PECA statistics

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Citations per year

Number of citations per year for the bioinformatics software tool PECA
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Tool usage distribution map

This map represents all the scientific publications referring to PECA per scientific context
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Popular tool citations

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Protocols

PECA specifications

Information


Unique identifier OMICS_20068
Name PECA
Alternative name Probe-level Expression Change Averaging
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 2.0
Computer skills Advanced
Version 1.16.0
Stability Stable
Requirements
limma, affy, R(>=3.3), preprocessCore, aroma.affymetrix, genefilter, ROTS, aroma.core, SpikeIn
Maintained Yes

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Documentation


Maintainers


  • person_outline Tomi Suomi
  • person_outline Tomi Suomi
  • person_outline Laura Elo

Publication for Probe-level Expression Change Averaging

PECA citations

 (4)
library_books

Enhanced differential expression statistics for data independent acquisition proteomics

2017
Sci Rep
PMCID: 5517573
PMID: 28724900
DOI: 10.1038/s41598-017-05949-y

[…] antly higher pAUC of 0.916 than t-test (pAUC = 0.836), MSstats (pAUC = 0.844) or mapDIA (pAUC = 0.895), with bootstrap test p < 0.01 in all comparisons (Fig. ). Although in terms of true positives, ROPECA performed slightly more conservatively than the other tested methods, at a typical FDR threshold of 0.05, the number of true positives reported by all the methods were roughly the same (Fig. ). I […]

library_books

Analysis of Time Resolved Gene Expression Measurements across Individuals

2013
PLoS One
PMCID: 3857324
PMID: 24349258
DOI: 10.1371/journal.pone.0082340

[…] ession data from each replicate. The quantile-normalized probe-level data was transformed into probe set-level signal log-ratios between each non-Thp sample and the corresponding Thp sample using the probe-level expression change averaging procedure , as described in GEO (GSE18017).From the original preprocessed datasets, only those probe sets were retained that mapped to a unique Entrez ID. If mu […]

library_books

Quantitative Proteomics Analysis of the Nuclear Fraction of Human CD4+ Cells in the Early Phases of IL 4 induced Th2 Differentiation*

2010
PMCID: 2938108
PMID: 20467038
DOI: 10.1074/mcp.M900483-MCP200

[…] we used the so-called random effect meta-analysis model to estimate representative expression ratios for each protein from the three biological replicates. The approach is conceptually similar to the probe-level expression change averaging procedure that we have successfully applied to combine data across gene expression microarray experiments (). For microarray applications, the method takes into […]

call_split

Probe level estimation improves the detection of differential splicing in Affymetrix exon array studies

2009
Genome Biol
PMCID: 2728531
PMID: 19607685
DOI: 10.1186/gb-2009-10-7-r77
call_split See protocol

[…] is simplifies the model to:(3) (Equation 3)which allows the probeset-level expression change μ(uv)g = μug - μvg to be estimated directly using, for instance, the median over the probes. This type of probe-level expression change averaging approach PECA has been shown to improve the detection of differential expression in gene expression microarray studies []. Moreover, in case of replicated sampl […]


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PECA institution(s)
Turku Centre for Biotechnology, Turku, Finland

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