All software used or developed by the ENCODE Consortium
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- OpenMiChrom — sourceUsed to create an ensemble of 3D structures with chromatin dynamics simulation software with input data from the Sequence Annotations (bed file) from PyMEGABASE.
- PyMEGABASE — sourcePyMEGABASE is used to generate sequence annotations at the compartment and subcompartment level for physical modeling annotations.
- pandasPandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
- SwanSwan is a Python library designed for the analysis and visualization of transcriptomes.Software type: other
- AnalyzeSpearATACSoftware used to analyze Greenleaf lab's SpearATAC (perturbation followed by snATAC-seq) data.
- GraphReg — sourceGraphReg (Chromatin interaction aware gene regulatory modeling with graph attention networks) is a graph neural network based gene regulation model which integrates DNA sequence, 1D epigenomic data (such as chromatin accessibility and histone modifications), and 3D chromatin conformation data (such as Hi-C, HiChIP, Micro-C, HiCAR) to predict gene expression in an informative way.
- HiCDCPlus — sourceThe package HiCDCPlus provides methods to determine significant and differential chromatin interactions by use of a negative binomial generalized linear model, as well as implementations for TopDom to call topologically associating domains (TADs), and Juicer eigenvector to find the A/B compartments. This vignette explains the use of the package and demonstrates typical workflows on HiC and HiChIP data.
- ZeroneZerone discretizes several ChIP-seq replicates simultaneously and resolves conflicts between them. Publication available at: doi: 10.1093/bioinformatics/btw336
- Fastx Toolkit — sourceThe FASTX-Toolkit is a collection of command line tools for Short-Reads FASTA/FASTQ files preprocessing.
- 3d-dna — sourceWe begin with a series of iterative steps whose goal is to eliminate misjoins in the input scaffolds. Each step begins with a scaffold pool (initially, this pool is the set of input scaffolds themselves). The scaffolding algorithm is used to order and orient these scaffolds. Next, the misjoin correction algorithm is applied to detect errors in the scaffold pool, thus creating an edited scaffold pool. Finally, the edited scaffold pool is used as an input for the next iteration of the misjoin correction algorithm. The ultimate effect of these iterations is to reliably detect misjoins in the input scaffolds without removing correctly assembled sequence. After this process is complete, the scaffolding algorithm is applied to the revised input scaffolds, and the output – a single “megascaffold” which concatenates all the chromosomes – is retained for post-processing.
- bioraddbg ATAC-seq MACS2 — sourceThis Docker container provides an easy to use Docker interface to MACS2 for peak calling with settings tailored for Bio-Rad Single Cell ATAC-seq chemistry.
- bioraddbg ATAC-seq filter beads — sourceThis Docker container provides an easy to use Docker interface to a bead filtration tool with settings tailored for Bio-Rad Single Cell ATAC-seq chemistry. This container takes in .BAM files and performs "knee calling" to compute a bead barcode whitelist and jaccard index threshold for bead-to-droplet merging.
- bioraddbg ATAC-seq BWA — sourceThis Docker container provides an easy to use Docker interface to the BWA alignment tool with settings tailored for Bio-Rad ATAC-Seq chemistry.