Evidence map›Paper›PMID 28784090›Full record

ArticleBMC bioinformatics2017

Repliscan: a tool for classifying replication timing regions.

Gregory J Zynda, Jawon Song, Lorenzo Concia, Emily E Wear, Linda Hanley-Bowdoin, William F Thompson, Matthew W Vaughn

Abstract read
In one paragraph

Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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  9. LSD1 is required for euchromatic origin firing and replication timing.Signal transduction and targeted therapy · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Gregory J ZyndaTexas Advanced Computing Center, University of Texas at Austin, 10100 Burnet Road, Austin, 78758-4497, TX, USA.
Jawon SongTexas Advanced Computing Center, University of Texas at Austin, 10100 Burnet Road, Austin, 78758-4497, TX, USA.
Lorenzo ConciaDepartment of Plant and Microbial Biology, North Carolina State University, Raleigh, 27695-7612, NC, USA.
Emily E WearDepartment of Plant and Microbial Biology, North Carolina State University, Raleigh, 27695-7612, NC, USA.
Linda Hanley-BowdoinDepartment of Plant and Microbial Biology, North Carolina State University, Raleigh, 27695-7612, NC, USA.
William F ThompsonDepartment of Plant and Microbial Biology, North Carolina State University, Raleigh, 27695-7612, NC, USA.
Matthew W VaughnTexas Advanced Computing Center, University of Texas at Austin, 10100 Burnet Road, Austin, 78758-4497, TX, USA. vaughn@tacc.utexas.edu.ORCID http://orcid.org/0000-0002-1384-4283

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundReplication timing experiments that use label incorporation and high throughput sequencing produce peaked data similar to ChIP-Seq experiments. However, the differences in experimental design, coverage density, and possible results make traditional ChIP-Seq analysis methods inappropriate for use with replication timing.

resultsTo accurately detect and classify regions of replication across the genome, we present Repliscan. Repliscan robustly normalizes, automatically removes outlying and uninformative data points, and classifies Repli-seq signals into discrete combinations of replication signatures. The quality control steps and self-fitting methods make Repliscan generally applicable and more robust than previous methods that classify regions based on thresholds.

conclusionsRepliscan is simple and effective to use on organisms with different genome sizes. Even with analysis window sizes as small as 1 kilobase, reliable profiles can be generated with as little as 2.4x coverage.

Indexed as

DNA Replication TimingSoftwareGenomeGenome SizeHigh-Throughput Nucleotide SequencingSequence Analysis, DNAClassificationDNA replicationRepli-seq

Identifiers

PMID28784090
PMCPMC5547489

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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.