Showing 32 of total 32 results (show query)

bioc

bnbc:Bandwise normalization and batch correction of Hi-C data

Tools to normalize (several) Hi-C data from replicates.

Maintained by Kipper Fletez-Brant. Last updated 5 months ago.

hicpreprocessingnormalizationsoftwarecpp

30.3 match 1 stars 3.88 score 15 scripts

bioc

Chicago:CHiCAGO: Capture Hi-C Analysis of Genomic Organization

A pipeline for analysing Capture Hi-C data.

Maintained by Mikhail Spivakov. Last updated 5 months ago.

epigeneticshicsequencingsoftware

10.3 match 4.81 score 32 scripts

bioc

GRaNIE:GRaNIE: Reconstruction cell type specific gene regulatory networks including enhancers using single-cell or bulk chromatin accessibility and RNA-seq data

Genetic variants associated with diseases often affect non-coding regions, thus likely having a regulatory role. To understand the effects of genetic variants in these regulatory regions, identifying genes that are modulated by specific regulatory elements (REs) is crucial. The effect of gene regulatory elements, such as enhancers, is often cell-type specific, likely because the combinations of transcription factors (TFs) that are regulating a given enhancer have cell-type specific activity. This TF activity can be quantified with existing tools such as diffTF and captures differences in binding of a TF in open chromatin regions. Collectively, this forms a gene regulatory network (GRN) with cell-type and data-specific TF-RE and RE-gene links. Here, we reconstruct such a GRN using single-cell or bulk RNAseq and open chromatin (e.g., using ATACseq or ChIPseq for open chromatin marks) and optionally (Capture) Hi-C data. Our network contains different types of links, connecting TFs to regulatory elements, the latter of which is connected to genes in the vicinity or within the same chromatin domain (TAD). We use a statistical framework to assign empirical FDRs and weights to all links using a permutation-based approach.

Maintained by Christian Arnold. Last updated 5 months ago.

softwaregeneexpressiongeneregulationnetworkinferencegenesetenrichmentbiomedicalinformaticsgeneticstranscriptomicsatacseqrnaseqgraphandnetworkregressiontranscriptionchipseq

5.7 match 5.40 score 24 scripts