multiOutput: Analysis results for multiple pairs: visualization outputs

Description Usage Arguments Value Examples

View source: R/multiOutput.R

Description

Analysis results for multiple pairs: visualization outputs including overall pathway clustering and output for each pathway The multiOutput is function to generate visualization outputs for multiple pairs: including overall pathway clustering outputs, model MDS plot, model clustering output, heatmap of gene posterior mean, kegg pathway topology for each pathway

Usage

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multiOutput(mcmc.merge.list, dataset.names, select.pathway.list, ARS_pathway,
  output = c("clustPathway", "mdsModel", "clustModel", "genePM", "keggView"),
  hashtb = NULL, pathways = NULL, keggViewSelect = c(1, 2), optK = NULL,
  kegg_pathname = NULL, hs_gene_id = NULL)

Arguments

mcmc.merge.list:

a list of merged MCMC output matrices.

dataset.names:

a vector of dataset names.

select.pathway.list:

a list of selected pathways (containing gene components).

ARS_pathway:

a list of two data frames: pathway specific ARS values and their permuted p-value (pathway on rows, column being ARS value or the p-values).

output:

five options: "clustPathway" (pathway clustering),"mdsModel"(model MDS plot),"clustModel" (model clustering output), "genePM" (generating heatmap of gene posterior mean),"keggView" (generating kegg pathway topology, human KEGG only). For details, please refer to manuscript. cannot be empty.

hashtb:

hash table for text mining.

pathways:

complete pathway names for text mining.

keggViewSelect:

which two datasets to view in KEGG topology.

optK:

Optimal number of clusters based on clustering diagnostic results. For "clustPathway" output only.

kegg_pathname:

KEGG pathway name list. For "keggView" only.

hs_gene_id:

Human sapiens gene id. For "keggView" only.

Value

stored output in created folders.

Examples

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## Not run: 
#mcmc.merge.list from the merge step
#select.pathway.list from the pathSelect step
#ARS_pathway from the multiARS step
data(hashtb) #include hashtb & pathways
dataset.names <- c("hb","hs","ht","mb","ms","mt")
library(KEGG.db)
kegg_pathname <- unlist(as.list(KEGGPATHID2NAME))
library("org.Hs.eg.db")
hs_gene_id <- unlist(mget(x=rownames(mcmc.merge.list[[1]]),
envir=org.Hs.egALIAS2EG))
multiOutput(mcmc.merge.list,dataset.names,select.pathway.list,
ARS_pathway, output=c("clustPathway","mdsModel","clustModel","genePM","keggView"),
hashtb=hashtb,pathways=pathways,keggViewSelect = c(1,4),optK=7)

## End(Not run)

matianzhou/CAMO documentation built on May 21, 2019, 10:12 a.m.