corOrt: Calculate ortholog gene correlation coefficients
In disco: Discordance and Concordance of Transcriptomic Responses

Description Usage Arguments Details Value Bibliography See Also Examples

Calculate correlation between sets of matched orthologous genes using either method from Takao et al. (2015) or Seok et al. (2013)

1	corOrt(x, g = NULL, pval = 0.05, lfc = 0)

`x`	an object of class matchedOrtholog
`g`	either a vector of gene names of genes of interest, or an object of class "tmod" with definitions of modules. If NULL, all genes will be used
`pval`	p value threshold
`lfc`	log_2 fold change threshold

This function calculates Pearson Correlation, squared Pearson correlation and Spearman correlation for mouse and human logFC values for genes with significant p-values for differential regulation. As in PNAS 2013 110 (9) 3507-3512, for the calculation of squared Pearson correlation coefficient all the genes that are significantly regulated in at least one specie are taken into account, while for the calculation of Spearman's correlation coefficient only the genes significantly regulated in both species as in PNAS 2015 112 (4) 1167-1172.

The parameters can be calculated either for all genes in the orthologs object, for an explicit list of genes as a character vector parameter g, or for a set of tmod modules, if the parameter g is an object of class tmod.

corOrt returns a data frame with the following columns:

r: Pearson correlation coefficient r
Seok: correlation measure described by Seok et al. – squared Pearson r correlation coefficient for genes significantly up- or downregulated in one of the two orthologous sets
Seok.N: number of gene pairs that were used to calculate the Seok coefficient
rho: Spearman correlation coefficient rho
Takao: correlation measure described by Takao et al. – Spearman correlation coefficient for genes significantly up- or downregulated in both of the two gene orthologous sets
Takao.N: number of gene pairs that were used to calculate the Takao coefficient; smaller or equal to Seok.N
N: total number of gene pairs in the given gene set

Seok, Junhee, et al. "Genomic responses in mouse models poorly mimic human inflammatory diseases." Proceedings of the National Academy of Sciences 110.9 (2013): 3507-3512.

Takao, Keizo, and Tsuyoshi Miyakawa. "Genomic responses in mouse models greatly mimic human inflammatory diseases." Proceedings of the National Academy of Sciences 112.4 (2015): 1167-1172.

modCor

library(tmod)
data(tmod)
data(orthologs)
a <- corOrt(orthologs)
disco <- disco.score(orthologs)
ord <- order(disco, decreasing = TRUE)
concordant <- tmodCERNOtest(toupper(orthologs$genes)[ord])
corOrt(orthologs, g=tmod[concordant$ID])