ArticleBMC genomics2022
Protocol variations in run-on transcription dataset preparation produce detectable signatures in sequencing libraries.
Article in BMC genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Improving calls of differentially transcribed enhancers and their upstream regulators.Bioinformatics advances · 2026Article
- Improving confidence of differential transcription calls in enhancers.bioRxiv : the preprint server for biology · 2025Article
- 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
- Internal and external normalization of nascent RNA sequencing run-on experiments.BMC bioinformatics · 2024Article
- Transcription dosage compensation does not occur in Down syndrome.BMC biology · 2023Article
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5 authors.
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Abstract
backgroundA variety of protocols exist for producing whole genome run-on transcription datasets. However, little is known about how differences between these protocols affect the signal within the resulting libraries.
resultsUsing run-on transcription datasets generated from the same biological system, we show that a variety of GRO- and PRO-seq preparation methods leave identifiable signatures within each library. Specifically we show that the library preparation method results in differences in quality control metrics, as well as differences in the signal distribution at the 5
conclusionsRun-on sequencing protocol variations result in technical signatures that can be used to identify both the enrichment and library preparation method of a particular data set. These technical signatures are batch effects that limit detailed comparisons of pausing ratios and eRNAs identified across protocols. However, these batch effects have only limited impact on our ability to infer which regulators underlie the observed transcriptional changes.
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