Evidence map›Paper›PMID 30922228›Full record

ArticleBMC genomics2019

ALFA: annotation landscape for aligned reads.

Mathieu Bahin, Benoit F Noël, Valentine Murigneux, Charles Bernard, Leila Bastianelli, Hervé Le Hir, Alice Lebreton, Auguste Genovesio

Abstract read
In one paragraph

Article in BMC genomics, 2019. 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
–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

7 citing papers in PubMed.

  1. Integrated mapping resolves pathogenicity of 11Journal of the Endocrine Society · 2026
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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.

Mathieu BahinComputational Biology and Bioinformatics group,, Institut de biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, PSL University, 75005, Paris, France.
Benoit F NoëlComputational Biology and Bioinformatics group,, Institut de biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, PSL University, 75005, Paris, France.
Valentine MurigneuxExpression of eukaryotic messenger RNAs group, Institut de biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, PSL University, 75005, Paris, France.
Charles BernardComputational Biology and Bioinformatics group,, Institut de biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, PSL University, 75005, Paris, France.
Leila BastianelliComputational Biology and Bioinformatics group,, Institut de biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, PSL University, 75005, Paris, France.
Hervé Le HirExpression of eukaryotic messenger RNAs group, Institut de biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, PSL University, 75005, Paris, France.
Alice LebretonBacterial Infection & RNA Destiny group, Institut de biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, PSL University, 75005, Paris, France. alice.lebreton@ens.fr.
Auguste GenovesioComputational Biology and Bioinformatics group,, Institut de biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, PSL University, 75005, Paris, France. auguste.genovesio@ens.fr.ORCID http://orcid.org/0000-0003-1877-5595

Funding

Agence Nationale de la Recherche ANR-10-LABX-54 MEMO LIFEAgence Nationale de la Recherche (FR) ANR-11-IDEX-0001-02 PSL Reserach UniversityFondation pour la Recherche Médicale FRM-AJE20131128944Institut National de la Santé et de la Recherche Médicale (FR) ATIP Avenir
6 · The paper itself

Abstract

backgroundThe last 10 years have seen the rise of countless functional genomics studies based on Next-Generation Sequencing (NGS). In the vast majority of cases, whatever the species, whatever the experiment, the two first steps of data analysis consist of a quality control of the raw reads followed by a mapping of those reads to a reference genome/transcriptome. Subsequent steps then depend on the type of study that is being made. While some tools have been proposed for investigating data quality after the mapping step, there is no commonly adopted framework that would be easy to use and broadly applicable to any NGS data type.

resultsWe present ALFA, a simple but universal tool that can be used after the mapping step on any kind of NGS experiment data for any organism with available genomic annotations. In a single command line, ALFA can compute and display distribution of reads by categories (exon, intron, UTR, etc.) and biotypes (protein coding, miRNA, etc.) for a given aligned dataset with nucleotide precision. We present applications of ALFA to Ribo-Seq and RNA-Seq on Homo sapiens, CLIP-Seq on Mus musculus, RNA-Seq on Saccharomyces cerevisiae, Bisulfite sequencing on Arabidopsis thaliana and ChIP-Seq on Caenorhabditis elegans.

conclusionsWe show that ALFA provides a powerful and broadly applicable approach for post mapping quality control and to produce a global overview using common or dedicated annotations. It is made available to the community as an easy to install command line tool and from the Galaxy Tool Shed.

Indexed as

AnimalsArabidopsisCaenorhabditis elegansComputational BiologyGene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansMiceMolecular Sequence AnnotationSaccharomyces cerevisiaeSequence Analysis, RNASoftwareNGSPost mappingQuality controlToolUniversal

Identifiers

PMID30922228
PMCPMC6440077

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.