SRMA: an R package for resequencing array data analysis.

Bioinformatics
Nianxiang ZhangWenyi Wang

Abstract

Sequencing by hybridization to oligonucleotides has evolved into an inexpensive, reliable and fast technology for targeted sequencing. Hundreds of human genes can now be sequenced within a day using a single hybridization to a resequencing microarray. However, several issues inherent to these arrays (e.g. cross-hybridization, variable probe/target affinity) cause sequencing errors and have prevented more widespread applications. We developed an R package for resequencing microarray data analysis that integrates a novel statistical algorithm, sequence robust multi-array analysis (SRMA), for rare variant detection with high sensitivity (false negative rate, FNR 5%) and accuracy (false positive rate, FPR 1×10⁻⁵). The SRMA package consists of five modules for quality control, data normalization, single array analysis, multi-array analysis and output analysis. The entire workflow is efficient and identifies rare DNA single nucleotide variations and structural changes such as gene deletions with high accuracy and sensitivity. http://cran.r-project.org/, http://odin.mdacc.tmc.edu/~wwang7/SRMAIndex.html

References

May 30, 2008·Nature Genetics·Walter Bodmer, Carolina Bonilla
Apr 7, 2011·Proceedings of the National Academy of Sciences of the United States of America·Peidong ShenCurt Scharfe
Jun 10, 2011·Bioinformatics·Petr DanecekUNKNOWN 1000 Genomes Project Analysis Group
Jan 17, 2012·Parkinsonism & Related Disorders·E J WilkinsM K Horne

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Citations

Jul 16, 2019·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·Liang WangYue Yang

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