Performance comparison of SNP detection tools with illumina exome sequencing data--an assessment using both family pedigree information and sample-matched SNP array data.
To apply exome-seq-derived variants in the clinical setting, there is an urgent need to identify the best variant caller(s) from a large collection of available options. We have used an Illumina exome-seq dataset as a benchmark, with two validation scenarios--family pedigree information and SNP array data for the same samples, permitting global high-throughput cross-validation, to evaluate the quality of SNP calls derived from several popular variant discovery tools from both the open-source and commercial communities using a set of designated quality metrics. To the best of our knowledge, this is the first large-scale performance comparison of exome-seq variant discovery tools using high-throughput validation with both Mendelian inheritance checking and SNP array data, which allows us to gain insights into the accuracy of SNP calling through such high-throughput validation in an unprecedented way, whereas the previously reported comparison studies have only assessed concordance of these tools without directly assessing the quality of the derived SNPs. More importantly, the main purpose of our study was to establish a reusable procedure that applies high-throughput validation to compare the quality of SNP discovery tools with a focus on exome-seq, which can be used to compare any forthcoming tool(s) of interest.
Advanced Biomedical Computing Center, SAIC-Frederick, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA Current address: Cancer Research and Technology Program, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc. PO Box B, Frederick, MD, 21702. stephensr@mail.nih.gov yiming@mail.nih.gov.
Ming
M
Yi
Advanced Biomedical Computing Center, SAIC-Frederick, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.
Yongmei
Y
Zhao
Advanced Biomedical Computing Center, SAIC-Frederick, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.
Li
L
Jia
Endocrine Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA.
Mei
M
He
Endocrine Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA.
Electron
E
Kebebew
Advanced Biomedical Computing Center, SAIC-Frederick, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA Current address: Cancer Research and Technology Program, Frederick National Laboratory for Cancer Research, Leidos Biomedical Research, Inc. PO Box B, Frederick, MD, 21702. stephensr@mail.nih.gov yiming@mail.nih.gov.
Robert M
RM
Stephens
D059472:Exome; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D010375:Pedigree; D020641:Polymorphism, Single Nucleotide; D017422:Sequence Analysis, DNA / Q000379:methods*