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calc_group_median.Rd
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calc_group_median.Rd
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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/calculations.R
\name{calc_group_median}
\alias{calc_group_median}
\title{Calculate medians of groups of columns}
\usage{
calc_group_median(obj, data, groups, cols = NULL, other_cols = FALSE,
out_names = NULL, dataset = NULL)
}
\arguments{
\item{obj}{A \code{\link[taxa]{taxmap}} object}
\item{data}{The name of a table in \code{obj$data}.}
\item{groups}{Group multiple columns per treatment/group. This should be a
vector of group IDs (e.g. character, integer) the same length as
\code{cols} that defines which samples go in which group. When used, there
will be one column in the output for each unique value in \code{groups}.}
\item{cols}{The columns in \code{data} to use. By
default, all numeric columns are used. Takes one of the following inputs:
\describe{
\item{TRUE/FALSE:}{All/No columns will used.}
\item{Character vector:}{The names of columns to use} \item{Numeric vector:}{The indexes of
columns to use}
\item{Vector of TRUE/FALSE of length equal to the number of columns:}{Use the columns corresponding to \code{TRUE} values.} }}
\item{other_cols}{Preserve in the output non-target columns present in the
input data. New columns will always be on the end. The "taxon_id" column
will be preserved in the front. Takes one of the following inputs:
\describe{
\item{NULL:}{No columns will be added back, not even the taxon id column.}
\item{TRUE/FALSE:}{All/None of the non-target columns will be preserved.}
\item{Character vector:}{The names of columns to preserve}
\item{Numeric vector:}{The indexes of columns to preserve}
\item{Vector of TRUE/FALSE of length equal to the number of columns:}{Preserve the columns corresponding to \code{TRUE} values.}}}
\item{out_names}{The names of count columns in the output. Must be the same
length and order as \code{cols} (or \code{unique(groups)}, if \code{groups} is used).}
\item{dataset}{DEPRECIATED. use "data" instead.}
}
\value{
A tibble
}
\description{
For a given table in a \code{\link[taxa]{taxmap}} object, split columns by a
grouping factor and return row medians in a table.
}
\examples{
\dontrun{
# Parse data for examples
x = parse_tax_data(hmp_otus, class_cols = "lineage", class_sep = ";",
class_key = c(tax_rank = "taxon_rank", tax_name = "taxon_name"),
class_regex = "^(.+)__(.+)$")
# Calculate the medians for each group
calc_group_median(x, "tax_data", hmp_samples$sex)
# Use only some columns
calc_group_median(x, "tax_data", hmp_samples$sex[4:20],
cols = hmp_samples$sample_id[4:20])
# Including all other columns in ouput
calc_group_median(x, "tax_data", groups = hmp_samples$sex,
other_cols = TRUE)
# Inlcuding specific columns in output
calc_group_median(x, "tax_data", groups = hmp_samples$sex,
other_cols = 2)
calc_group_median(x, "tax_data", groups = hmp_samples$sex,
other_cols = "otu_id")
# Rename output columns
calc_group_median(x, "tax_data", groups = hmp_samples$sex,
out_names = c("Women", "Men"))
}
}
\seealso{
Other calculations: \code{\link{calc_group_mean}},
\code{\link{calc_group_rsd}},
\code{\link{calc_group_stat}},
\code{\link{calc_n_samples}},
\code{\link{calc_obs_props}},
\code{\link{calc_prop_samples}},
\code{\link{calc_taxon_abund}},
\code{\link{compare_groups}},
\code{\link{counts_to_presence}},
\code{\link{rarefy_obs}}, \code{\link{zero_low_counts}}
}
\concept{calculations}