Computational protocol: Long-Term Effects of Ionizing Radiation on Gene Expression in a Zebrafish Model

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Protocol publication

[…] The quality of the data for all chips was evaluated using probe-level models, using the affyPLM package in the R statistical computing environment , . These data were then normalized using quantile normalization, and probe set expression values were calculated using the Robust Multiarray Average method , . Any probe sets having an interquartile range less than 0.2 were filtered out for all subsequent analyses. The Linear Models for Microarray Data (LIMMA) package was used to determine which probe sets differed among the five treatment groups using comparisons enumerated in the Results section. Only probe sets that had a significant result for the overall F-test were considered significant for any of the comparisons to protect against increasing errors due to increasing multiple comparisons. A 5% false discovery rate (FDR) was used to determine significance for any given test.Pathway-based analyses were conducted using multivariate analysis of variance using the sets of genes belonging to the same Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Classical multidimensional scaling was used to represent the variation in all genes within the gene set using only two dimensions and Euclidean distances. Permutations were used to test significance, and a 5% FDR was used to adjust for multiple testing. This is an extension of Hoteling’s T2 approach , . […]

Pipeline specifications

Software tools affyPLM, limma
Application Gene expression microarray analysis
Organisms Danio rerio