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iGA specifications

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Unique identifier OMICS_18766
Name iGA
Alternative name Iterative Group Analysis
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages Perl
Computer skills Advanced
Stability Stable
Maintained No

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Publication for Iterative Group Analysis

iGA in publications

 (4)
PMCID: 5790912
PMID: 29382730
DOI: 10.1128/mBio.02118-17

[…] deviation of five biological replicates. download fig s7, pdf file, 0.2 mb., cell extract proteomics data and analysis. download table s1, xlsx file, 1 mb., enrichment analysis was performed by the iterative group analysis (iga) method () after the annotation of detected proteins with gene ontology (go) terms (amigo 2) (). upregulated proteins in the gi-eu comparison displayed enrichment […]

PMCID: 3751782
PMID: 23962043
DOI: 10.1186/1752-0509-7-80

[…] figure a)., next, we identified differentially expressed biological process go terms (degos) in each tissue by first ranking all genes in descending order of limma significance and then performing iterative group analysis (iga) [] for each go term with ≤ 100 constituent genes. we computed p-values for each term’s iga score using a null distribution obtained via 1000 random permutations […]

PMCID: 2761411
PMID: 19775443
DOI: 10.1186/1471-2105-10-307

[…] function; go: gene ontology; gevd: generalized extreme value distribution function; gsa: gene set analysis; gsea: gene set enrichment analysis; ibmt: intensity based modified t-test; iga: iterative group analysis; ks: kolmogorov-smirnov test; lr: likelihood ratio; ml: maximum likelihood; modks: modified kolmogorov-smirnov; ogl: ordered gene list; rma: robust multi-array average; sp: […]

PMCID: 2673224
PMID: 19265549
DOI: 10.1186/1471-2407-9-77

[…] were compared to the untreated ones. the rank product method [] was used to identify genes consistently up- or down-regulated. gene ontology (go) analysis was applied for functional studies using iterative group analysis (iga) [] utilizing the source database http://source.stanford.edu[]. false discovery rates for go-terms were estimated by performing 100 permutations., in the ex vivo […]


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iGA institution(s)
Plant Science Group, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow, UK; Bioinformatics Research Centre, Department of Computing Science, University of Glasgow, Glasgow, UK; Sir Henry Wellcome Functional Genomics Facility, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow, UK
iGA funding source(s)
Supported by BBSRC grants 17/GG17989 and 17/P17237.

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