perform.scran: Performs Scran normalisation, hvg selection, scaling and...

In connorhknight/IBRAP_no_decontX: Integrated Benchmarking scRNA-seq Analytical Pipeline

Description

A new method-assay is produced. Raw counts are normalised and HVGs identified using Scran

Usage

perform.scran(
  object,
  assay = "RAW",
  slot = "counts",
  batch = NULL,
  vars.to.regress = NULL,
  do.scale = TRUE,
  do.center = TRUE,
  new.assay.suffix = "",
  n.genes = 1500,
  max.cluster.size = 1000,
  center_size_factors = TRUE
)

Arguments

object	IBRAP S4 class object
assay	Character. String containing indicating which assay to use
slot	Character. String indicating which slot within the assay should be sourced
batch	Character. Which column in the metadata defines the batches. Default = NULL
vars.to.regress	Character. Which column in the metadata should be regressed. Default = NULL
do.scale	Boolean. Whether to scale the features variance. Default = TRUE
do.center	Boolean. Whether to centre features to zero. Default = TRUE
new.assay.suffix	Character. What should be added as a suffix for SCRAN
n.genes	Numerical. Top number of genes to retain when finding HVGs. Default = 1500
max.cluster.size	Numerical. When performing quickCluster, what is the maximum size the clusters can be. Default = 1000
center_size_factors	Boolean Should size factor variance be centred. Default = TRUE

Value

Produces a new 'methods' assay containing normalised, scaled and HVGs.

Examples

object <- perform.scran(object = object, 
                        assay = 'RAW', 
                        slot = 'counts', 
                        vars.to.regress = 'RAW_total.counts', do.scale = T)

connorhknight/IBRAP_no_decontX documentation built on Feb. 13, 2022, 2:32 p.m.