Statistics for ChIP-chip and DNase hypersensitivity experiments on NimbleGen arrays.
Data obtained from high-density oligonucleotide tiling arrays present new computational challenges for users. This chapter presents ACME (Algorithm for Capturing Microarray Enrichment), a computer program developed for the analysis of data obtained using NimbleGen-tiled microarrays. ACME identifies signals or "peaks" in tiled array data using a simple sliding window and threshold strategy and assigns a probability value (p value) to each and every probe on the array. We present data indicating that this approach can be applied successfully to at least two different genomic applications involving tiled arrays: ChIP-chip and DNase-chip. In addition to highlighting previously described methods for analyzing tiled array data, we provide recommendations for assessing the quality of ChIP-chip and DNase-chip data, suggestions for optimizing the use of ACME, and descriptions of several of ACME features designed to facilitate interpretation of processed tiled array data. ACME is written in R language and is freely available upon request or through Bioconductor.
Scacheri
Peter C
PC
Department of Genetics, Case Western Reserve University, Cleveland, OH, USA.
Crawford
Gregory E
GE
Davis
Sean
S
D000465:Algorithms; D000818:Animals; D004247:DNA / Q000378:metabolism; D003627:Data Interpretation, Statistical; D003851:Deoxyribonucleases / Q000502:physiology; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000706:statistics & numerical data*; D012984:Software
D004247:DNA; D003851:Deoxyribonucleases