MSprep-package: This module implements parsing and data frame construction...

In interzoneboy/MS-prep: MSprep does basic parsing of sieve data

Description

This module implements basic parsing of sieve MS and MS/MS data, into a logically constructed R data frame, suitable for further processing. Also a case study of how to explicitly pipeline analysis and data processing, using functions, decorators, and magrittr n'est pas une pipelines.

Author(s)

Maintainer: matt s [e-mail]

Examples

EXAMPLE of how to use this package
example <- function(){

library(ggplot2)
library(reshape2)
library(magrittr)

writeOut <- function(dd, n){
    write.csv(dd, file=n, quote=F, row.names=F)
    return(dd)
}


fname <- "example_sieve_data_file.csv"

example_prepare_data <- function(fname){

    fname %>% 
    #
    # Read in the data file, and immediately write out a copy as v1.csv
    p(read_data_file)() %>% 
    p(writeOut)("v1.csv") %>%

    # Remove columns that contain "blank", "pool", or "pr", and write out a
    # copy of this intermediate data as v2.csv
    p(remove_cols)(c(function(x){grep("blank",names(x),ignore.case=T)}
                     , function(x){grep("pool",names(x),ignore.case=T)}
                     , function(x){grep("pr",names(x),ignore.case=T)})) %>% 
    p(writeOut)("v2.csv") %>%

    # Transpose this smaller frame, treating the 1st three columns as row-information. This row information
    # is processed into the names(...) of the transposed data frame, and the original names(...) become the
    # "sample_id" column.
    p(transpose)(1:3, "sample_id") %>% 
    p(writeOut)("v3.csv")


}


}

interzoneboy/MS-prep documentation built on June 13, 2020, 7:03 a.m.