Step 2 of mcRigor two-step: Re-partition single cells that previously formed dubious metacells into smaller metacells.

Usage

mcRigorTS_Step2(
  step1_res,
  obj_singlecell,
  cell_membership_twostep,
  twostep_gamma = NULL,
  method = c("seacells", "mc1", "mc2", "supercell", "metaq"),
  custom_thre = F,
  color_field = NULL
)

Arguments

step1_res: A list of results obtained form Step 1 of mcRigor two-step, given by function mcRigorTS_Step1.
obj_singlecell: A Seurat object of the original single cells.
cell_membership_twostep: A dataframe, each column of which contains the metacell membership of single cells that need to be re-partitioned under a given gamma (granularity level). The column names should be the corresponding gamma's (in the character type). The row names should be the single cell id's.
twostep_gamma: The granularity level value for the second step. Default is NULL.
method: The metacell partitioning method used to build metacells. Available: "seacells" (default, SEACells), "mc1" (MetaCell), "mc2" (MetaCell2), "supercell" (SuperCell), "metaq" (MetaQ).
custom_thre: A boolean indicating whether to re-compute the threshold values.
color_field: The variable based on which to color the cells.

Value

A list containing the following fields:

obj_sc_dub: A Seurat object of single cells that are marked as dubious and will be re-partitioned.
target_res: A list containing the permutation results, derived thresholds, and mcRigor results in dubious metacell detection, given by function mcRigor_threshold.
obj_metacell_step1: The metacell object built under the membership sc_membership, with more dubious metacells marked.