FindMajorIsoforms: FindMajorIsoforms
In smorabit/scWGCNA: hdWGCNA

FindMajorIsoforms

R Documentation

FindMajorIsoforms

Description

Finds the set of "major isoforms" for each gene in each cell population. The set of major isoforms consists of the isoforms accounting for a desired proportion of a gene's expression. Pseudobulk replicates in each sample and cell population are used for this calculation.

Usage

FindMajorIsoforms(
  seurat_obj,
  group.by,
  replicate_col,
  isoform_delim = "[.]",
  proportion_thresh = 0.8,
  low_thresh = 25,
  assay = "iso",
  slot = "counts",
  cluster_markers = NULL,
  wgcna_name = NULL
)

Arguments

`seurat_obj`	A Seurat object
`group.by`	column in seurat_obj@meta.data containing grouping info, ie clusters or celltypes
`replicate_col`	column in seurat_obj@meta.data denoting each replicate / sample
`isoform_delim`
`proportion_thresh`	desired proportion of expression to define the set of major isoforms. Default = 0.8.
`low_thresh`	lower bound of expression level for considering an isoform as part of the major isoform set.
`assay`	Assay in seurat_obj containing isoform expression information.
`slot`	Slot in seurat_obj, default to counts slot.
`cluster_markers`	Cell population marker gene table from Seurat FindAllMarkers for the same cell populations specified in group.by. Optional parameter, will exclude isoforms that are not from marker genes.
`wgcna_name`	The name of the hdWGCNA experiment in the seurat_obj@misc slot

Details

FindMajorIsoforms computes the set of major isoforms in a given Seurat object that contains isoform-level expression information. First, pseudobulk replicates are computed for the given cell populations and samples present in the Seurat object. For each gene in each cell population, we rank the gene's isoforms by expression level and take the top expressing isoforms that make up the desired proportion of the gene's total expression, making sure to exclude any very lowly expressed isoforms.

Optionally, the user may supply a marker gene table for each cell population (formatted like the output of Seurat FindAllMarkers), and then the algorithm will only return major isoforms of the given marker genes.