GeMSTONE: orchestrated prioritization of human germline mutations in the cloud

Abstract Integrative analysis of whole-genome/exome-sequencing data has been challenging, especially for the non-programming research community, as it requires simultaneously managing a large number of computational tools. Even computational biologists find it unexpectedly difficult to reproduce results from others or optimize their strategies in an end-to-end workflow. We introduce Germline Mutation Scoring Tool fOr Next-generation sEquencing data (GeMSTONE), a cloud-based variant prioritization tool with high-level customization and a comprehensive collection of bioinformatics tools and data libraries (http://gemstone.yulab.org/). GeMSTONE generates and readily accepts a shareable ‘recipe’ file for each run to either replicate previous results or analyze new data with identical parameters and provides a centralized workflow for prioritizing germline mutations in human disease within a streamlined workflow rather than a pool of program executions.

[1]  Kenneth Offit,et al.  Sequencing an Ashkenazi reference panel supports population-targeted personal genomics and illuminates Jewish and European origins , 2014, Nature Communications.

[2]  E. Lundberg,et al.  Towards a knowledge-based Human Protein Atlas , 2010, Nature Biotechnology.

[3]  J. Kere,et al.  Mutation in CEP63 co-segregating with developmental dyslexia in a Swedish family , 2015, Human Genetics.

[4]  Gonçalo R. Abecasis,et al.  Unified representation of genetic variants , 2015, Bioinform..

[5]  James Taylor,et al.  Next-generation sequencing data interpretation: enhancing reproducibility and accessibility , 2012, Nature Reviews Genetics.

[6]  P. Stenson,et al.  The Human Gene Mutation Database: building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine , 2013, Human Genetics.

[7]  Alejandro Sifrim,et al.  Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data , 2015, The Lancet.

[8]  Ricardo Villamarín-Salomón,et al.  ClinVar: public archive of interpretations of clinically relevant variants , 2015, Nucleic Acids Res..

[9]  S. Gabriel,et al.  Analysis of 6,515 exomes reveals a recent origin of most human protein-coding variants , 2012, Nature.

[10]  Ralf Herwig,et al.  ConsensusPathDB—a database for integrating human functional interaction networks , 2008, Nucleic Acids Res..

[11]  Gonçalo R. Abecasis,et al.  The variant call format and VCFtools , 2011, Bioinform..

[12]  Adam Kiezun,et al.  Exome Aggregation Consortium , 2016 .

[13]  Susumu Goto,et al.  Data, information, knowledge and principle: back to metabolism in KEGG , 2013, Nucleic Acids Res..

[14]  Justin C. Fay,et al.  Identification of deleterious mutations within three human genomes. , 2009, Genome research.

[15]  M. Falchi,et al.  Multiple rare genetic variants co‐segregating with familial IgA nephropathy all act within a single immune‐related network , 2016, Journal of internal medicine.

[16]  Judith A. Blake,et al.  Mouse Genome Database (MGD)-2017: community knowledge resource for the laboratory mouse , 2016, Nucleic Acids Res..

[17]  Jana Marie Schwarz,et al.  MutationTaster evaluates disease-causing potential of sequence alterations , 2010, Nature Methods.

[18]  Martin Vingron,et al.  IntAct: an open source molecular interaction database , 2004, Nucleic Acids Res..

[19]  Haiyuan Yu,et al.  HINT: High-quality protein interactomes and their applications in understanding human disease , 2012, BMC Systems Biology.

[20]  D. Mackay,et al.  Exome Sequencing Identifies a Missense Variant in EFEMP1 Co-Segregating in a Family with Autosomal Dominant Primary Open-Angle Glaucoma , 2015, PloS one.

[21]  M. Metzker.  Sequencing technologies — the next generation , 2010, Nature Reviews Genetics.

[22]  D. G. MacArthur,et al.  Guidelines for investigating causality of sequence variants in human disease , 2014, Nature.

[23]  Shamil R Sunyaev,et al.  Pooled association tests for rare variants in exon-resequencing studies. , 2010, American journal of human genetics.

[24]  S. Henikoff,et al.  Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm , 2009, Nature Protocols.

[25]  김삼묘,et al.  “Bioinformatics” 특집을 내면서 , 2000 .

[26]  Kathryn Roeder,et al.  Testing for an Unusual Distribution of Rare Variants , 2011, PLoS genetics.

[27]  Volker Brendel,et al.  BioExtract Server—An Integrated Workflow-Enabling System to Access and Analyze Heterogeneous, Distributed Biomolecular Data , 2010, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[28]  Kara Dolinski,et al.  The BioGRID interaction database: 2015 update , 2014, Nucleic Acids Res..

[29]  Á. Carracedo,et al.  Whole-exome sequencing identifies rare pathogenic variants in new predisposition genes for familial colorectal cancer , 2014, Genetics in Medicine.

[30]  Xihong Lin,et al.  Rare-variant association testing for sequencing data with the sequence kernel association test. , 2011, American journal of human genetics.

[31]  K. Pollard,et al.  Detection of nonneutral substitution rates on mammalian phylogenies. , 2010, Genome research.

[32]  Henning Hermjakob,et al.  The Reactome pathway knowledgebase , 2013, Nucleic Acids Res..

[33]  François Schiettecatte,et al.  OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders , 2014, Nucleic Acids Res..

[34]  P. Bork,et al.  A method and server for predicting damaging missense mutations , 2010, Nature Methods.

[35]  Jean-Michel Claverie,et al.  The human gene damage index as a gene-level approach to prioritizing exome variants , 2015, Proceedings of the National Academy of Sciences.

[36]  David Baker,et al.  Protein Structure Prediction Using Rosetta , 2004, Numerical Computer Methods, Part D.

[37]  K. Boycott,et al.  Rare-disease genetics in the era of next-generation sequencing: discovery to translation , 2013, Nature Reviews Genetics.

[38]  Gonçalo R. Abecasis,et al.  The Sequence Alignment/Map format and SAMtools , 2009, Bioinform..

[39]  D. Mackay,et al.  Exome sequencing identifies novel and recurrent mutations in GJA8 and CRYGD associated with inherited cataract , 2014, Human Genomics.

[40]  E. Boerwinkle,et al.  dbNSFP: A Lightweight Database of Human Nonsynonymous SNPs and Their Functional Predictions , 2011, Human mutation.

[41]  R. Rosenfeld.  Nature , 2009, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.

[42]  E. Birney,et al.  Pfam: the protein families database , 2013, Nucleic Acids Res..

[43]  Andrew J. Hill,et al.  Analysis of protein-coding genetic variation in 60,706 humans , 2015, bioRxiv.

[44]  J. Mesirov,et al.  GenePattern 2.0 , 2006, Nature Genetics.

[45]  A. Nekrutenko,et al.  Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences , 2010, Genome Biology.

[46]  Aaron R. Quinlan,et al.  GEMINI: Integrative Exploration of Genetic Variation and Genome Annotations , 2013, PLoS Comput. Biol..

[47]  A. Valencia,et al.  POLE and POLD1 mutations in 529 kindred with familial colorectal cancer and/or polyposis: review of reported cases and recommendations for genetic testing and surveillance , 2015, Genetics in Medicine.

[48]  Kenny Q. Ye,et al.  An integrated map of genetic variation from 1,092 human genomes , 2012, Nature.

[49]  Leila Mohammadi,et al.  BMC Cancer , 2001 .

[50]  Bale,et al.  Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology , 2015, Genetics in Medicine.

[51]  G. Latkovskis,et al.  Next-generation-sequencing-based identification of familial hypercholesterolemia-related mutations in subjects with increased LDL–C levels in a latvian population , 2015, BMC Medical Genetics.

[52]  Serafim Batzoglou,et al.  Identifying a High Fraction of the Human Genome to be under Selective Constraint Using GERP++ , 2010, PLoS Comput. Biol..

[53]  J. Shendure,et al.  A general framework for estimating the relative pathogenicity of human genetic variants , 2014, Nature Genetics.

[54]  Pablo Cingolani,et al.  © 2012 Landes Bioscience. Do not distribute. , 2022 .

[55]  M. Bourbon,et al.  Mutational analysis of a cohort with clinical diagnosis of familial hypercholesterolemia: considerations for genetic diagnosis improvement , 2015, Genetics in Medicine.

[56]  J. Lupski,et al.  Whole-Exome Sequencing in Familial Parkinson Disease. , 2016, JAMA neurology.

[57]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[58]  Florian Halbritter,et al.  GeneProf: analysis of high-throughput sequencing experiments , 2011, Nature Methods.

[59]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[60]  Ayal B. Gussow,et al.  The Intolerance of Regulatory Sequence to Genetic Variation Predicts Gene Dosage Sensitivity , 2015, PLoS genetics.

[61]  Ellen T. Gelfand,et al.  The Genotype-Tissue Expression (GTEx) project , 2013, Nature Genetics.

[62]  M. T. Medina,et al.  EFHC1 variants in juvenile myoclonic epilepsy: reanalysis according to NHGRI and ACMG guidelines for assigning disease causality , 2016, Genetics in Medicine.