Evidence map›Paper›PMID 26202974›Full record

ArticleNucleic acids research2015

Allelome.PRO, a pipeline to define allele-specific genomic features from high-throughput sequencing data.

Daniel Andergassen, Christoph P Dotter, Tomasz M Kulinski, Philipp M Guenzl, Philipp C Bammer, Denise P Barlow, Florian M Pauler, Quanah J Hudson

Abstract readValidation Study
In one paragraph

Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
–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

28 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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  8. Article
  9. Building Haplotype-Resolved 3D Genome Maps of Chicken Skeletal Muscle.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
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  18. Modern epigenetics methods in biological research.Methods (San Diego, Calif.) · 2021
    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

8 authors.

Daniel AndergassenCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria.
Christoph P DotterCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria.
Tomasz M KulinskiCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria.
Philipp M GuenzlCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria.
Philipp C BammerCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria.
Denise P BarlowCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria.
Florian M PaulerCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria FPauler@cemm.oeaw.ac.at.
Quanah J HudsonCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria QHudson@cemm.oeaw.ac.at.

Funding

Austrian Science Fund FWF P 25185
6 · The paper itself

Abstract

Detecting allelic biases from high-throughput sequencing data requires an approach that maximises sensitivity while minimizing false positives. Here, we present Allelome.PRO, an automated user-friendly bioinformatics pipeline, which uses high-throughput sequencing data from reciprocal crosses of two genetically distinct mouse strains to detect allele-specific expression and chromatin modifications. Allelome.PRO extends approaches used in previous studies that exclusively analyzed imprinted expression to give a complete picture of the 'allelome' by automatically categorising the allelic expression of all genes in a given cell type into imprinted, strain-biased, biallelic or non-informative. Allelome.PRO offers increased sensitivity to analyze lowly expressed transcripts, together with a robust false discovery rate empirically calculated from variation in the sequencing data. We used RNA-seq data from mouse embryonic fibroblasts from F1 reciprocal crosses to determine a biologically relevant allelic ratio cutoff, and define for the first time an entire allelome. Furthermore, we show that Allelome.PRO detects differential enrichment of H3K4me3 over promoters from ChIP-seq data validating the RNA-seq results. This approach can be easily extended to analyze histone marks of active enhancers, or transcription factor binding sites and therefore provides a powerful tool to identify candidate cis regulatory elements genome wide.

Indexed as

AllelesSoftwareAnimalsCells, CulturedChromatin ImmunoprecipitationGenomicsHigh-Throughput Nucleotide SequencingHistone CodeMiceMice, Inbred StrainsSequence Analysis, DNASequence Analysis, RNA

Identifiers

PMID26202974
PMCPMC4666383

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.