base_FastPearson: Get correlation index from expression matrix

In shijianasdf/BasicBioinformaticsAnalysisFromZhongShan: Launch Usual Clinical tool for Kind Yield

Description

FastPearson help get cor from expression matrix.

Usage

FastPearson(data,
            transposition = F,
            control.markers=NULL,
            target.markers=NULL,
            method = "pearson",
            order = F,
            parallel = F)

Arguments

data	a expression matrix
transposition	Whether transpose the matrix.IF you input a gene expression matrix with rownames gene,you should set transposition = T
control.markers	If NULL,use all pairs strategy,else use one pair strategy.Only one control marker is supported
target.markers	when control.marker is not a NULL value,it specified the target variates you want.Default is NULL,which means you wan correlation between control.markers to other variates
method	One of "pearson","kendall" and "spearman".Default is "pearson"
order	whether order the cormatrix with corrplot::corrMatOrder
parallel	whether use parallel strategy

Value

a list of long data frame and a cormatrix

Author(s)

Weibin Huang<[e-mail]>

Examples

library(lucky)
data=state.x77;colnames(data)

## All pairs
l1 <- FastPearson(data = state.x77,
            transposition = F,
            control.markers=NULL,
            target.markers=NULL,
            method = "pearson",
            order = F,
            parallel = F)
View(l1$longdata)
View(l1$cormatrix)

## One pair with no specified target
l2 <- FastPearson(data = state.x77,
                  transposition = F,
                  control.markers="Income",
                  target.markers=NULL,
                  method = "pearson",
                  order = F,
                  parallel = F)
View(l2$longdata)

## One pair with specified target
l3 <- FastPearson(data = state.x77,
                  transposition = F,
                  control.markers="Income",
                  target.markers=c("Illiteracy","Life Exp"),
                  method = "pearson",
                  order = F,
                  parallel = F)
View(l3$longdata)

shijianasdf/BasicBioinformaticsAnalysisFromZhongShan documentation built on Jan. 3, 2020, 10:08 p.m.