Description Usage Arguments Value See Also Examples
View source: R/functions_cleane.R
Separates metabolites into groups based on pooled plasma missing rates so that different thresholds of metrics can be applied to each group.
1 | subset_met(df, miss, numsplit = 5, mincut = 0.02, maxcut = 0.95)
|
df |
The metabolomics dataset, ideally read from the |
miss |
Vector of missing rates of equal length to number of rows in |
numsplit |
The number of equal sized sections to divide metabolites into based on missing rate of pooled plasma columns. Divides the range of missing rates between |
mincut |
A cutoff to specify that any metabolite with pooled plasma missing rate less than or equal to this value should be retained. Default is |
maxcut |
A cutoff to specify that any metabolite with pooled plasma missing rate greater than this values should be removed. Default is |
A list consisting of a number of elements equal to numsplit
. Each element contains a matrix of the given metabolite group based on the pooled plasma missing rate. The list keys are simple integers corresponding to the split number.
See MetProc-package
for examples of running the full process.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | library(MetProc)
#Read in metabolomics data
metdata <- read.met(system.file("extdata/sampledata.csv", package="MetProc"),
headrow=3, metidcol=1, fvalue=8, sep=",", ppkey="PPP", ippkey="BPP")
#Get indices of pooled plasma and samples
groups <- get_group(metdata,"PPP","X")
#Calculate a pooled plasma missing rate and sample missing rate
#for each metabolite in data
missrate <- get_missing(metdata,groups[['pp']],groups[['sid']])
#Group metabolites into 5 groups based on pooled plasma
#missing rate
subsets <- subset_met(metdata,missrate[['ppmiss']],5,.02,.95)
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