Quality assessment software tools | ChIP sequencing data analysis
The absence of a quality control (QC) system is a major weakness for the comparative analysis of genome-wide profiles generated by next-generation sequencing (NGS). This concerns particularly genome binding/occupancy profiling assays like chromatin immunoprecipitation (ChIP-seq) but also related enrichment-based studies like methylated DNA immunoprecipitation/methylated DNA binding domain sequencing, global run on sequencing or RNA-seq.
Provides tools for both low and high-level analysis of next generation, ultra-high throughput signature sequencing data. USeq is an R package that aims to support the development of next generation sequencing data analysis applications. The software contains more than 25 command line applications written in Java, including ChIP-Seq Apps, RNA-Seq Apps, RNA Editing Apps, Sam Alignment Apps, or Converter Apps.
Computes quick but highly informative enrichment and quality measures for ChIP-seq/DNase-seq/FAIRE-seq/MNase-seq data. It can also be used to obtain robust estimates of the predominant fragment length or characteristic tag shift values in these assays. Phantompeakqualtools can be used to (i) Compute the predominant insert-size (fragment length) based on strand cross-correlation peak; (ii) compute data quality measures based on relative phantom peak; (iii) call peaks and regions for punctate binding datasets
Automates quality controls and data analyses on ChIP-seq and DNase-seq data. ChiLin generates comprehensive quality control reports that include comparisons with historical data derived from over 23,677 public ChIP-seq and DNase-seq samples (11,265 datasets) from eight literature-based classified categories. Therefore, ChiLin can be an attractive solution to rapidly process batches of ChIP-seq datasets in an automated manner with detailed QC reports.
Allows peak calling, visualization, quality check and Polymerase Chain Reaction (PCR) bias filtering of ChIP-seq data. DROMPA calls peaks by comparing the read distribution of the ChIP sample with that of the corresponding input sample. The software identifies peaks as bar graph protein-binding sites when the peaks are sharp (approximately 1 kbp) and when they are broad (approximately 1 Mbp). It can accept multiple mapped reads (reads mapped on multiple loci of the reference genome).
Assists in the analysis of ChIP-seq. CCAT is a general-purpose framework that provides a linear signal-noise model for ChIP-seq analysis with negative control. This application estimates the noise rate using control library and derived a library-swapping approach for false discovery rate (FDR) estimation. An option of bootstrapping is also included in this method.
Assists users to evaluate the quality of ChIP-seq. The NGS-QC database hosts quality scores for over 28,000 datasets, covering a variety of ChIP-sequencing and related assays performed from about 8 species (Homo sapiens: 54%; Mus musculus: 34%; D. melanogaster: 6%). It contains an algorithm designed to: (i) infer a set of global QC indicators (QCis); or to (ii) provide local QCis to judge the robustness of cumulative read counts in a particular region.
Allows users to discretize ChIP-seq data. Zerone combines an arbitrary number of ChIP-seq replicates in a single discretized profile, where conflicts are resolved by maximizing the likelihood of the underlying statistical model. This program controls the quality of its output to detect potential anomalies. This tool produces congruent window-based outputs, and it can process hundreds of experiments per day on average hardware.