check_outlier: Check for outlier clusters

In AllenInstitute/scrattch.hicat: Hierarchical Iterative Clustering Analysis for Transcriptomic data

Check for outlier clusters

Description

This function checks for outliers looks for unexpected combinations of marker gene expression (e.g., GAD1 + SLC17A7) and for particularly high or low expression of indicated QC metrics, and flags any of the clusters meeting those criteria as potential outliers. This should (in theory) find things like poor quality clusters and clusters of doublets. Specific genes and thresholds currnetly hard-coded in, but might be updated in later iterations.

Usage

check_outlier(
  anno,
  cluster,
  norm.dat,
  select.cells = colnames(norm.dat),
  keep.cl = NULL,
  neun.thresh = 0.5,
  neun.colname = "facs_population_plan",
  neun.val = "NeuN-pos",
  qc.metrics = c("Genes.Detected.CPM", "percent_reads_aligned_total", "complexity_cg"),
  test.genes = c("SNAP25", "GAD1", "GAD2", "SLC17A7", "SLC17A6"),
  expr.th = 3,
  prop.th = c(0.4, 0.4, 0.4, 0.4, 0.4),
  min.prop.th = 0.8,
  plot = TRUE,
  plot.path = "output/"
)

Arguments

anno	anno dataframe which must include column names listed in 'neun.colname' and 'qc.metrics'. "cluster" is added from 'cluster' parameter below.
cluster	cluster labels for all cells along with sample_id as their names
norm.dat	expression dataframe with columns as cells and rows as gene names and cpm normalized
select.cells	column nmaes of norm.dat
keep.cl	clusters to definitely keep in analysis (e.g., to exclude from consideration as an outlier cluster) default is NULL
neun.thresh	fraction of cells expressing NeuN to be considered NeuN positive (default is 0.5)
neun.colname	column name in anno with the Nuen information
neun.val	value corresponding to non-neuronal marker in neun.colname in anno
qc.metrics	required columns from anno dataframe. default is Genes.Detected.CPM", "percent_reads_aligned_total", "complexity_cg"
test.genes	CURRENTLY NOT USED. This function will eventually allow for a pre-defined set of genes to be entered. default is "SNAP25", "GAD1", "GAD2", "SLC17A7", "SLC17A6"
expr.th	expression threshold for detecting test genes
prop.th	proportion threshold of detected genes by cluster (default is 0.4, 0.4, 0.4, 0.4, 0.4)
min.prop.th	one of last 4 test genes should have detection at least at this amount
plot	default is TRUE
plot.path	path of plot, default is ./output/

Value

gives outlier clusters and exploratory plots

AllenInstitute/scrattch.hicat documentation built on June 6, 2024, 5:31 a.m.