join_data: Step 3: Create a datatable of gene-mapped read counts

In csglab/PhantomPurgeR: PhantomPurgeR

Step 3: Create a datatable of gene-mapped read counts

Description

Step 3: Create a datatable of gene-mapped read counts

Usage

join_data(out, min_umi_cell = 1)

Arguments

out	A list of read counts data for all samples.
min_umi_cell	The minimum number of UMIs associated with a cell barcode. Barcodes with fewer UMIs are discarded. Default is 1 (i.e. all cell barcodes are retained). For large datasets with many samples set to a larger value (50-200) to reduce memory requirements.

Details

The read counts is created by joining data from all samples into a single datatable in which each row contains the mapped read counts across all the samples for each unique cell barcode-gene-umi combination that make up the three first columns. An outcome character variable (e.g. "(3,0,2,1)") to group the observations into unique outcomes is added as the last column.

Value

A list out containing sample_names and read_counts (a datatable of joined read counts table with an outcome variable column)

csglab/PhantomPurgeR documentation built on July 27, 2023, 8:05 a.m.