rescueCells: rescueCells

In chris-mcginnis-ucsf/MULTI-seq: deMULTIplex is a software suite for MULTI-seq sample barcode FASTQ pre-processing and cell barcode classification.

rescueCells

Description

'rescueCells' has four steps:
(1) Normalize MULTI-seq sample barcode UMI count matrix containing negative cells and equal numbers of cells from each sample group, as defined during the initial MULTI-seq sample classification workflow.
(2) Perform k-means clustering on the parsed, normalized sample barcode data
(3) Compute the rate at which k-means and 'ground-truth' sample classifications match
(4) Compute the rate at which k-means and potential reclassifications match for negative cells binned by classification stability values.

Usage

 rescueCells <- function(barTable, classifications, reclassifications) 

Arguments

barTable	MULTI-seq sample barcode UMI count matrix, as generated by MULTIseq.align. Note: Do not include summary columns. Include all cellIDs, regardless of initial sample classification workflow results.
classifications	Initial (i.e. pre-rescued) results from the MULTI-seq sample classification worklfow. Includes singlets, doublets, and negative cells.
reclassifications	Dataframe of potential reclassifications and classification stability values, as generated by 'findReclassCells'.

Value

Dataframe containing the 'ground-truth' and classification-stability-binned k-means matching rates (mean and standard deviation). Used as input for visualization to determine classification stability threshold at which negative and 'ground-truth' cells deviate.

Author(s)

Chris McGinnis

Examples

  ## Perform semi-supervised reclassification
  ind <- which(final.calls=="Negative")
  reclass.cells <- findReclassCells(barTable, names(final.calls)[ind])
  reclass.res <- rescueCells(barTable, final.calls, reclass.cells)

  ## Visualize k-means match rate x classification stability
  ggplot(reclass.res[-1, ], aes(x=ClassStability, y=MatchRate_mean)) +
    geom_point() +
    xlim(c(nrow(reclass.res)-1,1)) +
    ylim(c(0,1.05)) +
    geom_errorbar(aes(ymin=MatchRate_mean-MatchRate_sd, ymax=MatchRate_mean+MatchRate_sd), width =.1) +
    geom_hline(yintercept = reclass.res$MatchRate_mean[1], color="red") +
    geom_hline(yintercept = reclass.res$MatchRate_mean[1]+3*reclass.res$MatchRate_sd[1], color="red",lty=2) +
    geom_hline(yintercept = reclass.res$MatchRate_mean[1]-3*reclass.res$MatchRate_sd[1], color="red",lty=2)

  ## Finalize sample classification results
  final.calls.rescued <- final.calls
  to.rescue <- rownames(reclass.cells)[which(reclass.cells$ClassStability >= 16)]
  final.calls.rescued[to.rescue] <- reclass.cells[to.rescue,"Reclassification"]

chris-mcginnis-ucsf/MULTI-seq documentation built on Nov. 22, 2023, 8:24 p.m.