examine_dataset: Generate several plots and objects for dataset exploration

Description Usage Arguments Value

View source: R/workflows.R

Description

This function examines several facets of the dataset, inclusing filtering cells based on metadata, dimension reduction, cluster analysis, and visualization

Usage

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examine_dataset(cell_data_dataframe = data.frame(),
  normalized_expression_matrix = matrix(), .species = "mmusculus",
  color_var = character())

Arguments

cell_dataframe:

cell_dataframe consists of sample names of each cell to be examined, as well as all other data that might be used for visualizing the resulting cells. This data.frame must have a character column named 'sample_name', which must match the row names of normalized_expression_matrix

normalized_expression_matrix:

this must be a CxG matrix, with C cells and G genes, The C cells are the rownamews of the matrix and must match the sample_name column from cell_dataframe. The column names must be ENSEMBL IDs. The entries of the matrix must be the normalized since they will be used in tsne

.species:

currently either 'mmusculus' or 'hsapiens'

color_var:

variable name to color cells by in overview ggplot images. This must correspond to a column name in cell_data_dataframe.

Value

This function returns a list with the following elements:


robAndrewCarter/rnaseqUtils documentation built on July 29, 2017, 6:51 p.m.