ArticleGenome research2013
PRISM offers a comprehensive genomic approach to transcription factor function prediction.
Article in Genome research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- WhichTF is functionally important in your open chromatin data?PLoS computational biology · 2022Article
- Article
- Transcriptional regulation ofFrontiers in cell and developmental biology · 2022Article
- Transcription Factor PLAGL1 Is Associated with Angiogenic Gene Expression in the Placenta.International journal of molecular sciences · 2020Article
- A functional enrichment test for molecular convergent evolution finds a clear protein-coding signal in echolocating bats and whales.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Combined analysis of dissimilar promoter accessibility and gene expression profiles identifies tissue-specific genes and actively repressed networks.Epigenetics & chromatin · 2019Article
- An MTF1 binding site disrupted by a homozygous variant in the promoter of ATP7B likely causes Wilson Disease.European journal of human genetics : EJHG · 2018Article
- Independent erosion of conserved transcription factor binding sites points to shared hindlimb, vision and external testes loss in different mammals.Nucleic acids research · 2018Article
- A screen for deeply conserved non-coding GWAS SNPs uncovers a MIR-9-2 functional mutation associated to retinal vasculature defects in human.Nucleic acids research · 2018Article
- Evolutionary analysis across mammals reveals distinct classes of long non-coding RNAs.Genome biology · 2016Article
- Erosion of Conserved Binding Sites in Personal Genomes Points to Medical Histories.PLoS computational biology · 2016Article
- Changes in the enhancer landscape during early placental development uncover a trophoblast invasion gene-enhancer network.Placenta · 2016Article
- Integrating motif, DNA accessibility and gene expression data to build regulatory maps in an organism.Nucleic acids research · 2015Article
- A family of transposable elements co-opted into developmental enhancers in the mouse neocortex.Nature communications · 2015Article
- Motif enrichment tool.Nucleic acids research · 2014Article
- Automated discovery of tissue-targeting enhancers and transcription factors from binding motif and gene function data.PLoS computational biology · 2014Article
- A comprehensive collection of systems biology data characterizing the host response to viral infection.Scientific data · 2014Article
- Structure-aided prediction of mammalian transcription factor complexes in conserved non-coding elements.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2013Article
- Computational methods to detect conserved non-genic elements in phylogenetically isolated genomes: application to zebrafish.Nucleic acids research · 2013Article
- The enhancer landscape during early neocortical development reveals patterns of dense regulation and co-option.PLoS genetics · 2013Article
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7 authors.
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Abstract
The human genome encodes 1500-2000 different transcription factors (TFs). ChIP-seq is revealing the global binding profiles of a fraction of TFs in a fraction of their biological contexts. These data show that the majority of TFs bind directly next to a large number of context-relevant target genes, that most binding is distal, and that binding is context specific. Because of the effort and cost involved, ChIP-seq is seldom used in search of novel TF function. Such exploration is instead done using expression perturbation and genetic screens. Here we propose a comprehensive computational framework for transcription factor function prediction. We curate 332 high-quality nonredundant TF binding motifs that represent all major DNA binding domains, and improve cross-species conserved binding site prediction to obtain 3.3 million conserved, mostly distal, binding site predictions. We combine these with 2.4 million facts about all human and mouse gene functions, in a novel statistical framework, in search of enrichments of particular motifs next to groups of target genes of particular functions. Rigorous parameter tuning and a harsh null are used to minimize false positives. Our novel PRISM (predicting regulatory information from single motifs) approach obtains 2543 TF function predictions in a large variety of contexts, at a false discovery rate of 16%. The predictions are highly enriched for validated TF roles, and 45 of 67 (67%) tested binding site regions in five different contexts act as enhancers in functionally matched cells.
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