Evidence map›Paper›PMID 27540267›Full record

ArticleBioinformatics (Oxford, England)2016

ReadXplorer 2-detailed read mapping analysis and visualization from one single source.

Rolf Hilker, Kai Bernd Stadermann, Oliver Schwengers, Evgeny Anisiforov, Sebastian Jaenicke, Bernd Weisshaar, Tobias Zimmermann, Alexander Goesmann

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing 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

56 citing papers in PubMed.

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  6. CRISPR-Cas9-driven genome editing inFrontiers in microbiology · 2025
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  7. Sigma Factor Engineering inMicroorganisms · 2024
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  17. Activation and Identification of a Griseusin Cluster inMolecules (Basel, Switzerland) · 2021
    Article
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  20. Article
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

8 authors.

Rolf HilkerBioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, Giessen 35392, Germany.
Kai Bernd StadermannFaculty of Biology, Chair of Genome Research, Bielefeld University, Bielefeld 33615, Germany.
Oliver SchwengersBioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, Giessen 35392, Germany.
Evgeny AnisiforovBioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, Giessen 35392, Germany.
Sebastian JaenickeBioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, Giessen 35392, Germany.
Bernd WeisshaarFaculty of Biology, Chair of Genome Research, Bielefeld University, Bielefeld 33615, Germany.
Tobias ZimmermannBioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, Giessen 35392, Germany.
Alexander GoesmannBioinformatics and Systems Biology, Faculty of Biology and Chemistry, Justus-Liebig-University, Giessen 35392, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationThe vast amount of already available and currently generated read mapping data requires comprehensive visualization, and should benefit from bioinformatics tools offering a wide spectrum of analysis functionality from just one source. Appropriate handling of multiple mapped reads during mapping analyses remains an issue that demands improvement.

resultsThe capabilities of the read mapping analysis and visualization tool ReadXplorer were vastly enhanced. Here, we present an even finer granulated read mapping classification, improving the level of detail for analyses and visualizations. The spectrum of automatic analysis functions has been broadened to include genome rearrangement detection as well as correlation analysis between two mapping data sets. Existing functions were refined and enhanced, namely the computation of differentially expressed genes, the read count and normalization analysis and the transcription start site detection. Additionally, ReadXplorer 2 features a highly improved support for large eukaryotic data sets and a command line version, enabling its integration into workflows. Finally, the new version is now able to display any kind of tabular results from other bioinformatics tools. AVAILABILITY AND IMPLEMENTATION: http://www.readxplorer.org CONTACT: readxplorer@computational.bio.uni-giessen.deSupplementary information: Supplementary data are available at Bioinformatics online.

Indexed as

Genomic Structural VariationSoftwareTranscription Initiation SiteArabidopsisComputational BiologyGene ExpressionGenomeRNA, PlantSequence Analysis, RNARNA, Plant

Identifiers

PMID27540267
PMCPMC5167064

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.