ohely-srmaanrpackage-2012.pdf (293.18 kB)
Download fileSRMA: an R package for resequencing array data analysis
journal contribution
posted on 2012-07-15, 00:00 authored by N Zhang, Y Xu, Martin O'HelyMartin O'Hely, T P Speed, C Scharfe, W WangSequencing 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.
History
Journal
BioinformaticsVolume
28Issue
14Pagination
1928 - 1930Publisher
Oxford University PressLocation
Oxford, Eng.Publisher DOI
ISSN
1367-4803eISSN
1460-2059Language
engPublication classification
C Journal article; C1.1 Refereed article in a scholarly journalCopyright notice
2012, The AuthorsUsage metrics
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Categories
Keywords
AlgorithmsComputational BiologyHumansOligonucleotide Array Sequence AnalysisSequence Analysis, DNASoftwareScience & TechnologyLife Sciences & BiomedicineTechnologyPhysical SciencesBiochemical Research MethodsBiotechnology & Applied MicrobiologyComputer Science, Interdisciplinary ApplicationsMathematical & Computational BiologyStatistics & ProbabilityBiochemistry & Molecular BiologyComputer ScienceMathematicsVARIANTS