S4Vectors S4 implementation of vectors and lists
The S4Vectors package defines the Vector and List virtual classes and a set of generic functions that extend the semantic of ordinary vectors and lists in R. Package developers can easily implement vector-like or list-like objects as concrete subclasses of Vector or List. In addition, a few low-level concrete subclasses of general interest (e.g. DataFrame, Rle, and Hits) are implemented in the S4Vectors package itself (many more are implemented in the IRanges package and in other Bioconductor infrastructure packages).
fastLiquidAssociation functions for genome-wide application of Liquid Association
This package extends the function of the LiquidAssociation package for genome-wide application. It integrates a screening method into the LA analysis to reduce the number of triplets to be examined for a high LA value and provides code for use in subsequent significance analyses.
ChIPseeker ChIPseeker for ChIP peak Annotation, Visualization and Comparison
This package implements functions to retrieve the nearest genes around the peak, annotate genomic region of the peak. Visualization functions are implemented to summarize genomic annotation, distance to TSS, and overlap of peaks or genes.
NetPathMiner NetPathMiner for Biological Network Construction, Path Mining and Visualization
NetPathMiner is a general framework for network path mining using genome-scale networks. It constructs networks from KGML, SBML and BioPAX files, providing three network representations, metabolic, reaction and gene representations. NetPathMiner finds active paths and applies machine learning methods to summarize found paths for easy interpretation. It also provides static and interactive visualizations of networks and paths to aid manual investigation.
meshr Tools for conducting enrichment analysis of MeSH
A set of annotation maps describing the entire MeSH assembled using data from MeSH
MeSHDbi DBI to construct MeSH-related package from sqlite file.
The package is unified implementation of MeSH.db, MeSH.AOR.db, and MeSH.PCR.db and also is interface to construct Gene-MeSH package (org.MeSH.XXX.db). loadMeSHDbiPkg import sqlite file and generate org.MeSH.XXX.db.
GenomicFiles Parallel queries distributed by file or by range
This package provides infrastructure for parallel queries distributed 'by file' or 'by range'. User defined map and reduce functions provide added flexibility for data combination and manipulation.
gaucho Genetic Algorithms for Understanding Clonal Heterogeneity and Ordering
Use genetic algorithms to determine the relationship between clones in heterogenous populations such as cancer sequencing samples
RefNet A queryable collection of molecular interactions, from many sources
Molecular interactions with metadata, some archived, some dynamically obtained
compcodeR RNAseq data simulation, differential expression analysis and performance comparison of differential expression methods
This package provides extensive functionality for comparing results obtained by different methods for differential expression analysis of RNAseq data. It also contains functions for simulating count data and interfaces to several packages for performing the differential expression analysis.
TitanCNA Subclonal copy number and LOH prediction whole genome sequencing of tumours
Hidden Markov model to segment and predict regions of subclonal copy number alterations (CNA) and loss of heterozygosity (LOH), and estimate cellular prevalenece of clonal clusters in tumour whole genome sequencing data.
npGSEA Permutation approximation methods for gene set enrichment analysis (non-permutation GSEA)
Current gene set enrichment methods rely upon permutations for inference. These approaches are computationally expensive and have minimum achievable p-values based on the number of permutations, not on the actual observed statistics. We have derived three parametric approximations to the permutation distributions of two gene set enrichment test statistics. We are able to reduce the computational burden and granularity issues of permutation testing with our method, which is implemented in this package. npGSEA calculates gene set enrichment statistics and p-values without the computational cost of permutations. It is applicable in settings where one or many gene sets are of interest. There are also built-in plotting functions to help users visualize results.
Sushi Tools for visualizing genomics data
Flexible, quantitative, and integrative genomic visualizations for publication-quality multi-panel figures
DMRforPairs DMRforPairs: identifying Differentially Methylated Regions between unique samples using array based methylation profiles
DMRforPairs allows researchers to compare n>=2 unique samples with regard to their methylation profile. The (pairwise) comparison of n unique single samples distinguishes DMRforPairs from other existing pipelines as these often compare groups of samples in either single CpG locus or region based analysis. DMRforPairs defines regions of interest as genomic ranges with sufficient probes located in close proximity to each other. Probes in one region are optionally annotated to the same functional class(es). Differential methylation is evaluated by comparing the methylation values within each region between individual samples and (if the difference is sufficiently large), testing this difference formally for statistical significance.
VariantFiltering Filtering of coding and non-coding genetic variants
Filter genetic variants using different criteria such as inheritance model, amino acid change consequence, minimum allele frequencies across human populations, splice site strength, conservation, etc.
CoverageView Coverage visualization package for R
This package provides a framework for the visualization of genome coverage profiles. It can be used for ChIP-seq experiments, but it can be also used for genome-wide nucleosome positioning experiments or other experiment types where it is important to have a framework in order to inspect how the coverage distributed across the genome
metaMS MS-based metabolomics annotation pipeline
MS-based metabolomics data processing and compound annotation pipeline.
flowCL flowCL: Semantic labelling of flow cytometric cell populations
Semantic labelling of flow cytometric cell populations.
BiocCheck Bioconductor-specific package checks
Bioconductor-specific package checks
Rariant Identification and Assessment of Single Nucleotide Variants through Shifts in Non-Consensus Base Call Frequencies
The 'Rariant' package identifies single nucleotide variants from sequencing data based on the difference of binomially distributed mismatch rates between matched samples.
FRGEpistasis Epistasis Analysis for Quantitative Traits by Functional Regression Model
A Tool for Epistasis Analysis Based on Functional Regression Model
flowCyBar Analyze flow cytometric data using gate information
A package to analyze flow cytometric data using gate information to follow population/community dynamics
CompGO An R pipeline for .bed file annotation, comparing GO term enrichment between gene sets and data visualisation
This package contains functions to accomplish several tasks. It is able to download full genome databases from UCSC, import .bed files easily, annotate these .bed file regions with genes (plus distance) from aforementioned database dumps, interface with DAVID to create functional annotation and gene ontology enrichment charts based on gene lists (such as those generated from input .bed files) and finally visualise and compare these enrichments using either directed acyclic graphs or scatterplots.
ChIPQC Quality metrics for ChIPseq data
Quality metrics for ChIPseq data
ABSSeq ABSSeq: a new RNA-Seq analysis method based on absolute expression differences and generalized Poisson model
Inferring differential expression genes by absolute expression differences between two groups, utilizing generalized Poisson model to account for over-dispersion across samples and heterogeneity of differential expression across genes.
ASSIGN Adaptive Signature Selection and InteGratioN (ASSIGN)
ASSIGN is a computational tool to evaluate the pathway deregulation/activation status in individual patient samples. ASSIGN employs a flexible Bayesian factor analysis approach that adapts predetermined pathway signatures derived either from knowledge-based literatures or from perturbation experiments to the cell-/tissue-specific pathway signatures. The deregulation/activation level of each context-specific pathway is quantified to a score, which represents the extent to which a patient sample encompasses the pathway deregulation/activation signature.
nondetects Non-detects in qPCR data
Methods to model and impute non-detects in the results of qPCR experiments.
messina Single-gene classifiers and outlier-resistant detection of differential expression for two-group and survival problems.
Messina is a collection of algorithms for constructing optimally robust single-gene classifiers, and for identifying differential expression in the presence of outliers or unknown sample subgroups. The methods have application in identifying lead features to develop into clinical tests (both diagnostic and prognostic), and in identifying differential expression when a fraction of samples show unusual patterns of expression.
viper Virtual Inference of Protein-activity by Enriched Regulon analysis
Inference of protein activity from gene expression data, including the VIPER and msVIPER algorithms
UNDO Unsupervised Deconvolution of Tumor-Stromal Mixed Expressions
UNDO is an R package for unsupervised deconvolution of tumor and stromal mixed expression data. It detects marker genes and deconvolutes the mixing expression data without any prior knowledge.
sapFinder A package for variant peptides detection and visualization in shotgun proteomics.
sapFinder is developed to automate (1) variation-associated database construction, (2) database searching, (3) post-processing, (4) HTML-based report generation in shotgun proteomics.
Rcpi Toolkit for Compound-Protein Interaction in Drug Discovery
The Rcpi package offers an R/Bioconductor package emphasizing the comprehensive integration of bioinformatics and chemoinformatics into a molecular informatics platform for drug discovery.
QDNAseq Quantitative DNA sequencing for chromosomal aberrations
Quantitative DNA sequencing for chromosomal aberrations.
rpx R Interface to the ProteomeXchange Repository
This package implements an interface to proteomics data submitted to the ProteomeXchange consortium.
MLSeq Machine learning interface for RNA-Seq data
This package applies several machine learning methods, including SVM, bagSVM, Random Forest and CART, to RNA-Seq data.
metaseqR metaseqR: an R package for the analysis and result reporting of RNA-Seq gene expression data using multiple statistical algorithms.
Provides an interface to several normalization and statistical testing packages for RNA-Seq gene expression data. Additionally, it creates several diagnostic plots, performs meta-analysis by combinining the results of several statistical tests and reports the results in an interactive way.
massiR massiR: MicroArray Sample Sex Identifier
Predicts the sex of samples in gene expression microarray datasets
INPower An R package for computing the number of susceptibility SNPs
An R package for computing the number of susceptibility SNPs and power of future studies
COPDSexualDimorphism Sexual dimorphic and COPD differential analysis for gene expression and methylation.
Sexual dimoprhic and COPD differential (SDCD) analysis contrasts regression coefficients from two stratified analysis. Stratification can be done in two ways: by COPD status or by sex. For COPD-stratified analysis, SDCD analysis contrasts sexual dimorphism between cases and controls, while sex-stratified SDCD analsysis contrasts COPD differential expression pattern between males and females. The package is meant to be used in conjunction with the package limma.
CAFE Chromosmal Aberrations Finder in Expression data
Detection and visualizations of gross chromosomal aberrations using Affymetrix expression microarrays as input
Basic4Cseq Basic4Cseq: an R/Bioconductor package for analyzing 4C-seq data
Basic4Cseq is an R/Bioconductor package for basic filtering, analysis and subsequent visualization of 4C-seq data. Virtual fragment libraries can be created for any BSGenome package, and filter functions for both reads and fragments and basic quality controls are included. Fragment data in the vicinity of the experiment's viewpoint can be visualized as a coverage plot based on a running median approach and a multi-scale contact profile.
alsace ALS for the Automatic Chemical Exploration of mixtures
Alternating Least Squares (or Multivariate Curve Resolution) for analytical chemical data, in particular hyphenated data where the first direction is a retention time axis, and the second a spectral axis. Package builds on the basic als function from the ALS package and adds functionality for high-throughput analysis, including definition of time windows, clustering of profiles, retention time correction, etcetera.
dualKS Dual KS Discriminant Analysis and Classification
This package implements a Kolmogorov Smirnov rank-sum based algorithm for training (i.e. discriminant analysis--identification of genes that discriminate between classes) and classification of gene expression data sets. One of the chief strengths of this approach is that it is amenable to the "multiclass" problem. That is, it can discriminate between more than 2 classes.
Clomial Infers clonal composition of a tumor
Clomial fits binomial distributions to counts obtained from Next Gen Sequencing data of multiple samples of the same tumor. The trained parameters can be interpreted to infer the clonal structure of the tumor.
scsR SiRNA correction for seed mediated off-target effect
Corrects genome-wide siRNA screens for seed mediated off-target effect. Suitable functions to identify the effective seeds/miRNAs and to visualize their effect are also provided in the package.
EDDA Experimental Design in Differential Abundance analysis
EDDA can aid in the design of a range of common experiments such as RNA-seq, Nanostring assays, RIP-seq and Metagenomic sequencing, and enables researchers to comprehensively investigate the impact of experimental decisions on the ability to detect differential abundance.
DMRcate Illumina 450K methylation array spatial analysis methods
De novo identification and extraction of differentially methylated regions (DMRs) in the human genome using Illumina Infinium HumanMethylation450 BeadChip array data. Provides functionality for filtering probes possibly confounded by SNPs and cross-hybridisation. Includes bedGraph and plotting functions.
unifiedWMWqPCR Unified Wilcoxon-Mann Whitney Test for testing differential expression in qPCR data
This packages implements the unified Wilcoxon-Mann-Whitney Test for qPCR data. This modified test allows for testing differential expression in qPCR data.
sangerseqR Tools for Sanger Sequencing Data in R
This package contains several tools for analyzing Sanger Sequencing data files in R, including reading .scf and .ab1 files, making basecalls and plotting chromatograms.
CopyNumber450k R package for calling CNV from Illumina 450k methylation microarrays
This package contains a set of functions that allow CNV calling from Illumina 450k methylation microarrays.
GSCA GSCA: Gene Set Context Analysis
GSCA takes as input several lists of activated and repressed genes. GSCA then searches through a compendium of publicly available gene expression profiles for biological contexts that are enriched with a specified pattern of gene expression. GSCA provides both traditional R functions and interactive, user-friendly user interface.
COMPASS Combinatorial Polyfunctionality Analysis of Single Cells
COMPASS is a statistical framework that enables unbiased analysis of antigen-specific T-cell subsets. COMPASS uses a Bayesian hierarchical framework to model all observed cell-subsets and select the most likely to be antigen-specific while regularizing the small cell counts that often arise in multi-parameter space. The model provides a posterior probability of specificity for each cell subset and each sample, which can be used to profile a subject's immune response to external stimuli such as infection or vaccination.
CNEr CNE detection and visualization.
Large-scale identification and advanced visualization of sets of conserved noncoding elements.
MIMOSA Mixture Models for Single-Cell Assays
Modeling count data using Dirichlet-multinomial and beta-binomial mixtures with applications to single-cell assays.
Detect synergistic miRNA regulatory modules by overlapping neighbourhood expansion.
SomaticSignatures Somatic Signatures
The SomaticSignatures package identifies mutational signatures of single nucleotide variants (SNVs).
trackViewer light package to plot elegant track layers
plot ChIP-seq, RNA-seq, miRNA-seq, DNA-seq and etc NGS sequence data, especially for big files.
iClusterPlus Integrative clustering of multi-type genomic data
Integrative clustering of multiple genomic data using a joint latent variable model
AtlasRDF Gene Expression Atlas query and gene set enrichment package.
Query the Gene Expression Atlas RDF data at the European Bioinformatics Institute using genes, experimental factors (such as disease, cell type, compound treatments), pathways and proteins. Also contains a function to perform an enrichment of your gene list across Experimental Factor Ontology (EFO) using the Atlas background set.
GeneOverlap Test and visualize gene overlaps
Test two sets of gene lists and visualize the results.
COHCAP City of Hope CpG Island Analysis Pipeline
This package provides a pipeline to analyze single-nucleotide resolution methylation data (Illumina 450k methylation array, targeted BS-Seq, etc.). It provides QC metrics, differential methylation for CpG Sites, differential methylation for CpG Islands, integration with gene expression data, and visualization of methylation values.
asmn All sample mean normalization.
Performs all sample mean normalization using raw data output from BeadStudio and MethyLumiM data.
geneRxCluster gRx Differential Clustering
Detect Differential Clustering of Genomic Sites such as gene therapy integrations. The package provides some functions for exploring genomic insertion sites originating from two different sources. Possibly, the two sources are two different gene therapy vectors. Vectors are preferred that target sensitive regions less frequently, motivating the search for localized clusters of insertions and comparison of the clusters formed by integration of different vectors. Scan statistics allow the discovery of spatial differences in clustering and calculation of False Discovery Rates (FDRs) providing statistical methods for comparing retroviral vectors. A scan statistic for comparing two vectors using multiple window widths to detect clustering differentials and compute FDRs is implemented here.
flowBin Combining multitube flow cytometry data by binning
Software to combine flow cytometry data that has been multiplexed into multiple tubes with common markers between them, by establishing common bins across tubes in terms of the common markers, then determining expression within each tube for each bin in terms of the tube-specific markers.
roar Identify differential APA usage from RNA-seq alignments
Identify preferential usage of APA sites, comparing two biological conditions, starting from known alternative sites and alignments obtained from standard RNA-seq experiments.
PhenStat Statistical analysis of phenotypic data
Package contains methods for statistical analysis of phenotypic data such as Mixed Models and Fisher Exact Test.
The CCREPE (Compositionality Corrected by REnormalizaion and PErmutation) package is designed to assess the significance of general similarity measures in compositional datasets. In microbial abundance data, for example, the total abundances of all microbes sum to one; CCREPE is designed to take this constraint into account when assigning p-values to similarity measures between the microbes. The package has two functions: ccrepe: Calculates similarity measures, p-values and q-values for relative abundances of bugs in one or two body sites using bootstrap and permutation matrices of the data. nc.score: Calculates species-level co-variation and co-exclusion patterns based on an extension of the checkerboard score to ordinal data.
flowMatch Matching and meta-clustering in flow cytometry
Matching cell populations and building meta-clusters and templates from a collection of FC samples.
PECA Probe-level Expression Change Averaging
Calculates Probe-level Expression Change Averages (PECA) to identify differential expression in Affymetrix gene expression microarray studies or in proteomic studies using peptide-level mesurements respectively.
mmnet What the package does (short line)
This package gives the implementations microbiome metabolic network constructing and analyzing. It introduces a unique metagenomic systems biology approach, mapping metagenomic data to the KEGG global metabolic pathway and constructing a systems-level network. The system-level network and the next topological analysis will be of great help to analysis the various functional properties, including regulation and metabolic functionality of the metagenome.
CRISPRseek Design of target-specific guide RNAs in CRISPR-Cas9, genome-editing systems
The package includes functions to find potential guide RNAs for input target sequences, optionally filter guide RNAs without restriction enzyme cut site, or without paired guide RNAs, genome-wide search for off-targets, score, rank, fetch flank sequence and indicate whether the target and off-targets are located in exon region or not. Potential guide RNAs are annotated with total score of the top5 and topN off-targets, detailed topN mismatch sites, restriction enzyme cut sites, and paired guide RNAs. This package leverages Biostrings and BSgenome packages.
GOTHiC Binomial test for Hi-C data analysis
This is a Hi-C analysis package using a cumulative binomial test to detect interactions between distal genomic loci that have significantly more reads than expected by chance in Hi-C experiments. It takes mapped paired NGS reads as input and gives back the list of significant interactions for a given bin size in the genome.
GenomicAlignments Representation and manipulation of short genomic alignments
Provides efficient containers for storing and manipulating short genomic alignments (typically obtained by aligning short reads to a reference genome). This includes read counting, computing the coverage, junction detection, and working with the nucleotide content of the alignments.
CNVrd2 CNVrd2: a read depth-based method to detect and genotype complex common copy number variants from next generation sequencing data.
CNVrd2 uses next-generation sequencing data to measure human gene copy number for multiple samples, indentify SNPs tagging copy number variants and detect copy number polymorphic genomic regions.
PSICQUIC Protemics Standard Initiative Common QUery InterfaCe
PSICQUIC is a project within the HUPO Proteomics Standard Initiative (HUPO-PSI). It standardises programmatic access to molecular interaction databases.
h5vc Managing alignment tallies using a hdf5 backend
This package contains functions to interact with tally data from NGS experiments that is stored in HDF5 files. For detail see the webpage at http://www.ebi.ac.uk/~pyl/h5vc.
metaSeq Meta-analysis of RNA-Seq count data in multiple studies
The probabilities by one-sided NOISeq are combined by Fisher's method or Stouffer's method
interactiveDisplay Package for enabling powerful shiny web displays of Bioconductor objects
The interactiveDisplay package contains the methods needed to generate interactive Shiny based display methods for Bioconductor objects.
ChAMP Chip Analysis Methylation Pipeline for Illumina HumanMethylation450
The package includes quality control metrics, a selection of normalization methods and novel methods to identify differentially methylated regions and to highlight copy number aberrations.
flipflop Fast lasso-based isoform prediction as a flow problem
Flipflop discovers which isoforms of a gene are expressed in a given sample together with their abundances, based on RNA-Seq read data.
FGNet Functional gene networks derived from biological enrichment analyses
Build and visualize functional gene networks from clustering of enrichment analyses in multiple annotation spaces. The package includes an interface to perform the analysis through David and GeneTerm Linker.
TFBSTools Software package for transcription factor binding site (TFBS) analysis
TFBSTools is a package for the analysis and manipulation of transcription factor binding sites and transcription factor profile matrices.
sRAP Simplified RNA-Seq Analysis Pipeline
This package provides a pipeline for gene expression analysis (primarily for RNA-Seq data). The normalization function is specific for RNA-Seq analysis, but all other functions (Quality Control Figures, Differential Expression and Visualization, and Functional Enrichment via BD-Func) will work with any type of gene expression data.
spliceSites Manages align gap positions from RNA-seq data
Align gap positions from RNA-seq data
shinyTANDEM Provides a GUI for rTANDEM
This package provides a GUI interface for rTANDEM. The GUI is primarily designed to visualize rTANDEM result object or result xml files. But it will also provides an interface for creating parameter objects, launching searches or performing conversions between R objects and xml files.
qcmetrics A Framework for Quality Control
The package provides a framework for generic quality control of data. It permits to create, manage and visualise individual or sets of quality control metrics and generate quality control reports in various formats.
openCyto Hierarchical Gating Pipeline for flow cytometry data
This package is designed to facilitate the automated gating methods in sequential way to mimic the manual gating strategy.
MSstats Protein Significance Analysis in DDA, SRM and DIA for Label-free or Label-based Proteomics Experiments
A set of tools for statistical relative protein significance analysis in DDA, SRM and DIA experiments.
methylMnM detect different methylation level (DMR)
To give the exactly p-value and q-value of MeDIP-seq and MRE-seq data for different samples comparation.
flowMap A probabilistic algorithm for matching and comparing multiple flow cytometry samples
This package provides an algorithm to compare and match cell populations across multiple flow cytometry samples. The method is based on the Friedman-Rafsky test, a nonparametric multivariate statistical test, where two cell distributions match if they occupy a similar feature space. The algorithm allows the users to specify a reference sample for comparison or to construct a reference sample from the available data. The output of the algorithm is a set of text files where the cell population labels are replaced by a metaset of population labels, generated from the matching process.
The package is developed for the analysis of affinity-based epitranscriptome shortgun sequencing data from MeRIP-seq (maA-seq). It was built on the basis of the exomePeak MATLAB package (Meng, Jia, et al. "Exome-based analysis for RNA epigenome sequencing data." Bioinformatics 29.12 (2013): 1565-1567.) with new functions for differential analysis of two experimental conditions to unveil the dynamics in post-transcriptional regulation of the RNA methylome. The exomePeak R-package accepts and statistically supports multiple biological replicates, internally removes PCR artifacts and multi-mapping reads, outputs exome-based binding sites (RNA methylation sites) and detects differential post-transcriptional RNA modification sites between two experimental conditions in term of percentage rather the absolute amount. The package is still under active development, and we welcome all biology and computation scientist for all kinds of collaborations and communications. Please feel free to contact Dr. Jia Meng
if you have any questions.
epivizr R Interface to epiviz web app
This package provides Websocket communication to the epiviz web app (http://epiviz.cbcb.umd.edu) for interactive visualization of genomic data. Objects in R/bioc interactive sessions can be displayed in genome browser tracks or plots to be explored by navigation through genomic regions. Fundamental Bioconductor data structures are supported (e.g., GenomicRanges and SummarizedExperiment objects), while providing an easy mechanism to support other data structures. Visualizations (using d3.js) can be easily added to the web app as well.
DNaseR DNase I footprinting analysis of DNase-seq data
Strand-specific digital genomic footprinting in DNase-seq data. The cumulative Skellam distribution function (package 'skellam') is used to detect significant normalized count differences of opposed sign at each DNA strand. This is done in order to determine the protein-binding footprint flanks. Preprocessing of the mapped reads is recommended before running DNaseR (e.g., quality checking and removal of sequence-specific bias).
Visualize significant conserved amino acid sequence pattern in groups based on probability theory
CexoR An R package to uncover high-resolution protein-DNA interactions in ChIP-exo replicates
Strand specific peak-pair calling in ChIP-exo replicates. The cumulative Skellam distribution function (package 'skellam') is used to detect significant normalized count differences of opposed sign at each DNA strand (peak-pairs). Irreproducible discovery rate for overlapping peak-pairs across biological replicates is estimated using the package 'idr'.
bioassayR R library for Bioactivity analysis
bioassayR provides tools for statistical analysis of small molecule bioactivity data
ampliQueso Analysis of amplicon enrichment panels
The package provides tools and reports for the analysis of amplicon sequencing panels, such as AmpliSeq
AllelicImbalance Investigates allele specific expression
Provides a framework for allelic specific expression investigation using RNA-seq data
STRINGdb STRINGdb (Search Tool for the Retrieval of Interacting proteins database)
The STRINGdb package provides a user-friendly interface to the STRING protein-protein interactions database ( http://www.string-db.org ).
SimBindProfiles Similar Binding Profiles
SimBindProfiles identifies common and unique binding regions in genome tiling array data. This package does not rely on peak calling, but directly compares binding profiles processed on the same array platform. It implements a simple threshold approach, thus allowing retrieval of commonly and differentially bound regions between datasets as well as events of compensation and increased binding.
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