journal article Sep 30, 2014

Detailed comparison of two popular variant calling packages for exome and targeted exon studies

PeerJ Vol. 2 pp. e600 · PeerJ
View at Publisher Save 10.7717/peerj.600
Topics

No keywords indexed for this article. Browse by subject →

References
44
[1]
A method and server for predicting damaging missense mutations

Ivan A Adzhubei, Steffen Schmidt, Leonid Peshkin et al.

Nature Methods 2010 10.1038/nmeth0410-248
[2]
Bauer "Variant calling comparison CASAVA1.8 and GATK" Nature Precedings (2011) 10.1038/npre.2011.6107.1
[3]
Blankenberg "Galaxy: a web-based genome analysis tool for experimentalists" (2001)
[4]
Boland "The new sequencer on the block: comparison of Life Technology’s Proton sequencer to an Illumina HiSeq for whole-exome sequencing" Human Genetics (2013) 10.1007/s00439-013-1321-4
[5]
Carson "Effective filtering strategies to improve data quality from population-based whole exome sequencing studies" BMC Bioinformatics (2014) 10.1186/1471-2105-15-125
[6]
Cheng "Assessing single nucleotide variant detection and genotype calling on whole-genome sequenced individuals" Bioinformatics (2014) 10.1093/bioinformatics/btu067
[7]
A framework for variation discovery and genotyping using next-generation DNA sequencing data

Mark A DePristo, Eric Banks, Ryan Poplin et al.

Nature Genetics 2011 10.1038/ng.806
[8]
Fu "Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants" Nature (2013) 10.1038/nature11690
[9]
Garrison "Haplotype-based variant detection from short-read sequencing" (2012)
[10]
Galaxy: A platform for interactive large-scale genome analysis

Belinda Giardine, Cathy Riemer, ROSS C. HARDISON et al.

Genome Research 2005 10.1101/gr.4086505
[11]
Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences

Jeremy Goecks, Anton Nekrutenko, James Taylor

Genome Biology 2010 10.1186/gb-2010-11-8-r86
[12]
Koboldt "VarScan: variant detection in massively parallel sequencing of individual and pooled samples" Bioinformatics (2009) 10.1093/bioinformatics/btp373
[13]
VarScan 2: Somatic mutation and copy number alteration discovery in cancer by exome sequencing

Daniel C. Koboldt, Qunyuan Zhang, David E. Larson et al.

Genome Research 2012 10.1101/gr.129684.111
[14]
Lam "Detecting and annotating genetic variations using the HugeSeq pipeline" Nature Biotechnology (2012) 10.1038/nbt.2134
[15]
The European Nucleotide Archive

R. Leinonen, R. Akhtar, E. Birney et al.

Nucleic Acids Research 2011 10.1093/nar/gkq967
[16]
Lescai "Identification and validation of loss of function variants in clinical contexts" Molecular Genetics & Genomic Medicine (2014) 10.1002/mgg3.42
[17]
Fast and accurate short read alignment with Burrows–Wheeler transform

Heng Li, Richard Durbin

Bioinformatics 2009 10.1093/bioinformatics/btp324
[18]
Li "Bioinformatics pipelines for targeted resequencing and whole-exome sequencing of human and mouse genomes: a virtual appliance approach for instant deployment" PLoS ONE (2014) 10.1371/journal.pone.0095217
[19]
The Sequence Alignment/Map format and SAMtools

Heng Li, Bob Handsaker, Alec Wysoker et al.

Bioinformatics 2009 10.1093/bioinformatics/btp352
[20]
Linderman "Analytical validation of whole exome and whole genome sequencing for clinical applications" BMC Medical Genomics (2014) 10.1186/1755-8794-7-20
[21]
Liu "Variant callers for next-generation sequencing data: a comparison study" PLoS ONE (2013) 10.1371/journal.pone.0075619
[22]
High-throughput DNA sequencing errors are reduced by orders of magnitude using circle sequencing

Dianne I. Lou, Jeffrey A. Hussmann, Ross M. McBee et al.

Proceedings of the National Academy of Sciences 2013 10.1073/pnas.1319590110
[23]
A Systematic Survey of Loss-of-Function Variants in Human Protein-Coding Genes

Daniel G. MacArthur, Suganthi Balasubramanian, Adam Frankish et al.

Science 2012 10.1126/science.1215040
[24]
The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data

Aaron McKenna, Matthew Hanna, Eric Banks et al.

Genome Research 2010 10.1101/gr.107524.110
[25]
Narzisi "Accurate detection of de novo and transmitted INDELs within exome-capture data using micro-assembly" (2014)
[26]
Nevado "Pipeliner: software to evaluate the performance of bioinformatics pipelines for next-generation resequencing" Molecular Ecology Resources (2014) 10.1111/1755-0998.12286
[27]
SIFT: predicting amino acid changes that affect protein function

P. C. Ng

Nucleic Acids Research 2003 10.1093/nar/gkg509
[28]
Genotype and SNP calling from next-generation sequencing data

Rasmus Nielsen, Joshua S. Paul, Anders Albrechtsen et al.

Nature Reviews Genetics 2011 10.1038/nrg2986
[29]
O’Rawe "Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing" Genome Medicine (2013) 10.1186/gm432
[30]
Pabinger "A survey of tools for variant analysis of next-generation genome sequencing data" Briefings in Bioinformatics (2014) 10.1093/bib/bbs086
[31]
Pirooznia "Validation and assessment of variant calling pipelines for next-generation sequencing" Human Genomics (2014) 10.1186/1479-7364-8-14
[32]
Roberts "A comparative analysis of algorithms for somatic SNV detection in cancer" Bioinformatics (2013) 10.1093/bioinformatics/btt375
[33]
Schmitt "Detection of ultra-rare mutations by next-generation sequencing" Proceedings of the National Academy of Sciences of the United States of America (2012) 10.1073/pnas.1208715109
[34]
dbSNP: the NCBI database of genetic variation

S. T. Sherry

Nucleic Acids Research 2001 10.1093/nar/29.1.308
[35]
Talwalkar "SMaSH: a benchmarking toolkit for human genome variant calling" Bioinformatics (2014) 10.1093/bioinformatics/btu345
[37]
Van der Auwera "From FastQ data to high-confidence variant calls: the genome analysis toolkit best practices pipeline" (2002)
[38]
Wang "Detecting somatic point mutations in cancer genome sequencing data: a comparison of mutation callers" Genome Medicine (2013) 10.1186/gm495
[39]
ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data

K. Wang, M. Li, H. Hakonarson

Nucleic Acids Research 2010 10.1093/nar/gkq603
[40]
Worthey "Analysis and annotation of whole-genome or whole-exome sequencing–derived variants for clinical diagnosis" (2013) 10.1002/0471142905.hg0924s79
[41]
Xu "Comparison of somatic mutation calling methods in amplicon and whole exome sequence data" BMC Genomics (2014) 10.1186/1471-2164-15-244
[42]
Yi "Performance comparison of SNP detection tools with illumina exome sequencing data—an assessment using both family pedigree information and sample-matched SNP array data" Nucleic Acids Research (2014) 10.1093/nar/gku392
[43]
Comparing a few SNP calling algorithms using low-coverage sequencing data

Xiaoqing Yu, Shuying Sun

BMC Bioinformatics 2013 10.1186/1471-2105-14-274
[44]
Integrating human sequence data sets provides a resource of benchmark SNP and indel genotype calls

Justin M Zook, Brad Chapman, Jason Wang et al.

Nature Biotechnology 2014 10.1038/nbt.2835
Metrics
40
Citations
44
References
Details
Published
Sep 30, 2014
Vol/Issue
2
Pages
e600
Cite This Article
Charles D. Warden, Aaron W. Adamson, Susan L. Neuhausen, et al. (2014). Detailed comparison of two popular variant calling packages for exome and targeted exon studies. PeerJ, 2, e600. https://doi.org/10.7717/peerj.600
Related

You May Also Like