title: SRMA: an R package for resequencing array data analysis.
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.
  
  
  BACKGROUND
  http://cran.r-project.org/, http://odin.mdacc.tmc.edu/~wwang7/SRMAIndex.html
authors.affiliation: Department of Bioinformatics and Computational Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA.
authors.forename: Nianxiang
authors.initials: N
authors.lastname: Zhang
authors.forename: Yan
authors.initials: Y
authors.lastname: Xu
authors.forename: Martin
authors.initials: M
authors.lastname: O'Hely
authors.forename: Terence P
authors.initials: TP
authors.lastname: Speed
authors.forename: Curt
authors.initials: C
authors.lastname: Scharfe
authors.forename: Wenyi
authors.initials: W
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software