KOGMWU (version 1.2)

kog.mwu: Tests for KOG class enrichment.

Description

Determines whether some KOG classes are significantly enriched with up- or down-regulated genes (Mann-Whitney U test for continuous measure), or whether some KOG classes are significantly over-represented among "significant" genes (one-tailed Fisher's exact test for binary measure, 0 or 1).

Usage

kog.mwu(data, gene2kog, Alternative = "t")

Arguments

data

Two-column dataframe: gene id, measure of significance.

gene2kog

Two-column dataframe of gene annotations: gene id, KOG class. The gene list can be longer or shorter than the first column in the 'data' item.

Alternative

Tailedness of the Mann-Whitney U test: two-tailed ("t"), greater ("g"), or less ("l")

Value

For continuous measure, a dataframe with three columns: term : KOG class nseqs : Number of genes in this class delta.rank : Difference between the mean rank of genes belonging to this KOG class and all other genes pval : p-value of the Mann-Whitney U test padj : p-value adjusted using Benjamini-Hochberg 1995 "fdr" procedure

For binary measure, the output is similar but does not contain the delta.rank column.

Details

The measure can be continuous (such as log fold change), in which case Mann-Whitney U test will be performed, or binary (1 or 0: significant or not), in which case Fisher's exact test will be performed. The KOG class annotations for a collection of genes can be obtained using Weizhng Li's lab KOG BLAST server.

References

Dixon GB, Davies SW, Aglyamova GA, Meyer E, Bay LK and Matz MV (2015) Genomic determinants of coral heat tolerance across latitudes. Weizhong Li's KOG BLAST server: http://weizhong-lab.ucsd.edu/metagenomic-analysis/server/kog/

Examples

# NOT RUN {
data(adults.3dHeat.logFoldChange)
data(larvae.longTerm)
data(larvae.shortTerm)
data(gene2kog)

# Analyzing adult coral response to 3-day heat stress:
alfc.lth=kog.mwu(adults.3dHeat.logFoldChange,gene2kog) 
alfc.lth 

# coral larvae response to 5-day heat stress:
l.lth=kog.mwu(larvae.longTerm,gene2kog)
l.lth

# coral larvae response to 4-hour heat stress 
l.sth=kog.mwu(larvae.shortTerm,gene2kog)
l.sth

# compiling a table of delta-ranks to compare these results:
ktable=makeDeltaRanksTable(list("adults.long"=alfc.lth,"larvae.long"=l.lth,"larvae.short"=l.sth))

# Making a heatmap with hierarchical clustering trees: 
pheatmap(as.matrix(ktable),clustering_distance_cols="correlation") 

# exploring correlations between datasets
pairs(ktable, lower.panel = panel.smooth, upper.panel = panel.cor)
# p-values of these correlations in the upper panel:
pairs(ktable, lower.panel = panel.smooth, upper.panel = panel.cor.pval)

# plotting individual delta-rank correlations:
corrPlot(x="adults.long",y="larvae.long",ktable)
corrPlot(x="larvae.short",y="larvae.long",ktable)
# }