Sylamer is a system for finding significantly over or under-represented words in sequences according to a sorted gene list. Typically it is used to find significant enrichment or depletion of microRNA or siRNA seed sequences from microarray expression data. Sylamer is extremely fast and can be applied to genome-wide datasets with ease. Results are plotted in terms of a significance landscape plot. These plots show significance profiles for each word studied across the sorted genelist.
GENIE3 is an algorithm for the inference of gene regulatory networks from expression data. It decomposes the prediction of a regulatory network between p genes into p different regression problems. In each of the regression problems, the expression pattern of one of the genes (target gene) is predicted from the expression patterns of all the other genes (input genes), using tree-based ensemble methods Random Forests or Extra-Trees. The importance of an input gene in the prediction of the target gene expression pattern is taken as an indication of a putative regulatory link.
dynGENIE3 : Extension of GENIE3 for time series data
Mask is an R package and contains several functions to handle Affymetrix expression data. Its goal is to mask BAD probes that bias the expression results.
SpeCond performs a gene expression data analysis to detect condition-specific genes. Such genes are significantly up- or down-regulated in a small number of conditions.
CNAmet is an algorithm and R package that facilitates the integration of copy number, methylation and expression data. In addition to the CNAmet algorithm, the R package includes the S2N algorithm for the integration of copy number to expression data.
MATISSE (Module Analysis via Topology of Interactions and Similarity SEts) is a program for detection of functional modules using interaction networks and expression data. A functioncal module is a group of cellular components and their interactions that can be attributed a specific biological function.
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.