factor_sample_filter: Factor-based Sample Filtering: Function to filter single-cell...
In scone: Single Cell Overview of Normalized Expression data

Description Usage Arguments Details Value Examples

This function returns a sample-filtering report for each cell in the input expression matrix, describing whether it passed filtering by factor-based filtering, using PCA of quality metrics.

factor_sample_filter(expr, qual, gene_filter = NULL, max_exp_pcs = 5,
  qual_select_q_thresh = 0.01, force_metrics = NULL,
  good_metrics = NULL, min_qual_variance = 0.7, zcut = 1,
  mixture = TRUE, dip_thresh = 0.01, plot = FALSE,
  hist_breaks = 20)

`expr`	matrix The data matrix (genes in rows, cells in columns).
`qual`	matrix Quality metric data matrix (cells in rows, metrics in columns).
`gene_filter`	Logical vector indexing genes that will be used for PCA. If NULL, all genes are used.
`max_exp_pcs`	numeric number of expression PCs used in quality metric selection. Default 5.
`qual_select_q_thresh`	numeric. q-value threshold for quality/expression correlation significance tests. Default 0.01
`force_metrics`	logical. If not NULL, indexes quality metric to be forcefully included in quality PCA.
`good_metrics`	logical. If not NULL, indexes quality metric that indicate better quality when of higher value.
`min_qual_variance`	numeric. Minimum proportion of selected quality variance addressed in filtering. Default 0.70
`zcut`	A numeric value determining threshold Z-score for sd, mad, and mixture sub-criteria. Default 1.
`mixture`	A logical value determining whether mixture modeling sub-criterion will be applied per primary criterion (quality score). If true, a dip test will be applied to each quality score. If a metric is multimodal, it is fit to a two-component normal mixture model. Samples deviating zcut sd's from optimal mean (in the inferior direction), have failed this sub-criterion.
`dip_thresh`	A numeric value determining dip test p-value threshold. Default 0.05.
`plot`	logical. Should a plot be produced?
`hist_breaks`	hist() breaks argument. Ignored if 'plot=FALSE'.

None

A logical, representing samples passing factor-based filter.

mat <- matrix(rpois(1000, lambda = 5), ncol=10)
colnames(mat) <- paste("X", 1:ncol(mat), sep="")
qc = as.matrix(cbind(colSums(mat),colSums(mat > 0)))
rownames(qc) = colnames(mat)
colnames(qc) = c("NCOUNTS","NGENES")
mfilt = factor_sample_filter(expr = mat,
    qc, plot = TRUE,qual_select_q_thresh = 1)