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FStitch: a fast and simple algorithm for detecting nascent RNA transcripts

Authors:

Joseph Azofeifa,

Manuel Lladser,

Robin DowellAuthors Info & Claims

BCB '14: Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics

Pages 174 - 183

https://doi.org/10.1145/2649387.2649427

Published: 20 September 2014 Publication History

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. A detailed study of GRO-seq data has the potential to inform on many aspects of the transcription process. 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, a hidden Markov model (HMM) and logistic regression to robustly classify which regions of the genome are transcribed. Our algorithm builds on the strengths of previous approaches but is accurate, dependent on very little training data, robust to varying read depth, annotation agnostic, and fast.

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Cited By

Gupta ASasse SBerman RGruca MDowell RChu HDowney GGerber A(2022)Integrated genomics approaches identify transcriptional mediators and epigenetic responses to Afghan desert particulate matter in small airway epithelial cellsPhysiological Genomics10.1152/physiolgenomics.00063.202254:10(389-401)Online publication date: 1-Oct-2022
https://doi.org/10.1152/physiolgenomics.00063.2022
Tripodi IChowdhury MGruca MDowell R(2020)Combining signal and sequence to detect RNA polymerase initiation in ATAC-seq dataPLOS ONE10.1371/journal.pone.023233215:4(e0232332)Online publication date: 30-Apr-2020
https://doi.org/10.1371/journal.pone.0232332
Tripodi IAllen MDowell R(2018)Detecting Differential Transcription Factor Activity from ATAC-Seq DataMolecules10.3390/molecules2305113623:5(1136)Online publication date: 10-May-2018
https://doi.org/10.3390/molecules23051136
Show More Cited By

Index Terms

FStitch: a fast and simple algorithm for detecting nascent RNA transcripts
1. Applied computing
  1. Life and medical sciences

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Published In

cover image ACM Conferences

BCB '14: Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics

September 2014

851 pages

ISBN:9781450328944

DOI:10.1145/2649387

General Chairs:
Pierre Baldi
University of California, Irvine
,
Wei Wang
University of California, Los Angeles

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 20 September 2014

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September 20 - 23, 2014

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Cited By

Gupta ASasse SBerman RGruca MDowell RChu HDowney GGerber A(2022)Integrated genomics approaches identify transcriptional mediators and epigenetic responses to Afghan desert particulate matter in small airway epithelial cellsPhysiological Genomics10.1152/physiolgenomics.00063.202254:10(389-401)Online publication date: 1-Oct-2022
https://doi.org/10.1152/physiolgenomics.00063.2022
Tripodi IChowdhury MGruca MDowell R(2020)Combining signal and sequence to detect RNA polymerase initiation in ATAC-seq dataPLOS ONE10.1371/journal.pone.023233215:4(e0232332)Online publication date: 30-Apr-2020
https://doi.org/10.1371/journal.pone.0232332
Tripodi IAllen MDowell R(2018)Detecting Differential Transcription Factor Activity from ATAC-Seq DataMolecules10.3390/molecules2305113623:5(1136)Online publication date: 10-May-2018
https://doi.org/10.3390/molecules23051136
Azofeifa JAllen MLladser MDowell R(2017)An Annotation Agnostic Algorithm for Detecting Nascent RNA Transcripts in GRO-SeqIEEE/ACM Transactions on Computational Biology and Bioinformatics10.1109/TCBB.2016.252091914:5(1070-1081)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1109/TCBB.2016.2520919
Azofeifa JDowell R(2016)A generative model for the behavior of RNA polymeraseBioinformatics10.1093/bioinformatics/btw59933:2(227-234)Online publication date: 23-Sep-2016
https://doi.org/10.1093/bioinformatics/btw599
Lladser MAzofeifa JAllen MDowell R(2016)RNA Pol II transcription model and interpretation of GRO-seq dataJournal of Mathematical Biology10.1007/s00285-016-1014-474:1-2(77-97)Online publication date: 3-May-2016
https://doi.org/10.1007/s00285-016-1014-4

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