spagi-package: SPAGI: Identification of active signalling pathways by...

Description Author(s) Examples

Description

SPAGI is an R package for active pathway identification for RNA-seq gene expression profiles. This package contains the neccessary R code to run SPAGI as described in "SPAGI: Identification of active signalling pathways using RNA-seq gene expression profiles". SPAGI is implemented within a helpful framework to identify active pathway paths from RNA-seq gene expression profiles.

Author(s)

Md Humayun Kabir <humayun.mkabir@gmail.com>

Examples

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## Do a sample analysis using human ocular lens epithelial cell (LEC) RNA-seq gene expression data.

## Here we will use "pathway.path" as background data from the SPAGI repository.
## Also we will use "ROR1.data" as query RNA-seq gene expression data. This data is for ocular lens epithelial cell differentiated from human pluripotent stem cells.
## These data sets are loaded automatically with the package.

## Pre-process the query data (ROR1.data), the data has already been made in CPM and log2 normalized format. Also we have already made the replicate names same for the data.
ROR1.processed.data<-preprocess_querydata(cell.tissue.data = ROR1.data, exp.cutoff.th = 1.8)
## Identify active pathway paths of the processed query data
ROR1.active.pathway<-identify_active_pathway_path(pathway.path = pathway.path, processed.query.data = ROR1.processed.data)
## Get active pathway ranking metric (i.e., activity score and number of downstream transcription factors)
ROR1.active.pathway.ranking.metric<-get_pathway_ranking_metric(active.pathway.path = ROR1.active.pathway, processed.query.data = ROR1.processed.data, high.exp.th = 7)
## Plot the ranking metric result (i.e., activity score and number of downstream transcription factors) in a 2D plane
display_pathway_ranking_metric(pathway.ranking.metric = ROR1.active.pathway.ranking.metric)
## To separate the top ranked pathways we can do this
abline(v=45, h=0.2, lty=2, col="black")

VCCRI/SPAGI documentation built on May 23, 2019, 1:08 p.m.