crop_counts: Subsetting Counts dataframes by Metadata
In dlemas/microbes: tools for analyzing microbiome data

Description Usage Arguments Details Value Note Author(s) References See Also Examples

This function subsets data frames into smaller dataframes including only participants who meet the critereon in the metadata.

1	crop_counts(df, meta, variables, values)

`df`	data frame with column names of the study_id's
`meta`	metadata dataframe
`variables`	The names of the columns in metadata that the dataframe is being subset based on. These variables should be listed together in one vector.
`values`	The desired values of the columns above. Listed together in one vector in the order that "variables" is listed.

It is important that "variables" and "values" are the same length and cooresponding entries are in the same order.

The output is a subsetted version of the original data frame containing only the participants that contain the specified values for the specified variables.

no further notes

atomczik

no references

no additional functions

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (df, meta, variables, values) 
{
    df.t = setNames(data.frame(t(df[, ])), row.names(df))
    df.t$study_id <- row.names(df.t)
    merged.data <- merge(meta, df.t, by = "study_id")
    row.names(merged.data) <- merged.data$study_id
    merged.data <- merged.data[, -1]
    for (i in 1:length(variables)) {
        variable.column <- which(names(merged.data) == variables[i])
        merged.data = subset(merged.data, (merged.data[, variable.column] == 
            values[i]))
    }
    cropped.counts <- merged.data
    m <- length(meta)
    n <- length(merged.data)
    p <- m + 1
    cropped.counts = cropped.counts[, m:n]
    cropped.counts = setNames(data.frame(t(cropped.counts[, ])), 
        row.names(cropped.counts))
    return(cropped.counts)
  }