2023
DOI: 10.15252/msb.202311627
|View full text |Cite
|
Sign up to set email alerts
|

GRaNIE and GRaNPA: inference and evaluation of enhancer‐mediated gene regulatory networks

Abstract: Enhancers play a vital role in gene regulation and are critical in mediating the impact of noncoding genetic variants associated with complex traits. Enhancer activity is a cell‐type‐specific process regulated by transcription factors (TFs), epigenetic mechanisms and genetic variants. Despite the strong mechanistic link between TFs and enhancers, we currently lack a framework for jointly analysing them in cell‐type‐specific gene regulatory networks (GRN). Equally important, we lack an unbiased way of assessing… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
18
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
5
3

Relationship

1
7

Authors

Journals

citations
Cited by 32 publications
(18 citation statements)
references
References 102 publications
0
18
0
Order By: Relevance
“…First, we built PSM-specific enhancer-mediated gene-regulatory network (eGRN) using the GRaNIE (Gene Regulatory Network Inference including Enhancers) method [29], which constructs eGRN based on co-variation of chromatin [i.e., transcription factor (TF) binding site] accessibility, TF expression and corresponding target gene expression across samples. We generated paired transcriptome [i.e., RNA sequencing (RNA-seq)] and chromatin accessibility [i.e., assay for transposase-accessible chromatin with sequence (ATAC-seq)] data from wild-type, non-cultured PSM tissues.…”
Section: Resultsmentioning
confidence: 99%
See 2 more Smart Citations
“…First, we built PSM-specific enhancer-mediated gene-regulatory network (eGRN) using the GRaNIE (Gene Regulatory Network Inference including Enhancers) method [29], which constructs eGRN based on co-variation of chromatin [i.e., transcription factor (TF) binding site] accessibility, TF expression and corresponding target gene expression across samples. We generated paired transcriptome [i.e., RNA sequencing (RNA-seq)] and chromatin accessibility [i.e., assay for transposase-accessible chromatin with sequence (ATAC-seq)] data from wild-type, non-cultured PSM tissues.…”
Section: Resultsmentioning
confidence: 99%
“…Enhancer-mediated gene regulatory network(eGRN) was constructed from the matched RNA-seq and ATAC-seq data (24 samples for each) ofthe PSM explants from E10.5 wild-type embryosusing the developer’s version of the now published GRaNIE package (https://bioconductor.org/packages/release/bioc/html/GRaNIE.html)[29]. Raw gene counts from RNA-seq datawere produced with a summarizeOverlaps func-tion from the GenomicAlignments R package(https://bioconductor.org/packages/release/bioc/html/GenomicAlignments.html) [62], corrected for different experimental batches usingCombat-seq function from the R package sva[63] and log2 normalised.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Analysts often place a threshold on TSS to CRE distances under which there is putatively high confidence for the association. These thresholds range from ∼1 kilobase (kb) to 100s of kb, with little justification provided for any given choice (Kamal et al 2023; You et al 2021; McDaniel et al 2016; Wang et al 2015). It is unlikely that any single TSS to gene distance threshold is appropriate in all contexts, and categorical thresholds generally result in limitations that impact all downstream analyses.…”
Section: Introductionmentioning
confidence: 99%
“…Recent advancements in single-cell multi-omics data have led to the development of new tools for predicting TR activity. For example, tools such as FigR[14], GRaNIE[15], DIRECT-NET[16] and GLUE[17] utilize paired or integrated multiome data as inputs and employ linear/non-linear regression methods to construct gene regulatory networks. Other tools, like CellOracle[18], offer pre-built GRNs or the ability to create custom-defined GRNs using scATAC-seq data.…”
Section: Introductionmentioning
confidence: 99%