Dataset Information

VarScan: variant detection in massively parallel sequencing of individual and pooled samples.

ABSTRACT:

Summary

Massively parallel sequencing technologies hold incredible promise for the study of DNA sequence variation, particularly the identification of variants affecting human disease. The unprecedented throughput and relatively short read lengths of Roche/454, Illumina/Solexa, and other platforms have spurred development of a new generation of sequence alignment algorithms. Yet detection of sequence variants based on short read alignments remains challenging, and most currently available tools are limited to a single platform or aligner type. We present VarScan, an open source tool for variant detection that is compatible with several short read aligners. We demonstrate VarScan's ability to detect SNPs and indels with high sensitivity and specificity, in both Roche/454 sequencing of individuals and deep Illumina/Solexa sequencing of pooled samples.

SUBMITTER: Koboldt DC

PROVIDER: S-EPMC2734323 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature

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Publications

VarScan: variant detection in massively parallel sequencing of individual and pooled samples.

Koboldt Daniel C DC Chen Ken K Wylie Todd T Larson David E DE McLellan Michael D MD Mardis Elaine R ER Weinstock George M GM Wilson Richard K RK Ding Li L

Bioinformatics (Oxford, England) 20090619 17

<h4>Summary</h4>Massively parallel sequencing technologies hold incredible promise for the study of DNA sequence variation, particularly the identification of variants affecting human disease. The unprecedented throughput and relatively short read lengths of Roche/454, Illumina/Solexa, and other platforms have spurred development of a new generation of sequence alignment algorithms. Yet detection of sequence variants based on short read alignments remains challenging, and most currently availabl ...[more]

PMID: 19542151

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Project description:BackgroundCirculating cell-free (ccf) fetal DNA comprises 3-20% of all the cell-free DNA present in maternal plasma. Numerous research and clinical studies have described the analysis of ccf DNA using next generation sequencing for the detection of fetal aneuploidies with high sensitivity and specificity. We sought to extend the utility of this approach by assessing semi-automated library preparation, higher sample multiplexing during sequencing, and improved bioinformatic tools to enable a higher throughput, more efficient assay while maintaining or improving clinical performance.MethodsWhole blood (10mL) was collected from pregnant female donors and plasma separated using centrifugation. Ccf DNA was extracted using column-based methods. Libraries were prepared using an optimized semi-automated library preparation method and sequenced on an Illumina HiSeq2000 sequencer in a 12-plex format. Z-scores were calculated for affected chromosomes using a robust method after normalization and genomic segment filtering. Classification was based upon a standard normal transformed cutoff value of z = 3 for chromosome 21 and z = 3.95 for chromosomes 18 and 13.ResultsTwo parallel assay development studies using a total of more than 1900 ccf DNA samples were performed to evaluate the technical feasibility of automating library preparation and increasing the sample multiplexing level. These processes were subsequently combined and a study of 1587 samples was completed to verify the stability of the process-optimized assay. Finally, an unblinded clinical evaluation of 1269 euploid and aneuploid samples utilizing this high-throughput assay coupled to improved bioinformatic procedures was performed. We were able to correctly detect all aneuploid cases with extremely low false positive rates of 0.09%, <0.01%, and 0.08% for trisomies 21, 18, and 13, respectively.ConclusionsThese data suggest that the developed laboratory methods in concert with improved bioinformatic approaches enable higher sample throughput while maintaining high classification accuracy.

Dataset Information

VarScan: variant detection in massively parallel sequencing of individual and pooled samples.

Summary

Publications

VarScan: variant detection in massively parallel sequencing of individual and pooled samples.

Similar Datasets

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