suppressPackageStartupMessages({
    library(signatureSearch); 
    library(readr); library(dplyr); library(DT)
})

Short Introduction

This vignette shows the code and results for Gene Expression Signature Searches (GESS) with the downstream Functional Enrichment Analysis (FEA) of the query. Rank transformed GESS results grouped by cell type and the level of expression for each gene used in the query signature are illustrated for each result.
The introduction of GESS and FEA as well as their corresponding methods is available at this vignette of the signatureSearch package. Here, <gess_method> is used as GESS method, The <N_gess_drugs> top ranking unique hits in the GESS table were then used for FEA where three different annotation systems were used: GO Molecular Function (GO MF), GO Biological Process (GO BP) and KEGG pathways.

GESS/FEA workflow

wf_list <- runWF(drug="<drug>", refdb="<refdb>", 
                 gess_method="<gess_method>", fea_method="<fea_method>", 
                 N_gess_drugs=<N_gess_drugs>)

GESS/FEA results

GESS

gess_tb <- suppressMessages(as.data.frame(fread("results/<gess_method>_res.xls")))
datatable(gess_tb[1:10, 1:15], colnames=c('No'=1), escape = FALSE, options=list(scrollX=TRUE, autoWidth=TRUE))

Full table

GESS result ranks by cell type

Cell_tb <- suppressMessages(as.data.frame(fread("results/ResultRankByCell.xls")))
datatable(Cell_tb[1:10,], colnames=c('No'=1), escape = FALSE, options=list(scrollX=TRUE, autoWidth=TRUE)) 

Full table

GES expression level by query

Expres_tb <- suppressMessages(as.data.frame(fread("results/GESExpressionLevel.xls")))
datatable(Expres_tb[1:10,], colnames=c('No'=1), escape = FALSE, options=list(scrollX=TRUE, autoWidth=TRUE)) 

Full table



girke-lab/signatureSearch documentation built on Feb. 21, 2024, 8:32 a.m.