Evidence map›Paper›PMID 25495450›Full record

ArticleBMC bioinformatics2014

MPAgenomics: an R package for multi-patient analysis of genomic markers.

Quentin Grimonprez, Alain Celisse, Samuel Blanck, Meyling Cheok, Martin Figeac, Guillemette Marot

Abstract read
In one paragraph

Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Quentin GrimonprezMODAL team, Inria Lille-Nord Europe, Villeneuve-d'Ascq, France. quentin.grimonprez@inria.fr.
Alain Celisse
Samuel Blanck
Meyling Cheok
Martin Figeac
Guillemette Marot

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLast generations of Single Nucleotide Polymorphism (SNP) arrays allow to study copy-number variations in addition to genotyping measures.

resultsMPAgenomics, standing for multi-patient analysis (MPA) of genomic markers, is an R-package devoted to: (i) efficient segmentation and (ii) selection of genomic markers from multi-patient copy number and SNP data profiles. It provides wrappers from commonly used packages to streamline their repeated (sometimes difficult) manipulation, offering an easy-to-use pipeline for beginners in R.The segmentation of successive multiple profiles (finding losses and gains) is performed with an automatic choice of parameters involved in the wrapped packages. Considering multiple profiles in the same time, MPAgenomics wraps efficient penalized regression methods to select relevant markers associated with a given outcome.

conclusionsMPAgenomics provides an easy tool to analyze data from SNP arrays in R. The R-package MPAgenomics is available on CRAN.

Indexed as

DNA Copy Number VariationsPolymorphism, Single NucleotideSoftwareGenetic MarkersHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNAGenetic Markers

Identifiers

PMID25495450
PMCPMC4269855

What OpenQuestion holds

Textmetadata
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.