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SRMA: an R package for resequencing array data analysis

Zhang, Nianxiang, Xu, Yan, O'Hely, Martin, Speed, TP, Scharfe, C and Wang, W 2012, SRMA: an R package for resequencing array data analysis, Bioinformatics, vol. 28, no. 14, pp. 1928-1930, doi: 10.1093/bioinformatics/bts286.

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Title SRMA: an R package for resequencing array data analysis
Author(s) Zhang, Nianxiang
Xu, Yan
O'Hely, Martin
Speed, TP
Scharfe, C
Wang, W
Journal name Bioinformatics
Volume number 28
Issue number 14
Start page 1928
End page 1930
Total pages 3
Publisher Oxford University Press
Place of publication Oxford, Eng.
Publication date 2012-07-15
ISSN 1367-4803
1460-2059
Keyword(s) Algorithms
Computational Biology
Humans
Oligonucleotide Array Sequence Analysis
Sequence Analysis, DNA
Software
Science & Technology
Life Sciences & Biomedicine
Technology
Physical Sciences
Biochemical Research Methods
Biotechnology & Applied Microbiology
Computer Science, Interdisciplinary Applications
Mathematical & Computational Biology
Statistics & Probability
Biochemistry & Molecular Biology
Computer Science
Mathematics
VARIANTS
Summary 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.
Language eng
DOI 10.1093/bioinformatics/bts286
Field of Research 060199 Biochemistry and Cell Biology not elsewhere classified
Socio Economic Objective 970111 Expanding Knowledge in the Medical and Health Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2012, The Authors
Persistent URL http://hdl.handle.net/10536/DRO/DU:30087907

Document type: Journal Article
Collections: Faculty of Health
School of Medicine
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