Computational protocol: Transcriptome analysis of psoriasis in a large case-control sample: RNA-seq provides insights into disease mechanisms

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Protocol publication

[…] All subjects involved in this study provided written informed consent under a protocol adherent to the Helsinki Guidelines and approved by the Institutional Review Board of the University of Michigan Medical School. Libraries for RNA-seq were generated from polyadenylated skin punch biopsy RNA and sequenced at one library per lane on the Illumina Genome Analyzer IIx. Reads were aligned to the reference genome NCBI build 37 using TopHat (). and expression was normalized to the number of reads per kilobase per million mapped reads (RPKM). We used the Wilcoxon rank-sum test to identify differentially expressed genes. Significant differentially expressed genes were detected based p < 10−6 (corresponding to Family-wise error rate (FWER) < 0.025) with a fold change greater than 2. Functional annotation was performed using Gene Ontology (), KEGG (), and Reactome (). Transcription factor analyses were performed using Ingenuity Pathway Analysis software ( Significance thresholds were determined by Bonferroni correction. Coordinate gene expression analysis was performed using the weighted gene co-expression network (WGCNA) package (), with normal and lesional psoriatic skin samples being analyzed separately. Gene expression signatures were identified as described (; ). Additional details are provided in the . […]

Pipeline specifications

Software tools TopHat, IPA, WGCNA
Databases Reactome KEGG
Application RNA-seq analysis
Diseases Psoriasis