Computational protocol: Systems-Based Analyses of Brain Regions Functionally Impacted in Parkinson's Disease Reveals Underlying Causal Mechanisms

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Protocol publication

[…] Microarray expression data has been deposited to NCBI Gene Expression Omnibus , accession number, GSE54282. Microarray expression data for each brain region were normalized with the RMA algorithm included in R using a custom CDF file from the brain array database , . If samples from different platforms were available, they were first normalized separately and then merged into one dataset using Entrez gene ids as common identifier. Batch effect removal was performed using the ComBat algorithm to remove technical variation between results of the two platforms . Quality assessment of merged data was performed to ensure that no separation by platform was observed after batch effect removal. Differential gene expression was identified using an empirical Bayes moderated t-test available in the Bioconductor limma package . Genes were defined as differentially expressed if their absolute fold change was above 1.2.Proteomics expression data were pre-processed as described above under mass spectrometry, and differentially expressed proteins were defined using an absolute fold change cut-off of 1.2 and p-value threshold of 0.05. RNA-sequencing data were pre-processed by Expression Analysis ( and read count estimates were calculated using the RSEM algorithm . Differentially expressed genes were identified using the DEGseq R-package using a fold change threshold of 1.2 for consistency with microarray parameters . Gene and protein lists provided were mapped to Entrez gene identifiers using the DAVID bioinformatics resource . […]

Pipeline specifications

Software tools ComBat, limma, RSEM, DEGseq, DAVID
Databases Gene
Application RNA-seq analysis
Diseases Parkinson Disease