Provides web applications, as well as modular analysis pipelines for high-throughput sequencing (HTS) data analysis. HTSstation workflows rely on interconnected modules revolving around the sequence mapping which uses Bowtie to map sequencing reads to a reference genome or sequence database, and calculates genome-wide coverage profiles. The software offers several applications, such as mapping, analysis of ChIP-seq peaks, a e RNA-seq procedure, modules for 4C-seq and for applying SAMtools pileup to detect discordant bases in reads aligned to a reference genome.
Simplifies the Hi-C data pre-processing, contact matrix transformation, and topologically associating domain (TAD) calling into a few easy steps. HiCExplorer is a tool-suite that can be used with other pipelines and processing tools as we have built-in import/export functions covering commonly used Hi-C data formats. This method works with HiCBrowser, a browser and an underlying program to visualize Hi-C and other genomic tracks.
A software package for rigorous detection of differential interactions from Hi-C data. diffHic provides methods for read pair alignment and processing, counting into bin pairs, filtering out low-abundance events and normalization of trended or CNV-driven biases. It uses the statistical framework of the edgeR package to model biological variability and to test for significant differences between conditions. Several options for the visualization of results are also included. On real data, diffHic is able to successfully detect interactions with significant differences in intensity between biological conditions. It also compares favourably to existing software tools on simulated data sets. diffHic is able to accommodate complex experimental designs, including paired or blocked designs and those with more than two groups. It does this by accessing the generalized linear model functionality of edgeR.
Provides a toolbox for analysis and visualization of Hi-C data. 4D Nucleome Analysis Toolbox includes features for time series and karyotypically abnormal cell types analysis. The toolbox also offers functions necessary to (1) load Hi-C matrices into MATLAB, (2) normalize data using three different methods, (3) define topologically associating domains (TADs) using three different methods, (4) visualize translocations and (5) explore time series data.