contrast_each_group_to_the_rest: contrast_each_group_to_the_rest

In MonashBioinformaticsPlatform/celaref: Single-cell RNAseq cell cluster labelling by reference

Description

Produces a table of within-experiment differential expression results (for either query or reference experiment), where each group (cluster) is compared to the rest of the cells.

Usage

contrast_each_group_to_the_rest(dataset_se, dataset_name,
  groups2test = NA, num_cores = 1, n.group = Inf, n.other = n.group
  * 5, factors_to_rm = c())

Arguments

dataset_se	Summarised experiment object containing count data. Also requires 'ID' and 'group' to be set within the cell information (see colData())
dataset_name	Short, meaningful name for this dataset/experiment.
groups2test	An optional character vector specificing specific groups to check. By default (set to NA), all groups will be tested.
num_cores	Number of cores to use to run MAST jobs in parallel. Ignored if parallel package not available. Set to 1 to avoid parallelisation. Default = 1
n.group	How many cells to keep for each group in groupwise comparisons. Default = Inf
n.other	How many cells to keep from everything not in the group. Default = n.group * 5
factors_to_rm	If there are extra confounding factors that should be removed from MAST's zlm model (e.g individual, run), specify the column name(s) from colData in a vector here. Default=c().

Details

Note that this function is slow, because it runs the differential expression. It only needs to be run once per dataset though (unless group labels change). Having package parallel installed is highly recomended.

If this function runs out of memory, consider specifying n.group and n.other to run on a subset of cells (taken from each group, and proportionally from the rest for each test). Alternatively use subset_cells_by_group to subset dataset_se for each group independantly.

Both reference and query datasets should be processed with this function.

The tables produced by this function (usually named something like de_table.datasetname) contain summarised results of MAST results. Each group is compared versus cells in the group, versus not in the group, (Ie. always a 2-group contrast, other groups information is ignored). As per MAST reccomendataions, the proportion of genes seen in each cell is included in the model.

Value

A tibble the within-experiment de_table (differential expression table). This is a core summary of the individual experiment/dataset, which is used for the cross-dataset comparisons.

The table feilds won't neccesarily match across datasets, as they include cell annotations information. Important columns (used in downstream analysis) are:

ID

Gene identifier

ci_inner

Inner (conservative) 95% confidence interval of log2 fold-change.

fdr

Multiple hypothesis corrected p-value (using BH/FDR method)

group

Cells from this group were compared to everything else

sig_up

Significnatly differentially expressed (fdr < 0.01), with a positive fold change?

rank

Rank position (within group), ranked by CI inner, highest to lowest.

rescaled_rank

Rank scaled 0(top most overrepresented genes in group) - 1(top most not-present genes)

dataset

Name of dataset/experiment

Examples

de_table.demo_query  <- contrast_each_group_to_the_rest(
     demo_query_se, "a_demo_query")
     
de_table.demo_ref    <- contrast_each_group_to_the_rest(
     demo_ref_se, "a_demo_ref", num_cores=2)

MonashBioinformaticsPlatform/celaref documentation built on June 5, 2019, 11:35 a.m.