ENCODE Software
Software tools implemented and developed by the consortium for computational analysis
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- 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.
- interpretation_samples — sourceInterpretation code for Segway samples that produces classifier output and diagnostic plots from the apply_samples.py, for test samples.Software type: genome segmentation
- sQTLseekeR — sourcesQTLseekeR is a package to detect splicing QTLs (sQTLs), which are variants associated with change in the splicing pattern of a gene. In sQTLSeeker, splicing patterns are modeled by the relative expression of the transcripts of a gene. The most recent version of sQTLseekeR can be employed to detect genetic variant associated to any multivariate phenotypeSoftware type: variant annotation
- ggsashimi — sourcea command-line tool for the visualization of splicing events across multiple samples. Given a specified genomic region, ggsashimi creates sashimi plots for individual RNA-seq experiments as well as aggregated plots for groups of experiments. It uses popular bioinformatics file formats, it is annotation-independent, and allows the visualization of splicing events even for large genomic regions by scaling down the genomic segments between splice sites. It is implemented in python, and internally generates R code for plotting.Software type: visualization
- scPOST — sourceSimulation of single-cell datasets for power analyses that estimate power to detect cell state frequency shifts between conditions (e.g. an expansion of a cell state in disease vs. healthy), as described in our manuscript “Maximizing statistical power to detect clinically associated cell states with scPOST”.Software type: other
- cdr3-QTL — sourceWe tested associations between HLA genotypes and TCR-CDR3 amino acid compositions. We treated the amino acid composition of CDR3 as a quantitative trait, and tested its association with HLA genotype; we call this CDR3 quantitative trait loci analysis (cdr3-QTL), as described in our manuscript “HLA autoimmune risk alleles restrict the hypervariable region of T cell receptors”.Software type: other
- Imperio — sourceThis software includes (i) DeepBoost, a gradient boosting method for constructing boosted deep learning annotations by integrating deep learning allelic-effect annotations with fine-mapped SNPs; (ii) tools to combine these deep learning annotations with SNP-to-gene (S2G) linking strategies and relevant gene sets, and (iii) Imperio, a method for integrating deep learning annotations with S2G strategies to predict gene expression in whole blood and construct allelic-effect annotations based on changes in predicted expression. Applications of these 3 approaches to blood-related traits are described in our manuscript “Integrative approaches to improve the informativeness of deep learning models for human complex diseases”.Software type: other
- GSSG — sourceGSSG consists of tools to generate enhancer-driven and master-regulator gene scores in blood, and combine these gene scores with distal and proximal SNP-to-gene (S2G) linking strategies to construct SNP annotations for blood-related traits, as described in our manuscript “Unique contribution of enhancer-driven and master-regulator genes to autoimmune disease revealed using functionally informed SNIP-to-gene linking strategies”.Software type: other
- rtracklayer — sourceExtensible framework for interacting with multiple genome browsers (currently UCSC built-in) and manipulating annotation tracks in various formats (currently GFF, BED, bedGraph, BED15, WIG, BigWig and 2bit built-in). The user may export/import tracks to/from the supported browsers, as well as query and modify the browser state, such as the current viewport.
- Genomic Alignments — sourceProvides 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.
- vcf2diploid — sourceCreates phased diploid genomes variants from a vcf file by integrating variants to a reference genome.Software type: variant annotation
- snow — sourceThe snow package provides support for simple parallel computing on a network of workstations using R. A master R process calls makeCluster to start a cluster of worker processes; the master process then uses functions such as clusterCall and clusterApply to execute R code on the worker processes and collect and return the results on the master. This framework supports many forms of "embarrassingly parallel" computations.Software type: other
- Genomedata — sourceEfficiently stores multiple tracks of numeric data anchored to a genome. The format allows fast random access to hundreds of gigabytes of data, while retaining a small disk space footprint. Utilities have also been developed to load data into this format. A reference implementation in Python and C components is available under the GNU General Public License.
- Segway — sourceUses a machine learning method to analyze multiple tracks of functional genomics data, searching for recurring patterns. The software automatically partitions the genome into non-overlapping segments and assigns each segment a label. The resulting annotation provides a human-interpretable summary of the functional landscape of the genome, yielding hypotheses about novel instances or classes of functional elements.Software type: genome segmentation
- Segtools — sourceA Python package that analyzes genomic segmentations. The software efficiently calculates a variety of summary statistics and produces corresponding publication quality visualizations. The overall goal of Segtools is to provide a bird's-eye view of complex genomic data sets, allowing researchers to easily generate and confirm hypotheses.Software type: genome segmentation