add_qc_metrics.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/add_qc_metrics.R
\name{add_qc_metrics}
\alias{add_qc_metrics}
\title{Quality Control for Spatial Data}
\usage{
add_qc_metrics(spe, overwrite = FALSE)
}
\arguments{
\item{spe}{a \link[SpatialExperiment:SpatialExperiment]{SpatialExperiment}
object that has \code{sum_umi}, \code{sum_gene}, \code{expr_chrM_ratio}, and \code{in_tissue}
variables in the \code{colData(spe)}. Note that these are automatically created
when you build your \code{spe} object with \code{spatialLIBD::read10xVisiumWrapper()}.}

\item{overwrite}{a \code{logical(1)} specifying whether to overwrite the 7
\code{colData(spe)} columns that this function creates. If set to \code{FALSE} and any
of them are present, the function will return an error.}
}
\value{
A \link[SpatialExperiment:SpatialExperiment]{SpatialExperiment}
with added quality control information added to the \code{colData()}.
\describe{
\item{\code{scran_low_lib_size}}{shows spots that have a low library size.}
\item{\code{scran_low_n_features}}{spots with a low number of expressed genes.}
\item{\code{scran_high_Mito_percent}}{spots with a high percent of mitochondrial gene expression.}
\item{\code{scran_discard}}{spots belonging to either \code{scran_low_lib_size},
\code{scran_low_n_feature}, or \code{scran_high_Mito_percent}.}
\item{\code{edge_spot}}{spots that are automatically detected as the edge spots
of the \code{in_tissue} section.}
\item{\code{edge_distance}}{closest distance in number of spots to either the
vertical or horizontal edge.}
\item{\code{scran_low_lib_size_edge}}{spots that have a low library size and
are an edge spot.}
}
}
\description{
This function identify spots in a
\link[SpatialExperiment:SpatialExperiment]{SpatialExperiment-class} (SPE)
with outlier quality control values: low \code{sum_umi} or \code{sum_gene}, or high
\code{expr_chrM_ratio}, utilizing \link[scuttle:isOutlier]{scuttle::isOutlier}. Also identifies in-tissue
edge spots and distance to the edge for each spot.
}
\details{
The initial version of this function lives at
\url{https://github.com/LieberInstitute/Visium_SPG_AD/blob/master/code/07_spot_qc/01_qc_metrics_and_segmentation.R}.
}
\examples{
## Obtain the necessary data
spe_pre_qc <- fetch_data("spatialDLPFC_Visium_example_subset")

## For now, we fake out tissue spots in example data
spe_qc <- spe_pre_qc
spe_qc$in_tissue[spe_qc$array_col < 10] <- FALSE

## adds QC metrics to colData of the spe
spe_qc <- add_qc_metrics(spe_qc, overwrite = TRUE)
vars <- colnames(colData(spe_qc))
vars[grep("^(scran|edge)", vars)]

## visualize edge spots
vis_clus(spe_qc, sampleid = "Br6432_ant", clustervar = "edge_spot")

## specify your own colors
vis_clus(
    spe_qc,
    sampleid = "Br6432_ant",
    clustervar = "edge_spot",
    colors = c(
        "TRUE" = "lightgreen",
        "FALSE" = "pink",
        "NA" = "red"
    )
)
vis_gene(spe_qc, sampleid = "Br6432_ant", geneid = "edge_distance", minCount = -1)

## Visualize scran QC flags

## Check the spots with low library size as detected by scran::isOutlier()
vis_clus(spe_qc, sample_id = "Br6432_ant", clustervar = "scran_low_lib_size")

## Violin plot of library size with low library size highlighted in a
## different color.
scater::plotColData(spe_qc[, spe_qc$in_tissue], x = "sample_id", y = "sum_umi", colour_by = "scran_low_lib_size")

## Check any spots that scran::isOutlier() flagged
vis_clus(spe_qc, sampleid = "Br6432_ant", clustervar = "scran_discard")

## Low library spots that are on the edge of the tissue
vis_clus(spe_qc, sampleid = "Br6432_ant", clustervar = "scran_low_lib_size_edge")

## Use `low_library_size` (or other variables) and `edge_distance` as you
## please.
spe_qc$our_low_lib_edge <- spe_qc$scran_low_lib_size & spe_qc$edge_distance < 5

vis_clus(spe_qc, sample_id = "Br6432_ant", clustervar = "our_low_lib_edge")

## Clean up
rm(spe_qc, spe_pre_qc, vars)

}
\author{
Louise A. Huuki-Myers
}