geneCor: geneCor: Identification of correlation between two pairs of...
In huynguyen250896/geneCor: geneCor: Identification of correlation between two pairs of three datasets, visualization of Z-score distributions of those two pairs on a page, and examination of the significance of the skewness of those distributions.

Description Usage Arguments Author(s) References Examples

View source: R/geneCor.R

It automatically computes correlation coefficients of individual genes that share between the first data dat1 and its corresponding third data cordat1, and those that share between the second data dat2 and its corresponding third data cordat2 ; visualizes the Z-score distributions of between the first and second data versus their corresponding third data on a page; and examines the significance of the skewness for those distributions using D Agostino test. For further information on requirements as well as how to implement this tool, please visit my Github repository: https://github.com/huynguyen250896/geneCor.

1	geneCor(dat1, cordat1, alternative1, dat2, cordat2, alternative2, methodCC, adjustedP)

`dat1`	data.frame or matrix. The first input data includes its rows are samples and its columns are genes.
`cordat1`	data.frame or matrix. The data includes its rows are samples and its columns are clinical features. This itself is the corresponding third data of `dat1`. Namely, correlation analysis will be implemented between `dat1` and `cordat1`
`alternative1`	a character string specifying the alternative hypothesis for Z-score distribution between `dat1` and `cordat1`. Must be one of "two.sided", "greater" or "less". You can specify just the initial letter.
`dat2`	data.frame or matrix. The second input data includes its rows are samples and its columns are genes.
`cordat2`	data.frame or matrix. The data includes its rows are samples and its columns are clinical features. This itself is the corresponding third data of `dat2`. Namely, correlation analysis will be implemented between `dat2` and `cordat2`
`alternative2`	a character string specifying the alternative hypothesis for Z-score distribution between `dat2` and `cordat2`. Must be one of "two.sided", "greater" or "less". You can specify just the initial letter.
`methodCC`	Correlation method. Allowed values are `spearman`, `pearson` (default), `kendall`.
`adjustedP`	logical. Whether we should adjust the P-values gained from correlation analyses using the Benjamini-Hochberg procedure. Default is `adjustedP = T`

Quang-Huy Nguyen

Quang-Huy Nguyen, Duc-Hau Le. (2020). Multi-omics analysis detects novel prognostic subgroups of breast cancer. Frontiers in Genetics, 11(1265).

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geneCor(dat1 = cna, cordat1 = exp1, alternative1="less", dat2 = met, cordat2 = exp2, alternative2="greater", method = "spearman") 
#dat1 uses copy number alterations data, and cordat1 uses its corresponding gene expression data.
#dat2 uses methylation data, and cordat2 uses its corresponding gene expression data.