austria), Tae Hyun Hwang (Southwestern University, Dallas, TX), Jose MG Izarzugaza (DTU, Lyngby, Denmark), Martin Kircher (University of Washington, Seattle, WA), Biao Li (Gilead Sciences Inc., Foster City, CA), Yves Lussier (Arizona State University, Tucson, AZ), Ugur Sezerman (Sabanci University, Istanbul, Turkey), Hashem Shihab (University of Bristol, Bristol, UK), Nick Tatonetti (Columbia University, New York, NY), Jacob Tennessen (Oregon State University, Corvallis, OR), Ali Torkanami (Scripps Institute, San Diego, CA), Silvio Tosatto (University of Padova, Padova, Italy), Verena Zuber (University of Oslo, Oslo, Norway) and 4 anonymous reviewers who evaluated the papers where the editors of this special issue are co-authors.

This article has been published as part of BMC Genomics Volume 16 Supplement 8, 2015: VarI-SIG 2014: Identification and annotation of genetic variants in the context of structure, function and disease. The full contents of the supplement are available online at

Authors’ Affiliations

Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, USA
Department of Genetics, Rutgers University, Piscataway, USA
Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, USA
Department of Clinical and Diagnostic Sciences, University of Alabama at Birmingham, Birmingham, USA
Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, USA


  1. Capriotti E, Nehrt NL, Kann MG, Bromberg Y: Bioinformatics for personal genome interpretation. Brief Bioinform. 2012, 13 (4): 495-512. 10.1093/bib/bbr070.PubMed CentralView ArticlePubMedGoogle Scholar
  2. 1000 Genomes Project Consortium, Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, Handsaker RE, Kang HM, Marth GT, McVean GA: An integrated map of genetic variation from 1,092 human genomes. Nature. 2012, 491 (7422): 56-65. 10.1038/nature11632.View ArticleGoogle Scholar
  3. Sherry ST, Ward MH, Kholodov M, Baker J, Phan L, Smigielski EM, Sirotkin K: dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 2001, 29 (1): 308-311. 10.1093/nar/29.1.308.PubMed CentralView ArticlePubMedGoogle Scholar
  4. Fernald GH, Capriotti E, Daneshjou R, Karczewski KJ, Altman RB: Bioinformatics challenges for personalized medicine. Bioinformatics. 2011, 27 (13): 1741-1748. 10.1093/bioinformatics/btr295.PubMed CentralView ArticlePubMedGoogle Scholar
  5. MacArthur DG, Manolio TA, Dimmock DP, Rehm HL, Shendure J, Abecasis GR, Adams DR, Altman RB, Antonarakis SE, Ashley EA, et al: Guidelines for investigating causality of sequence variants in human disease. Nature. 2014, 508 (7497): 469-476. 10.1038/nature13127.PubMed CentralView ArticlePubMedGoogle Scholar
  6. Bromberg Y: Building a genome analysis pipeline to predict disease risk and prevent disease. J Mol Biol. 2013, 425 (21): 3993-4005. 10.1016/j.jmb.2013.07.038.View ArticlePubMedGoogle Scholar
  7. Bromberg Y, Capriotti E: SNP-SIG Meeting 2011: identification and annotation of SNPs in the context of structure, function, and disease. BMC Genomics. 2012, 13 (Suppl 4): S1-10.1186/1471-2164-13-S4-S1.PubMed CentralView ArticlePubMedGoogle Scholar
  8. Bromberg Y, Capriotti E: Thoughts from SNP-SIG 2012: future challenges in the annotation of genetic variations. BMC Genomics. 2013, 14 (Suppl 3): S1-PubMed CentralPubMedGoogle Scholar
  9. Bromberg Y, Capriotti E: SNP-SIG 2013: from coding to non-coding--new approaches for genomic variant interpretation. BMC Genomics. 2014, 15 (Suppl 4): S1-10.1186/1471-2164-15-S4-S1.PubMed CentralView ArticlePubMedGoogle Scholar
  10. Hecht M, Bromberg Y, Rost B: Better prediction of functional effects for sequence variants. BMC Genomics. 2015, 16 (Suppl 8): S1-PubMed CentralView ArticlePubMedGoogle Scholar
  11. Frankish A, Uszczynska B, Ritchie GRS, Gonzalez JM, Pervouchine D, Petryszak R, Mudge JM, Fonseca N, Brazma A, Guigo R, Harrow J: Comparison of GENCODE and RefSeq gene annotation and the impact of reference geneset on variant effect prediction. BMC Genomics. 2015, 16 (Suppl 8): S2-PubMed CentralView ArticlePubMedGoogle Scholar
  12. Ma M, Ru Y, Chuang LS, Hsu NY, Shi LS, Hakenberg J, Cheng WY, Uzilov A, Ding W, Glicksberg BS, Chen R: Disease-associated variants in different categories of disease located in distinct regulatory elements. BMC Genomics. 2015, 16 (Suppl 8): S3-View ArticleGoogle Scholar
  13. Pal LR, Yu C-H, Mount SM, Moult J: Insights from GWAS: emerging landscape of mechanisms underlying complex trait disease. BMC Genomics. 2015, 16 (Suppl 8): S4-PubMed CentralView ArticlePubMedGoogle Scholar
  14. Gnad F, Doll S, Manning G, Arnott D, Zhang Z: Bioinformatics analysis of thousands of TCGA tumors to determine the involvement of epigenetic regulators in human cancer. BMC Genomics. 2015, 16 (Suppl 8): S5-PubMed CentralView ArticlePubMedGoogle Scholar
  15. Di Lena P, Martelli PL, Fariselli P, Casadio R: NET-GE: a novel NETwork-based Gene Enrichment for detecting biological processes associated to Mendelian diseases. BMC Genomics. 2015, 16 (Suppl 8): S6-PubMed CentralPubMedGoogle Scholar
  16. Tian R, Basu MK, Capriotti E: Computational methods and resources for the interpretation of genomic variants in cancer. BMC Genomics. 2015, 16 (Suppl 8): S7-PubMed CentralView ArticlePubMedGoogle Scholar
  17. Handelman SK, Seweryn M, Smith RM, Hartmann K, Wang D, Pietrzak M, Johnson AD, Kloczkowski A, Sadee W: Conditional entropy in variation-adjusted windows detects selection signatures associated with expression quantitative trait loci (eQTLs). BMC Genomics. 2015, 16 (Suppl 8): S8-PubMed CentralView ArticlePubMedGoogle Scholar
  18. Kozlov K, Chebotarev D, Hassan M, Triska M, Triska P, Flegontov P, Tatarinova TV: Differential Evolution approach to detect recent admixture. BMC Genomics. 2015, 16 (Suppl 8): S9-PubMed CentralView ArticlePubMedGoogle Scholar


© Bromberg and Capriotti; licensee BioMed Central Ltd. 2015

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.