ArticleNucleic acids research2017
CisMapper: predicting regulatory interactions from transcription factor ChIP-seq data.
Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 22 citations in OpenAlex.
- Integrative approaches based on genomic techniques in the functional studies on enhancers.Briefings in bioinformatics · 2023Review
- Article
- Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data.Genome biology · 2022Article
- Computational methods for the prediction of chromatin interaction and organization using sequence and epigenomic profiles.Briefings in bioinformatics · 2021Article
- T-Gene: improved target gene prediction.Bioinformatics (Oxford, England) · 2020Article
- Machine learning uncovers cell identity regulator by histone code.Nature communications · 2020Article
- Endoplasmic reticulum stress actively suppresses hepatic molecular identity in damaged liver.Molecular systems biology · 2020Article
- Transcriptional network dynamics during the progression of pluripotency revealed by integrative statistical learning.Nucleic acids research · 2020Article
- Common Regulatory Targets of NFIA, NFIX and NFIB during Postnatal Cerebellar Development.Cerebellum (London, England) · 2020Article
- Quantitative prediction of enhancer-promoter interactions.Genome research · 2020Article
- Testing Proximity of Genomic Regions to Transcription Start Sites and Enhancers Complements Gene Set Enrichment Testing.Frontiers in genetics · 2020Article
- 7C: Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs.BMC genomics · 2019Article
- Maternal obesity programs increased leptin gene expression in rat male offspring via epigenetic modifications in a depot-specific manner.Molecular metabolism · 2017Article
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
Identifying the genomic regions and regulatory factors that control the transcription of genes is an important, unsolved problem. The current method of choice predicts transcription factor (TF) binding sites using chromatin immunoprecipitation followed by sequencing (ChIP-seq), and then links the binding sites to putative target genes solely on the basis of the genomic distance between them. Evidence from chromatin conformation capture experiments shows that this approach is inadequate due to long-distance regulation via chromatin looping. We present CisMapper, which predicts the regulatory targets of a TF using the correlation between a histone mark at the TF's bound sites and the expression of each gene across a panel of tissues. Using both chromatin conformation capture and differential expression data, we show that CisMapper is more accurate at predicting the target genes of a TF than the distance-based approaches currently used, and is particularly advantageous for predicting the long-range regulatory interactions typical of tissue-specific gene expression. CisMapper also predicts which TF binding sites regulate a given gene more accurately than using genomic distance. Unlike distance-based methods, CisMapper can predict which transcription start site of a gene is regulated by a particular binding site of the TF.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.