Computational protocol: Transcriptomic responses of the liver and adipose tissues to altered carbohydrate-fat ratio in diet: an isoenergetic study in young rats

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Protocol publication

[…] The CEL files derived from the liver, WAT, and BAT were quantified using robust multi-array average (RMA), factor analysis for robust microarray summarization (quantile normalization, qFARMS), and GCRMA, respectively [, , ], using the statistical language R (2.7.1) (http://www.r-project.org/) (R []), and Bioconductor (2.2) (http://www.bioconductor.org/) []. Hierarchical clustering was performed using the pvclust function in R []. The rank products (RP) method was used to identify differentially expressed gene probe sets of the quantified data []. The probe sets with a false discovery rate (FDR) <0.05 were considered to be differentially expressed between each group (L vs M, M vs H, and L vs H).The up- and downregulated probe sets picked out at FDR < 0.05 were functionally classified by the Biological Process in Gene Ontology (GO) with the Functional Annotation Tool of the Database for Annotation, Visualization, and Integrated Discovery (DAVID) [, ] and Quick GO (http://www.ebi.ac.uk/QuickGO/) []. In analysis of the liver, EASE scores, which are modified Fisher’s exact test p values were used to extract statistically overrepresented GO terms, and GO terms with p values <0.01 were regarded as significantly enriched. In analysis of WAT and BAT, Benjamini-Hochberg correction p values were used to extract statistically overrepresented GO terms, and GO terms with p values <0.05 were regarded as significantly enriched.Predicted upstream regulators among liver and adipose tissue transcriptomes were analyzed using Qiagen’s Ingenuity Pathway Analysis (IPA, Qiagen, https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis/). Activation z-scores were calculated as a measure of upstream regulators analysis. An absolute z-score ≥2.5 was judged as significantly activated or inhibited. Common upstream regulators that were predicted to be activated or inhibited in the liver, WAT, and BAT were picked out from a list of all upstream regulators. […]

Pipeline specifications

Software tools FARMS, GC–RMA, Pvclust, DAVID, QuickGO, IPA
Application Gene expression microarray analysis
Organisms Rattus norvegicus
Chemicals Amino Acids, Cholesterol, Fatty Acids, Glycerol, Hydrogen, Triglycerides