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.
Allows data-mining and visualization of next-generation sequencing (NGS) samples such as enrichment patterns of DNA-interacting proteins at functional genomic regions. ngs.plot has a built-in database of functional elements that facilitates the management of genomic coordinates for users. This software supports large sequencing data and is available through the Galaxy tool shed.
Allows analysis of enrichment-based epigenomic data. Repitools is an R package that provides several functions for quality assessment, visualization, summarization and statistical analysis of epigenomics experiments. The software utilizes aroma.affymetrix and several Bioconductor packages for various preprocessing steps. It includes for instance BayMeth for quantifying methylation. It was tested on Affymetrix and Nimblegen tiling microarrays and Illumina Genome Analyzer sequencing data.
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 clustering and visualization tool that enables the interactive exploration of genome-wide data. It is intended to "spark" insights into genome-scale data sets. The approach utilizes data clusters as a high-level visual guide and supports interactive inspection of individual regions within each cluster. The cluster view links to gene ontology analysis tools and the detailed region view connects to existing genome browser displays taking advantage of their wealth of annotation and functionality.
Allows comparison and integration of multiple ChIP-seq datasets and extraction of qualitative as well as quantitative information. seqMINER can handle the biological complexity of most experimental situations and proposes methods to the user for data classification according to the analysed features. In addition, through multiple graphical representations, seqMINER allows visualization and modelling of general as well as specific patterns in a given dataset.
Supplies a platform dedicated to the visualization and analyses of data belonging to diverse file formats and experimental protocols. metaseq is a library with the aim of furnishing: (i) a unified interface for ChIP-seq, RNA-seq, RNA immunoprecipitation and sequencing (RIP-seq) experiments, (ii) a mean for converting genomic signal into NumPy arrays as well as (iii) an access to data from commonly used file format such as BAM or GFF.
Annotates ChIP-seq data analysis. ChIPseeker supports annotating ChIP peaks and provides functions to visualize ChIP peaks coverage over chromosomes and profiles of peaks binding to TSS regions. Comparison of ChIP peak profiles and annotation are also supported. Moreover, it supports evaluating significant overlap among ChIP-seq datasets. Currently, ChIPseeker contains 15,000 bed file information from GEO database. These datasets can be downloaded and compare with user's own data to explore significant overlap datasets for inferring co-regulation or transcription factor complex for further investigation.
Computes tag density across functional features in parallel using multicores and a grid engine and to interactively explore it in a graphical user interface. iTagPlot allows you to stratify features by defining groups based on biological function and measurement, summary statistics and unsupervised clustering. iTagPlot uses an annotated list of genomic features in the BED format coupled with BED or BAM files of mapped reads to generate a tag density plot of the given feature with flanking upstream and downstream regions, the length of which is predetermined by the user.
Visualizes next-generation sequencing (NGS) signals and sequence motif densities along genomic features using average plots and heatmaps. It can also calculate sequence motif density profiles from reference genome. SeqPlots is useful both for exploratory data analyses and preparing replicable, publication quality plots. Other features of the software include collaboration and data sharing capabilities, as well as ability to store pre-calculated result matrixes, that combine many sequencing experiments and in-silico generated tracks with multiple different features.