Evidence map›Paper›PMID 27812418›Full record

ArticlePeerJ2016

The PARA-suite: PAR-CLIP specific sequence read simulation and processing.

Andreas Kloetgen, Arndt Borkhardt, Jessica I Hoell, Alice C McHardy

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 23% of its field
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

7 citing papers in PubMed, 10 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Andreas KloetgenDepartment for Algorithmic Bioinformatics, Heinrich-Heine Universität Düsseldorf, Düsseldorf, Germany; Department of Pediatric Oncology, Hematology and Clinical Immunology, Medical Faculty, Heinrich-Heine Universität Düsseldorf, Düsseldorf, Germany; Computational Biology of Infection Research, Helmholtz Center for Infection Research, Braunschweig, Germany.
Arndt BorkhardtDepartment of Pediatric Oncology, Hematology and Clinical Immunology, Medical Faculty, Heinrich-Heine Universität Düsseldorf , Düsseldorf , Germany.
Jessica I HoellDepartment of Pediatric Oncology, Hematology and Clinical Immunology, Medical Faculty, Heinrich-Heine Universität Düsseldorf , Düsseldorf , Germany.
Alice C McHardyDepartment for Algorithmic Bioinformatics, Heinrich-Heine Universität Düsseldorf, Düsseldorf, Germany; Computational Biology of Infection Research, Helmholtz Center for Infection Research, Braunschweig, Germany.
Heinrich Heine University Düsseldorf · DEHelmholtz Centre for Infection Research · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNext-generation sequencing technologies have profoundly impacted biology over recent years. Experimental protocols, such as photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation (PAR-CLIP), which identifies protein-RNA interactions on a genome-wide scale, commonly employ deep sequencing. With PAR-CLIP, the incorporation of photoactivatable nucleosides into nascent transcripts leads to high rates of specific nucleotide conversions during reverse transcription. So far, the specific properties of PAR-CLIP-derived sequencing reads have not been assessed in depth.

methodsWe here compared PAR-CLIP sequencing reads to regular transcriptome sequencing reads (RNA-Seq) to identify distinctive properties that are relevant for reference-based read alignment of PAR-CLIP datasets. We developed a set of freely available tools for PAR-CLIP data analysis, called the PAR-CLIP analyzer suite (PARA-suite). The PARA-suite includes error model inference, PAR-CLIP read simulation based on PAR-CLIP specific properties, a full read alignment pipeline with a modified Burrows-Wheeler Aligner algorithm and CLIP read clustering for binding site detection.

resultsWe show that differences in the error profiles of PAR-CLIP reads relative to regular transcriptome sequencing reads (RNA-Seq) make a distinct processing advantageous. We examine the alignment accuracy of commonly applied read aligners on 10 simulated PAR-CLIP datasets using different parameter settings and identified the most accurate setup among those read aligners. We demonstrate the performance of the PARA-suite in conjunction with different binding site detection algorithms on several real PAR-CLIP and HITS-CLIP datasets. Our processing pipeline allowed the improvement of both alignment and binding site detection accuracy. AVAILABILITY: The PARA-suite toolkit and the PARA-suite aligner are available at https://github.com/akloetgen/PARA-suite and https://github.com/akloetgen/PARA-suite_aligner, respectively, under the GNU GPLv3 license.

Indexed as

Cross-linking and immunoprecipitation (CLIP)Next-generation sequencingPosttranscriptional regulationRead alignmentRead simulationRNA-binding proteins

Identifiers

PMID27812418
PMCPMC5088580
OpenAlexW2539781216

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.