Analyses sparse chromatin accessibility data. chromVAR estimates the gain or loss of accessibility within sets of peaks sharing the same motif or annotation while controlling for known technical biases. It enables accurate clustering of scATAC-seq profiles and enables characterization of known, or the de novo identification of novel, sequence motifs associated with variation in chromatin accessibility across single cells or other sparse epigenomic data sets.
Aims to identify accurate normalization controls for assay for transposase-accessible chromatin (ATAC) –quantitative polymerase chain reaction (qPCR). APT is a program assisting researchers to detect optimal regions for ATAC-qPCR primers within peaks by comparing the number of spanning fragments in overlapping windows to the normalized peak height across samples. Moreover, it includes functionalities for the identification of custom normalization controls based on user-supplied ATAC-seq data.
Allows for unsupervised clustering and identification of cluster specific peaks for single cell ATAC-seq (scATAC-seq) data. scABC can deconvolve the underlying population structure by being applied to scATAC-seq data of complex mixtures. This software is appropriate for the identification of informative peaks for downstream analysis. It only utilizes the read counts within peaks to detect informative peaks and enables further analysis in an unbiased manner on the content of the peaks.
Examines epigenomic and transcriptomic next generation sequencing (NGS) data. Octopus-toolkit can be used for antibody- or enzyme-mediated experiments and studies for the quantification of gene expression. It can accelerate the data mining of public epigenomic and transcriptomic NGS data for basic biomedical research. This tool provides a private and a public mode: one to process the user’s own data, and the other to analyze public NGS data by retrieving raw files from the GEO database.
Allows detection of collaborative transcription factor pairs. MMARGE consists of a suite of software tools to analyze ChIP-seq, ATAC-seq, DNase I Hypersensitivity or other next generation sequencing (NGS) assays where genotyping or DNA sequence data is available. For performing, this tool needs two types of data: (1) genetic variation, and (2) high-throughput sequencing data (ChIP-seq, ATAC-seq, DNaseI-seq).
Offers a workflow for processing single-cell assay for transposase-accessible chromatin (ATAC-seq). ScAsAT is a scalable pipeline composed of four parts: (i) data processing; (ii) extraction of the features; (iii) investigating heterogeneity in cells and (iv) analyzing the differential accessibility of the peaks against two cluster of cells. It aims to increase grasp about epigenetic mechanisms at the single-cell level.
Executes and facilitates assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) analysis. esATAC needs low amount of biological sample to identify open chromatin peak regions unsing F-seq and covers raw data processing, downstream statistical analysis and several quality control (QC) functions. This software offers to users pre-set pipelines available through a command line interface.
Allows users to evaluate the achievement of their assay for transposase-accessible chromatin (ATAC) enrichment experiment and determine what further preparative work is required. atacR is based around three major steps: data loading and inspection, identification of best targets to use for normalization, and detection of differential count estimates. It provides functions that make each step of the workflow straightforward and assists researchers to make these potentially complex analyses more reproducible and the components reuseable in different contexts.
Serves as a pipeline for general analysis of chromatin accessibility data obtained from ATAC-seq experiments. ATAC-pipe exploits genome-wide chromatin accessibility, signatures of significant peaks, transcription factors (TFs) occupancy and nucleosome positions around regulatory. This software can also combine RNA-seq experiments with gene expression information to produce a scheme to construct complex regulatory networks.
Provides a pipeline for executing chromatin profiling assays. ATAC2GRN gathers optimized ATAC-seq and DNase1-seq pipelines to assess accurate genome regulatory network (GRN) inference. This software assists for maximizing ChIP recovery for transcription factor occupancy assessment. The project is composed of three main parts: one to generate figures, one part in both bash and Snakemake for the pipelines and the last one to estimate pipeline recapitulation of ChIP-seq.
Deduces changes in transcription factor (TF) activity from assay for transposase-accessible chromatin followed by sequencing (ATAC-seq) data. DaStK can be integrated at the tail-end of a traditional processing pipeline for ATAC-seq data, in which motif displacement (MD)-scores are calculated directly from called peaks and genomic sequence. It can be useful to evaluate and measure differences in chromatin accessibility across conditions.
Enables optimal processing of datasets from different enrichment patterns. Epimetheus is a quantile-based multi-profile normalization tool. Users have the possibility to exclude specific genomic regions like, for example, repetitive elements or any other genomic locations for which artefactual enrichments might be expected. The Epimetheus pipeline involves four main steps: (i) processing of the raw alignment data, (ii) generation of read count intensity (RCI) matrices, (iii) computation of two subsequent levels of normalization (quantile and Zscore) and (iv) generation of outputs and plots.
Represents epigenomic data by k-mer words associated with epigenomic mark. BROCKMAN enables the investigation of variation in k-mer occupancy across single cells as a basis for distinguishing different cell types, states, and treatments. It is based on matrix factorization and dimensionality reduction. This tool can be used to find differentially active transcription factors (TFs) and to interpret TF-TF interactions.
Facilitates processing of Assay for Transposase-Accessible Chromatin with high throughput sequencing (ATAC-seq) samples. I-ATAC is an interactive and cross-platform software that aims to facilitate data analysis for scientists generating data. It has been tested on ATAC-seq single and paired end data (in-house and publicly available) at The Jackson Laboratory for Genomics Medicine and UConn Health Center, USA. The software can also be used to perform quality checking and pre-preprocessing of whole genome sequencing (WGS) and ChIP-seq data.
Determines open chromatin regions and plausible transcription factor binding sites (TFBS) from single ATAC-seq data. HMMRATAC is based on an algorithm able to consider all the spectrum of the fragment lengths. This application uses a hidden Markov model able to split a dataset into multiple layers standing for different chromatin features and lastly exploits them to rearrange patterns. This application was tested on three standards datasets.
Predicts the location of genome-wide regulatory activity. DeppATAC is a deep-learning model that is jointly trained on both ATAC-seq and DNA sequence. It is able to successfully integrate DNA sequence and ATAC-seq signal. This tool can capture subtle signals such as footprints to make more accurate predictions. It captures the enrichment of binding activity in ATAC-seq signals. DeepATAC was trained on the subset of DeepSEA data.
Merges co-accessible regions into regulatory topics and ranks cells according their regulatory topic contributions. cisTopic first produces a binary accessibility matrix, selects both latent Dirichlet allocation and a specific model, and then, uses the topic cell distributions from LDA to identify cell state, to lastly browse region-topic distributions. This program can be applied to the forecasting of combinations of transcription factors in motif discovery or to investigate dynamic changes in chromatin state.
Assists users in analyzing next-generation sequencing (NGS) data. snakePipes provides DNA-mapping, ChIP-seq, ATAC-seq, RNA-seq, whole-genome bisulfite-seq (WGBS), HiC and single-cell RNA-seq workflows. It employs extensive quality-checks and produces reports that inform users about processing and analysis results. It provides workflows that allow processing and downstream analysis of data in an allele-specific manner.
Consists of an enrichment test for transcription factor (TF) footprinting data studies. BiFET can mimic true TF binding events and is able to recognize TFs whose footprints are over-represented in target regions compared to background regions. It employs DNase-seq or ATAC-seq data to make shape detection and motif-driven. This tool enables users to differentiate the most probable regulators of cell- or disease-specific functions from potentially spurious ones.
Performs transcriptional network analysis of gynecologic and basal breast cancer tumors. PSIONIC allows to integrate regulatory genomics resources with tumor expression data to examine gene regulation in cancers and interpret patient-specific transcriptional programs. This program can also be employed to predict activity for transcription factors (TFs) in cell line models correlated with sensitivity to TF inhibition.