Authors: Mengyuan Kan, Maya Shumyatcher, Blanca Himes
We integrated asthma-related publicly available datasets to investigate global and cell-specific gene expression signatures.
25 asthma-related datasets (23 microarray and 2 RNA-Seq datasets) were downloaded from the Gene Expression Omnibus (GEO) or the Sequence Read Archive (SRA). A total of 17 asthma vs. non-asthma and 13 glucocorticoid vs. control comparisons from the transcriptomic studies were selected for integration analyses and analyzed by RAVED (https://github.com/HimesGroup/raved). We integrated the differential expression results from individual studies using three summary statistics-based methods (i.e effect size-, p-value-, and rank-based methods). We integrated studies across all tissue and cell types to identify genes that globally differentially expressed across asthma or glucocorticoid exposure conditions. We also performed separate analyses for blood and structural cells to identify cell-specific expression patterns.
integration_results folder contains integration results for significant genes in asthma and glucocorticoid response. For each phenotype and cell/tissue group of interest, genes with q-value <0.05 obtained by at least two integration methods were considered significant. The files share the same format.
| Field | Description |
|---|---|
| Gene | gene symbol |
| N | number of studies |
| es_method.pval | p-value from effect size-based method |
| es_method.qval | q-value from effect size-based method |
| es_method.eff.size | combined effect size from effect size-based method |
| es_method.std.err | standard error from effect size-based method |
| p_method.pval-p | value from p-value-based method |
| p_method.qval | q-value from p-value-based method |
| rank_method.pval | p-value from rank-based method |
| rank_method.qval | q-value from rank-based method |
asthma_integration.R: R codes for integration analysis. Example data used are in the data folder. Note that for the rank-based method, 10000 permutations are used for demonstration.
data folder contains example data for running R script asthma_integration.R. datainfo.RDS contains information of datasets used. example.RDS contains differential expression analysis results in a list format. Two genes are used here for demonstration.
DE_results folder contains the RMD files for microarray datasets used for our integration analysis of transcriptomic data asthma and glucocorticoid response