Evidence map›Paper›PMID 25592595›Full record

ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2015

Kleat: cleavage site analysis of transcriptomes.

Inanç Birol, Anthony Raymond, Readman Chiu, Ka Ming Nip, Shaun D Jackman, Maayan Kreitzman, T Roderick Docking, Catherine A Ennis, A Gordon Robertson, Aly Karsan

Abstract read
In one paragraph

Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2015. 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.

  1. Review
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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

10 authors.

Inanç BirolCanada's Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, V5Z 4S6, Canada. ibirol@bcgsc.ca.
Anthony Raymond
Readman Chiu
Ka Ming Nip
Shaun D Jackman
Maayan Kreitzman
T Roderick Docking
Catherine A Ennis
A Gordon Robertson
Aly Karsan

Funding

De Novo Assembly Tools: Research with Unbiased Engines - Renewal (DNA-TRUER)R01HG007182 · NHGRI · PROVINCIAL HEALTH SERVICES AUTHORITY · PI BIROL, INANC · 2014 to 2022
$1.9M
Pan-cancer survey of candidate non-coding RNA transcripts on the cloud using a targeted de novo assembly approachR21CA187910 · NCI · BRITISH COLUMBIA CANCER AGENCY · PI BIROL, INANC · 2014 to 2016
$248k
Canadian Institutes of Health ResearchNCI NIH HHS R21 CA187910NHGRI NIH HHS R01 HG007182NHGRI NIH HHS R01HG007182
6 · The paper itself

Abstract

In eukaryotic cells, alternative cleavage of 3' untranslated regions (UTRs) can affect transcript stability, transport and translation. For polyadenylated (poly(A)) transcripts, cleavage sites can be characterized with short-read sequencing using specialized library construction methods. However, for large-scale cohort studies as well as for clinical sequencing applications, it is desirable to characterize such events using RNA-seq data, as the latter are already widely applied to identify other relevant information, such as mutations, alternative splicing and chimeric transcripts. Here we describe KLEAT, an analysis tool that uses de novo assembly of RNA-seq data to characterize cleavage sites on 3' UTRs. We demonstrate the performance of KLEAT on three cell line RNA-seq libraries constructed and sequenced by the ENCODE project, and assembled using Trans-ABySS. Validating the KLEAT predictions with matched ENCODE RNA-seq and RNA-PET libraries, we show that the tool has over 90% positive predictive value when there are at least three RNA-seq reads supporting a poly(A) tail and requiring at least three RNA-PET reads mapping within 100 nucleotides as validation. We also compare the performance of KLEAT with other popular RNA-seq analysis pipelines that reconstruct 3' UTR ends, and show that it performs favourably, based on an ROC-like curve.

Indexed as

Transcriptome3' Untranslated RegionsBinding SitesCell LineComputational BiologyGene LibraryHumansROC CurveSequence AlignmentSequence Analysis, RNA3' Untranslated Regions

Identifiers

PMID25592595
PMCPMC4350765

What OpenQuestion holds

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Registered trials

None linked

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.