ArticleBMC proceedings2009
Methods for interpreting lists of affected genes obtained in a DNA microarray experiment.
Article in BMC proceedings, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
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Who cites it
21 citing papers in PubMed.
- Article
- Transcriptome profiling of HepG2 cells exposed to the flame retardant 9,10-dihydro-9-oxa-10-phosphaphenanthrene 10-oxide (DOPO).Toxicology research · 2018Article
- The pathway not taken: understanding 'omics data in the perinatal context.American journal of obstetrics and gynecology · 2015Article
- What's that gene (or protein)? Online resources for exploring functions of genes, transcripts, and proteins.Molecular biology of the cell · 2014Review
- The structure of a gene co-expression network reveals biological functions underlying eQTLs.PloS one · 2013Article
- Identification of genes underlying different methylation profiles in refractory anemia with excess blast and refractory cytopenia with multilineage dysplasia in myelodysplastic syndrome.The Korean journal of hematology · 2012Article
- Role of cytokines in systemic lupus erythematosus: recent progress from GWAS and sequencing.Journal of biomedicine & biotechnology · 2012Review
- Genome-wide analysis of a Wnt1-regulated transcriptional network implicates neurodegenerative pathways.Science signaling · 2011Article
- Comparative transcriptomes profiling of photoperiod-sensitive male sterile rice Nongken 58S during the male sterility transition between short-day and long-day.BMC genomics · 2011Article
- Molecular markers and mechanisms of stroke: RNA studies of blood in animals and humans.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2011Review
- Article
- Analysing biological pathways in genome-wide association studies.Nature reviews. Genetics · 2010Review
- STARNET 2: a web-based tool for accelerating discovery of gene regulatory networks using microarray co-expression data.BMC bioinformatics · 2009Article
- Microarray data mining using Bioconductor packages.BMC proceedings · 2009Article
- Gene set analysis methods applied to chicken microarray expression data.BMC proceedings · 2009Article
- Use of GenMAPP and MAPPFinder to analyse pathways involved in chickens infected with the protozoan parasite Eimeria.BMC proceedings · 2009Article
- Biological pathway analysis by ArrayUnlock and Ingenuity Pathway Analysis.BMC proceedings · 2009Article
- Using microarrays to identify positional candidate genes for QTL: the case study of ACTH response in pigs.BMC proceedings · 2009Article
- Comparison of three microarray probe annotation pipelines: differences in strategies and their effect on downstream analysis.BMC proceedings · 2009Article
- Pathway results from the chicken data set using GOTM, Pathway Studio and Ingenuity softwares.BMC proceedings · 2009Article
Corrections and comments
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Authors and funding
31 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe aim of this paper was to describe and compare the methods used and the results obtained by the participants in a joint EADGENE (European Animal Disease Genomic Network of Excellence) and SABRE (Cutting Edge Genomics for Sustainable Animal Breeding) workshop focusing on post analysis of microarray data. The participating groups were provided with identical lists of microarray probes, including test statistics for three different contrasts, and the normalised log-ratios for each array, to be used as the starting point for interpreting the affected probes. The data originated from a microarray experiment conducted to study the host reactions in broilers occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria.
resultsSeveral conceptually different analytical approaches, using both commercial and public available software, were applied by the participating groups. The following tools were used: Ingenuity Pathway Analysis, MAPPFinder, LIMMA, GOstats, GOEAST, GOTM, Globaltest, TopGO, ArrayUnlock, Pathway Studio, GIST and AnnotationDbi. The main focus of the approaches was to utilise the relation between probes/genes and their gene ontology and pathways to interpret the affected probes/genes. The lack of a well-annotated chicken genome did though limit the possibilities to fully explore the tools. The main results from these analyses showed that the biological interpretation is highly dependent on the statistical method used but that some common biological conclusions could be reached.
conclusionIt is highly recommended to test different analytical methods on the same data set and compare the results to obtain a reliable biological interpretation of the affected genes in a DNA microarray experiment.
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Registered trials
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