Evidence map›Paper›PMID 24753414›Full record

ArticleNucleic acids research2014

VAP: a versatile aggregate profiler for efficient genome-wide data representation and discovery.

Charles Coulombe, Christian Poitras, Alexei Nordell-Markovits, Mylène Brunelle, Marc-André Lavoie, François Robert, Pierre-Étienne Jacques

Abstract read
In one paragraph

Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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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

7 authors.

Charles CoulombeDépartement d'informatique, Faculté des sciences, Université de Sherbrooke, Sherbrooke, Québec, J1K 2R1, Canada.
Christian PoitrasInstitut de recherches cliniques de Montréal, Montréal, Québec, H2W 1R7, Canada.
Alexei Nordell-MarkovitsDépartement d'informatique, Faculté des sciences, Université de Sherbrooke, Sherbrooke, Québec, J1K 2R1, Canada Département de biologie, Faculté des sciences, Université de Sherbrooke, Sherbrooke, Québec, J1K 2R1, Canada.
Mylène BrunelleDépartement de biologie, Faculté des sciences, Université de Sherbrooke, Sherbrooke, Québec, J1K 2R1, Canada.
Marc-André LavoieDépartement de biologie, Faculté des sciences, Université de Sherbrooke, Sherbrooke, Québec, J1K 2R1, Canada.
François RobertInstitut de recherches cliniques de Montréal, Montréal, Québec, H2W 1R7, Canada Département de médecine, Faculté de médecine, Université de Montréal, Montréal, Québec, H3T 1J4, Canada Pierre-Etienne.Jacques@USherbrooke.ca.
Pierre-Étienne JacquesDépartement d'informatique, Faculté des sciences, Université de Sherbrooke, Sherbrooke, Québec, J1K 2R1, Canada Département de biologie, Faculté des sciences, Université de Sherbrooke, Sherbrooke, Québec, J1K 2R1, Canada Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Sherbrooke, Québec, J1H 5N4, Canada Pierre-Etienne.Jacques@USherbrooke.ca.

Funding

Canadian Institutes of Health Research MOP-82891
6 · The paper itself

Abstract

The analysis of genomic data such as ChIP-Seq usually involves representing the signal intensity level over genes or other genetic features. This is often illustrated as a curve (representing the aggregate profile of a group of genes) or as a heatmap (representing individual genes). However, no specific resource dedicated to easily generating such profiles is currently available. We therefore built the versatile aggregate profiler (VAP), designed to be used by experimental and computational biologists to generate profiles of genomic datasets over groups of regions of interest, using either an absolute or a relative method. Graphical representation of the results is automatically generated, and subgrouping can be performed easily, based on the orientation of the flanking annotations. The outputs include statistical measures to facilitate comparisons between groups or datasets. We show that, through its intuitive design and flexibility, VAP can help avoid misinterpretations of genomics data. VAP is highly efficient and designed to run on laptop computers by using a memory footprint control, but can also be easily compiled and run on servers. VAP is accessible at http://lab-jacques.recherche.usherbrooke.ca/vap/.

Indexed as

SoftwareGenomicsInternet

Identifiers

PMID24753414
PMCPMC4086060

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.