Detailed simulation of cancer exome sequencing data reveals differences and common limitations of variant callers

[1]  P. Humphrey,et al.  The 2016 WHO Classification of Tumours of the Urinary System and Male Genital Organs-Part A: Renal, Penile, and Testicular Tumours. , 2016, European urology.

[2]  Michael C. Heinold,et al.  A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing , 2015, Nature Communications.

[3]  Ana Conesa,et al.  Qualimap 2: advanced multi-sample quality control for high-throughput sequencing data , 2015, Bioinform..

[4]  Andrew Menzies,et al.  Subclonal diversification of primary breast cancer revealed by multiregion sequencing , 2015, Nature Medicine.

[5]  J. Potash,et al.  Validation and assessment of variant calling pipelines for next-generation sequencing , 2014, Human Genomics.

[6]  D. Spandidos,et al.  Emerging targeted therapies for melanoma treatment (Review) , 2014, International journal of oncology.

[7]  Brandi L. Cantarel,et al.  BAYSIC: a Bayesian method for combining sets of genome variants with improved specificity and sensitivity , 2014, BMC Bioinformatics.

[8]  Heng Li,et al.  Toward better understanding of artifacts in variant calling from high-coverage samples , 2014, Bioinform..

[9]  Björn Usadel,et al.  Trimmomatic: a flexible trimmer for Illumina sequence data , 2014, Bioinform..

[10]  R. Satya,et al.  Comparison of somatic mutation calling methods in amplicon and whole exome sequence data , 2014, BMC Genomics.

[11]  P. A. Futreal,et al.  Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing , 2014, Nature Genetics.

[12]  Benjamin J. Raphael,et al.  Identifying driver mutations in sequenced cancer genomes: computational approaches to enable precision medicine , 2014, Genome Medicine.

[13]  Peilin Jia,et al.  Detecting somatic point mutations in cancer genome sequencing data: a comparison of mutation callers , 2013, Genome Medicine.

[14]  Mauricio O. Carneiro,et al.  From FastQ Data to High‐Confidence Variant Calls: The Genome Analysis Toolkit Best Practices Pipeline , 2013, Current protocols in bioinformatics.

[15]  Xiaoqing Yu,et al.  Comparing a few SNP calling algorithms using low-coverage sequencing data , 2013, BMC Bioinformatics.

[16]  R. Daniel Kortschak,et al.  A comparative analysis of algorithms for somatic SNV detection in cancer , 2013, Bioinform..

[17]  Vineet Bafna,et al.  Wessim: a whole-exome sequencing simulator based on in silico exome capture , 2013, Bioinform..

[18]  I. Cuesta,et al.  Comparison of variant calling methods in exome sequencing of matched tumor-normal sample pairs , 2013 .

[19]  H. Hakonarson,et al.  Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing , 2013, Genome Medicine.

[20]  A. Sivachenko,et al.  Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples , 2013, Nature Biotechnology.

[21]  Michael R. Speicher,et al.  A survey of tools for variant analysis of next-generation genome sequencing data , 2013, Briefings Bioinform..

[22]  Gabor T. Marth,et al.  Haplotype-based variant detection from short-read sequencing , 2012, 1207.3907.

[23]  T. Takano,et al.  Olaparib in platinum-sensitive ovarian cancer. , 2012, The New England journal of medicine.

[24]  K. Polyak,et al.  Intra-tumour heterogeneity: a looking glass for cancer? , 2012, Nature Reviews Cancer.

[25]  Steven L Salzberg,et al.  Fast gapped-read alignment with Bowtie 2 , 2012, Nature Methods.

[26]  Christopher A. Miller,et al.  VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. , 2012, Genome research.

[27]  Ken Chen,et al.  SomaticSniper: identification of somatic point mutations in whole genome sequencing data , 2012, Bioinform..

[28]  Sohrab P. Shah,et al.  JointSNVMix: a probabilistic model for accurate detection of somatic mutations in normal/tumour paired next-generation sequencing data , 2012, Bioinform..

[29]  M. Gerstung,et al.  Reliable detection of subclonal single-nucleotide variants in tumour cell populations , 2012, Nature Communications.

[30]  Tatiana Popova,et al.  Supplementary Methods , 2012, Acta Neuropsychiatrica.

[31]  Gholamreza Haffari,et al.  Feature-based classifiers for somatic mutation detection in tumour–normal paired sequencing data , 2011, Bioinform..

[32]  Heng Li,et al.  A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data , 2011, Bioinform..

[33]  Kristian Cibulskis,et al.  ContEst: estimating cross-contamination of human samples in next-generation sequencing data , 2011, Bioinform..

[34]  Denis C. Bauer Variant calling comparison CASAVA1.8 and GATK , 2011 .

[35]  M. DePristo,et al.  A framework for variation discovery and genotyping using next-generation DNA sequencing data , 2011, Nature Genetics.

[36]  M. DePristo,et al.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. , 2010, Genome research.

[37]  Thomas Seufferlein,et al.  Targeted treatments in colorectal cancer: state of the art and future perspectives , 2010, Gut.

[38]  Emily H Turner,et al.  Targeted Capture and Massively Parallel Sequencing of Twelve Human Exomes , 2009, Nature.

[39]  R. Elston,et al.  Choosing an optimal method to combine P‐values , 2009, Statistics in medicine.

[40]  Knut Reinert,et al.  SeqAn An efficient, generic C++ library for sequence analysis , 2008, BMC Bioinformatics.

[41]  S. Gabriel,et al.  EGFR Mutations in Lung Cancer: Correlation with Clinical Response to Gefitinib Therapy , 2004, Science.

[42]  Faraz Hach,et al.  SiNVICT: ultra-sensitive detection of single nucleotide variants and indels in circulating tumour DNA , 2017, Bioinform..

[43]  Francesco Vallania,et al.  Performance of common analysis methods for detecting low-frequency single nucleotide variants in targeted next-generation sequence data. , 2014, The Journal of molecular diagnostics : JMD.

[44]  T. Speed,et al.  Comparing somatic mutation-callers: beyond Venn diagrams , 2013, BMC Bioinformatics.

[45]  Ira M. Hall,et al.  BEDTools: a flexible suite of utilities for comparing genomic features , 2010, Bioinform..

[46]  Claude-Alain H. Roten,et al.  Fast and accurate short read alignment with Burrows–Wheeler transform , 2009, Bioinform..

[47]  S. Kunte Statistical computing , 2000 .