load_data: Analyzes and processes the repertoire sequencing data from...

In rodamian/Bindpred: package for antibody specificity and affinity prediction

Description

Analyzes and processes the repertoire sequencing data from cellranger vdj. This provides information on the single-cell level for each clone.

Usage

load_data(
  VDJ.directory,
  clonotype.level = FALSE,
  filter.prod = TRUE,
  filter.confidence = TRUE,
  filter.is.cell = TRUE,
  red.method = "pca",
  n.dims = 1:10
)

Arguments

VDJ.directory	Character vector with each element containing the path to the output of cellranger vdj runs. To integrate the repertoire with transcriptome data GEX data can by provided inside the corresponding folder. The name of the GEX folder must contain "gex" in his name (case insensitive). This pipeline assumes that the output file names have not been changed from the default 10x settings in the /outs/ folder.
red.method	Method of dimensionality reduction used. Options are "pca", "tsne", "umap".
n.dims	Number of dimension to be used in the chosen reduction. Default is 20.
filtered.prod	Logical indicating if the contigs file should be filtered by productive cells. Default set to TRUE
filtered.confidence	Logical indicating if the contigs file should be filtered by contigs with high_confidence. Default set to TRUE
filtered.is.cell	Logical indicating if the contigs file should be filtered by sequences that only come from cells. Default set to TRUE

Value

Returns a list of dataframes containing information on the cell or clonotype level.

Examples

## Not run: 
check_load_data <- load_data(VDJ.directory = "path/to/cellranger/outs/", clonotype.level = FALSE)

## End(Not run)

rodamian/Bindpred documentation built on July 29, 2021, 7:29 p.m.