Protein-DNA interactions are involved in many essential biological processes such as transcription, splicing, replication and DNA repair. ChIP-on-chip is a technique that combines chromatin immunoprecipitation with microarray technology. This technique is well suited for a comprehensive analysis of transcription factor binding sites, histone modification patterns, and nucleosome occupancy.
Provides a range of functionalities for ChIP data analyses. CisGenome allows visualization, data normalization, peak detection, false discovery rate (FDR) computation, gene-peak association, and sequence and motif analysis. The software can handle data from two types of designs common in ChIP-seq experiments. The basic functionalities of CisGenome can be used in combination to address several different biological questions.
A computational method that examines the ChIP-array-selected sequences and searches for DNA sequence motifs representing the protein-DNA interaction sites. MDscan combines the advantages of two widely adopted motif search strategies, word enumeration and position-specific weight matrix updating, and incorporates the ChIP-array ranking information to accelerate searches and enhance their success rates.
Discovers DNA motifs on protein binding microarray (PBM) data. kmerHMM is a computational pipeline for PBM motif discovery in which hidden markov models (HMMs) are trained to model DNA motifs, and Belief Propagation is used to elucidate multiple motif models from each trained HMM. The software model the dependence between adjacent nucleotide positions and can also deduce multiple binding modes for a given transcription factor (TF).
A software tool designed to characterize genome-wide protein-DNA interaction patterns from ChIP-chip and ChIP-Seq data. CEAS provides summary statistics on ChIP enrichment in important genomic regions such as individual chromosomes, promoters, gene bodies or exons, and infers the genes most likely to be regulated by the binding factor under study. CEAS also enables biologists to visualize the average ChIP enrichment signals over specific genomic regions, particularly allowing observation of continuous and broad ChIP enrichment that might be too subtle to detect from ChIP peaks alone.
A web-based application called Cistrome, based on the Galaxy open source framework. In addition to the standard Galaxy functions, Cistrome has 29 ChIP-chip- and ChIP-seq-specific tools in three major categories, from preliminary peak calling and correlation analyses to downstream genome feature association, gene expression analyses, and motif discovery.
A user-friendly software platform for genome-scale detection of known and novel motifs (recurring patterns) in DNA sequences, applicable to a wide range of motif discovery tasks. Amadeus outperforms extant tools and sets a new standard for motif discovery software in terms of accuracy, running time, range of application, wealth of output information and ease of use.
Performs peak detection in chromatin immunoprecipitation (ChIP)-chip signal. ChIPOTle was created for the analysis of ChIP-chip data obtained using tiled arrays, which allow to exploit both the 'single-tail' and 'neighbour effect'. The software uses a sliding window approach to identify potential sites of enrichment, and then estimates the significance of enrichment for a genomic region using a standard Gaussian error function. It also allows multiple correction testing, signal normalization, replication merging, and probe sorting.
Assesses statistical significance of transcription factor (TF)-binding from chromatin-immunoprecipitation/microarray (Chip²) data. Chipper computes p values without needing a separate control for developing a model of measurement error. It is able to return targets with significant p values. This tool does not require external control microarray experiments in order to parameterize error models.
Allows the integrative analysis of ChIP-chip/seq data across platforms and between laboratories. MM-ChIP proceeds by modeling the characteristic fragment size of the sequenced ChIP-DNA library for each individual data source. It uses then the 3’ direction to represent the protein-DNA interaction sites. Finally, a sliding window is used to score the significance of signal enrichment in the ChIP samples by measuring and comparing tags within the same windows between ChIP.
Detects transcription factor bound regions, which incorporate the dependence between probes while making little assumptions about the bound regions (e.g., length). BAC is robust to probe outliers with an exchangeable prior for the variances, which allows different variances for the probes but still shrink extreme empirical variances. Parameter estimation is carried out using Markov chain Monte Carlo and inference is based on the joint distribution of the parameters. Bound regions are detected using posterior probabilities computed from the joint posterior distribution of neighboring probes. It was showed that these posterior probabilities are well calibrated and can be used to obtain an estimate of the false discovery rate.
A computational tool to make tiling array analysis and to detect genomic loci that show hybridization patterns of interest. TileMap includes functions to (i) compute probe-level test-statistics according to the transcriptional or protein binding patterns specified by users; (ii) filter local repeats; and (iii) infer if a region is of interest or not by applying hidden markov model or moving window average (MA). Compared with previous tools, TileMap provides a flexible way to study tiling array hybridizations under multiple experimental conditions.
Assists in processing ChIP-chip and ChIP-seq data. W-ChIPeaks is a web application that employed a probe-based (or bin-based) enrichment threshold to define peaks and applied statistical methods to control false discovery rate for identified peaks. This resource includes two different web interfaces: probebased enrichment threshold level (PELT) for ChIP-chip and bin-based enrichment threshold level (BELT) for ChIP-seq.
A package that allows the identification of regions enriched for transcription factor binding sites in ChIP-chip experiments on Affymetrix tiling arrays. rMAT is based on the popular MAT software. It has been written in C and R and provides an efficient implementation of the functionality of MAT as well as statistical normalization techniques not available in the original MAT. We show that these model refinements can improve normalization and increase power when detecting enriched regions.
Allows users to jointly analyze ChIP-chip and ChIP-seq datasets using hidden Markov model (HHMM). ChIPmeta consists of method designed for combining ChIP-chip and ChIP-seq data, but the HHMM framework is rather general and can be applied to other scenarios where information collected from multiple sources may be integrated. The software can be useful in biomedical research.
Allows exploration of NimbleGen transcriptome data. ANAIS is a web-based tool for conducting all the analysis steps needed to interpret a NimbleGen expression experiment. The software includes six steps of analyses: (1) Normalization, (2) Probe to gene, (3) Quality controls, (4) Detection, (5) Differential analysis and (6) Queries and clustering. It accepts all one-colour NimbleGen expression array designs and produces graphical and numerical results.
Predicts biological contexts in which a transcription factor (TF) and its target genes are functionally active. ChIP-PED is a software which allows users to extend the scope of their ChIPx data to possibly novel biological systems without performing additional costly and time-consuming ChIPx experiments. Given a TF and its activated and repressed target genes defined using ChIPx and gene expression data in one or more biological contexts, the software searches for other contexts in which the TF is likely to be functionally active.
Analyzes ChIP experiments on transcription factors (TF) binding. CisFinder can proceed de novo identification and clustering of over-represented DNA motifs. This software extracts all over-represented motifs in a single run and describes them with estimated position frequency matrices (PFMs). It can process large sequences and data with a low-level enrichment of DNA motifs.
Provides summary statistics in graphs and offering several commonly demanded analyses. ChIPseek integrates HOMER et BEDTools software and enables peak annotation, locations, sequences and statistics such as charts and histograms for the visualization of the properties of the peaks. Users can explore peaks further via an UCSC genome browser. It contains filter tools to select interested peak subsets based on peak lengths and other characterictics.
Enables batch annotation of the binding sites identified from ChIP-seq, ChIP-chip, and CAGE. ChIPpeakAnno leverages the statistical environment R/Bioconductor with various sources of annotations, such as Ensembl, the UCSC genome database and others. This software permits users to compare set of peaks with any annotation feature objects, for example comparing to CpG islands, to conserved elements, or comparing two sets of peaks between replicates.