Sequencing of DNase I hypersensitive sites (DNase-seq) is a powerful technique for identifying cis-regulatory elements across the genome. Many people currently analyzing DNase-seq data are using tools designed for ChIP-seq work, but may be inappropriate for DNase-seq data.
A suite of tools for Motif Discovery and next-gen sequencing analysis. HOMER…
A suite of tools for Motif Discovery and next-gen sequencing analysis. HOMER contains many useful tools for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of…
A computational method for modeling the magnitude and shape of genome-wide…
A computational method for modeling the magnitude and shape of genome-wide DNase I hypersensitivity profiles to identify transcription factor (TF) binding sites. Through the use of machine-learning…
A detection algorithm that identifies regulatory features in ChIP-seq,…
A detection algorithm that identifies regulatory features in ChIP-seq, DNase-seq and FAIRE-seq data more accurately than assay-specific algorithms. The mathematical formalism underlying DFilter…
A library for analyzing DNase-seq data. Many people currently analyzing…
A library for analyzing DNase-seq data. Many people currently analyzing DNase-seq data are using tools designed for ChIP-seq work, but may be inappropriate for DNase-seq data where one is less…
Pipeline for analysis of deep sequencing data (ChIP-seq, DNaseI-seq).
Pipeline for analysis of deep sequencing data (ChIP-seq, DNaseI-seq).
Chooses a diverse panel of genomic assays that leverages methods from…
Chooses a diverse panel of genomic assays that leverages methods from submodular optimization. SSA serves as a model for how submodular optimization can be applied to other discrete problems in…
A peak-calling algorithm written in Perl, mainly intended for use in the…
A peak-calling algorithm written in Perl, mainly intended for use in the identification of peaks in mapped DNaseI-seq data. PeaKDEck also includes a set of utilities for processing and manipulation…
A broadly useful standalone tool for both interactive and batch analysis of…
A broadly useful standalone tool for both interactive and batch analysis of combined evidence from enriched regions (ERs) in multiple ChIP-seq or DNase-seq replicates. Besides rigorously combining…
Predicts transcription factors binding sites and epigenetic data by combining…
Predicts transcription factors binding sites and epigenetic data by combining sets of open-chromatin regions with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g.…
An R package and associated R Shiny web app for differential analysis of…
An R package and associated R Shiny web app for differential analysis of regulatory elements genome-wide using chromatin accessibility data, such as DNase-seq or ATAC-seq. Users can run the workflow…
Automates quality controls and data analyses on ChIP-seq and DNase-seq data.…
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…
An efficient footprint detection program. DNase2TF searches for relatively…
An efficient footprint detection program. DNase2TF searches for relatively protected regions within DNase I hypersensitive sites and generates a set of footprint candidates at a preset FDR threshold.…
Visualizes next-generation sequencing (NGS) signals and sequence motif…
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…
Enables the identification of protein binding footprints in DNase I…
Enables the identification of protein binding footprints in DNase I hypersensitive sites sequencing (DNase-seq) data. The cumulative Skellam distribution function (package 'skellam') is…
A supervised learning based footprint prediction framework. DeFCoM was designed…
A supervised learning based footprint prediction framework. DeFCoM was designed to capture variation in DNaseI signal within active footprints and unbound motif sites to enhance footprint…
A computational method for identifying individual transcription factor (TF)…
A computational method for identifying individual transcription factor (TF) binding sites from genome sequence information and cell-type–specific experimental data, such as DNase-seq. Romulus…
A mixture modeling framework to train multinomial based footprint models and…
A mixture modeling framework to train multinomial based footprint models and assign footprint likelihood scores to each candidate binding site. The modeling approach was also able to detect variation…
A discriminative algorithm for predicting TF-DNA interaction sites using…
A discriminative algorithm for predicting TF-DNA interaction sites using DNase-seq data. BinDNase implements an efficient method for selecting and extracting informative features from DNase I signal…
Applies a hierarchical Bayesian mixture model to infer regions of the genome…
Applies a hierarchical Bayesian mixture model to infer regions of the genome that are bound by particular transcription factors (TFs). CENTIPEDE starts by identifying a set of candidate binding sites…
An algorithm for accurately inferring transcription factor binding sites using…
An algorithm for accurately inferring transcription factor binding sites using chromatin accessibility data (DNase-seq, ATAC-seq). The hierarchical multiscale model underlying msCentipede identifies…
A logistic regression model. LR-DNase predicts binding sites for a specific…
A logistic regression model. LR-DNase predicts binding sites for a specific transcription factor (TF) using seven features derived from DNase-seq and genomic sequence. We calculate the area under the…
Integrates chromatin accessibility, motif scores, TF footprints, CpG/GC…
Integrates chromatin accessibility, motif scores, TF footprints, CpG/GC content, evolutionary conservation and other factors in an ensemble of TFCT-specific classifiers. Mocap uses sequence-derived…
A method based on hidden Markov models to integrate DNase I hypersensitivity…
A method based on hidden Markov models to integrate DNase I hypersensitivity and histone modifications occupancy for the detection of open chromatin regions and active binding sites. We have created…
Corrects batch effects (from multiple confounding variables) and library depth.…
Corrects batch effects (from multiple confounding variables) and library depth. ImpulseDE2 is a differential expression algorithm for longitudinal count data sets which arise in sequencing…
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