ArticleIEEE/ACM transactions on computational biology and bioinformatics
An Annotation Agnostic Algorithm for Detecting Nascent RNA Transcripts in GRO-Seq.
Article in IEEE/ACM transactions on computational biology and bioinformatics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 25 citations in OpenAlex.
- Atlas of nascent RNA transcripts reveals tissue-specific enhancer to gene linkages.BMC genomics · 2025Article
- LIET model: capturing the kinetics of RNA polymerase from loading to termination.Nucleic acids research · 2025Article
- TF Profiler: a transcription factor inference method that broadly measures transcription factor activity and identifies mechanistically distinct networks.Genome biology · 2025Article
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- Deconvolution of multiplexed transcriptional responses to wood smoke particles defines rapid aryl hydrocarbon receptor signaling dynamics.The Journal of biological chemistry · 2021Article
- PEPPRO: quality control and processing of nascent RNA profiling data.Genome biology · 2021Article
- Global Analyses to Identify Direct Transcriptional Targets of p53.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Liver Transcriptome Dynamics During Hibernation Are Shaped by a Shifting Balance Between Transcription and RNA Stability.Frontiers in physiology · 2021Article
- Article
- Epigenetic and transcriptional profiling of triple negative breast cancer.Scientific data · 2019Article
- Control of inducible gene expression links cohesin to hematopoietic progenitor self-renewal and differentiation.Nature immunology · 2018Article
- Nascent RNA sequencing analysis provides insights into enhancer-mediated gene regulation.BMC genomics · 2018Article
- Detecting Differential Transcription Factor Activity from ATAC-Seq Data.Molecules (Basel, Switzerland) · 2018Article
- Genome-wide dose-dependent inhibition of histone deacetylases studies reveal their roles in enhancer remodeling and suppression of oncogenic super-enhancers.Nucleic acids research · 2018Article
- A generative model for the behavior of RNA polymerase.Bioinformatics (Oxford, England) · 2017Article
- RNA Pol II transcription model and interpretation of GRO-seq data.Journal of mathematical biology · 2017Article
- Cistrome-based Cooperation between Airway Epithelial Glucocorticoid Receptor and NF-κB Orchestrates Anti-inflammatory Effects.The Journal of biological chemistry · 2016Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
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Abstract
We present a fast and simple algorithm to detect nascent RNA transcription in global nuclear run-on sequencing (GRO-seq). GRO-seq is a relatively new protocol that captures nascent transcripts from actively engaged polymerase, providing a direct read-out on bona fide transcription. Most traditional assays, such as RNA-seq, measure steady state RNA levels which are affected by transcription, post-transcriptional processing, and RNA stability. GRO-seq data, however, presents unique analysis challenges that are only beginning to be addressed. Here, we describe a new algorithm, Fast Read Stitcher (FStitch), that takes advantage of two popular machine-learning techniques, hidden Markov models and logistic regression, to classify which regions of the genome are transcribed. Given a small user-defined training set, our algorithm is accurate, robust to varying read depth, annotation agnostic, and fast. Analysis of GRO-seq data without a priori need for annotation uncovers surprising new insights into several aspects of the transcription process.
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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.