CMARRT (Correlation, Moving Average, Robust and Rapid method on Tiling array) is an R package for the analysis of tiling array data that incorporates the correlation structures among probe measurements.
tilingArray provides functionality that can be useful for the analysis of high-density tiling microarray data (such as from Affymetrix genechips) for measuring transcript abundance and architecture.
TileMap is a tool designed for tiling array data analysis. It can be used to identify genomic loci that show transcriptional activities and transcription factor binding patterns of interest.
MAT (Model-based Analysis of Tiling-array) detect regions enriched by transcription factor chromatin immunoprecipitation (ChIP) on Affymetrix tiling arrays (ChIP-chip). MAT models the baseline probe behavior by considering probe sequence and copy number on each array. It standardizes the probe value through the probe model, eliminating the need for sample normalization. MAT uses an innovative function to score regions for ChIP enrichment, which allows robust P value and false discovery rate calculations. MAT can detect ChIP regions from a single ChIP sample, multiple ChIP samples, or multiple ChIP samples with controls with increasing accuracy. The single-array ChIP region detection feature minimizes the time and monetary costs for laboratories newly adopting ChIP-chip to test their protocols and antibodies and allows established ChIP-chip laboratories to identify samples with questionable quality that might contaminate their data.
TileShuffle is a software of detection of transcribed or differentially expressed segments in tiling array data by permutation testing.This package contains functions for the analysis of tiling array data. It implements a statistical approach to detect expression or differential expression in terms of differences from the background distribution that avoids any intensity-related parameters. Moreover, it reduces the most dominant tiling array biases using an affinity-dependent permutation in conjunction with a windowing approach.
