get_ka_by_mean_or_mlr: Computing kinase activity using mean value and multiple...

In ecnuzdd/PhosMap: A Comprehensive R Package For Analyzing Quantitative Phosphoproteomics Data

Computing kinase activity using mean value and multiple linear regression (ridge regression) except KSEA

Description

Computing kinase activity using mean value and multiple linear regression (ridge regression) except KSEA

Usage

get_ka_by_mean_or_mlr(
  ptypes_data,
  species = "human",
  log2_label = FALSE,
  method = "mean"
)

Arguments

ptypes_data	A data frame of phosphorylation data after normalization.
species	A string representing the species of imported data, the options are human, mouse and rat.
log2_label	A boolean value representing whether data is logarithmetics, the default is FALSE.
method	A string for the method to compute kinase activity, the options are 'mean' and 'mlr' (multiple linear regression), the default is mean.

Value

A data frame that consists of kinase, psite, substrate, counting byond ratio_cutoff and corresponding original value.

Author(s)

Dongdong Zhan and Mengsha Tong

Examples

## Not run: 
ftp_url <- "ftp://111.198.139.72:4000/pub/PhosMap_datasets/function_demo_data/get_ka_by_mean_or_mlr.RData"
load_data <- load_data_with_ftp(ftp_url, 'RData')
writeBin(load_data, "get_ka_by_mean_or_mlr.RData")
load("get_ka_by_mean_or_mlr.RData")

kinase_activity_df <- get_ka_by_mean_or_mlr(
  cluster_df,
  species = 'human',
  log2_label = TRUE,
  method = 'mean'
)
head(kinase_activity_df)

## End(Not run)

ecnuzdd/PhosMap documentation built on Dec. 7, 2022, 4:09 a.m.