load_se_from_tables {celaref} | R Documentation

## load_se_from_tables

### Description

Create a SummarizedExperiment object (dataset_se) from a count matrix, cell information and optionally gene information.

`load_se_from_files` is a wrapper for `load_se_from_tables` that will read in tables from specified files.

### Usage

    load_se_from_tables(counts_matrix, cell_info_table, gene_info_table = NA,
      group_col_name = "group", cell_col_name = NA)

    load_se_from_files(counts_file, cell_info_file, gene_info_file = NA,
      group_col_name = "group", cell_col_name = NA)

### Arguments

`counts_matrix` | A tab-separated matrix of read counts for each gene (row) and each cell (column). Columns and rows should be named.
`cell_info_table` | Table of cell information. If there is a column labelled cell_sample, that will be used as the unique cell identifiers. If not, the first column is assumed to be cell identifiers, and will be copied to a new feild labelled cell_sample. Similarly - the clusters of these cells should be listed in one column - which can be called 'group' (case-sensitive) or specified with group_col_name. Minimal data format: <cell_sample> <group>
`gene_info_table` | Optional table of gene information. If there is a column labelled ID, that will be used as the gene identifiers (they must be unique!). If not, the first column is assumed to be a gene identifier, and will be copied to a new feild labelled ID. Must match all rownames in counts_matrix. If omitted, ID wll be generated from the rownames of counts_matrix. Default=NA
`group_col_name` | Name of the column in cell_info_table containing the cluster/group that each cell belongs to. Case-sensitive. Default='group'
`cell_col_name` | Name of the column in cell_info_table containing a cell id. Ignored if cell_sample column is already present. If omitted, (and no cell_sample column) will use first column. Case-sensitive. Default=NA
`counts_file` | A tab-separated file of a matrix of read counts. As per counts_matrix. First column should be gene ID, and top row cell ids.
`cell_info_file` | Tab-separated text file of cell information, as per cell_info_table. Columns must have names.
`gene_info_file` | Optional tab-separated text file of gene information, as per gene_info_file. Columns must have names. Default=NA

### Details

This function makes a SummarizedExperiment object in a form that should work for celaref functions. Specifically, that means it will have an 'ID' feild for genes (view with `rowData(dataset_se)`), and both 'cell_sample' and 'group' feild for cells (view with `colData(dataset_se)`). See parameters for detail. Additionally, the counts will be an integer matrix (not a sparse matrix), and the group feild (but not cell_sample or ID) will be a factor.

Note that data will be subsetted to cells present in both the counts matrix and cell info, this is handy for loading subsets of cells. However, if gene_info_file is defined, all genes must match exactly.

The `load_se_from_files` form of this function will run the same checks, but will read everything from files in one go. The `load_se_from_tables` form is perhaps more useful when the annotations need to be modified (e.g. programmatically adding a different gene identifier, renaming groups, removing unwanted samples).

Note that the SummarizedExperiment object can also be created without using these functions, it just needs the cell_sample, ID and group feilds as described above. Since sometimes it might be easier to add these to an existing SummarizedExperiment from upstream analyses.

### Value

A SummarisedExperiment object containing the count data, cell info and gene info.

### Functions

- `load_se_from_files`: To read from files

### See Also

SummarizedExperiment For general doco on the SummarizedExperiment objects.

Other Data loading functions: `contrast_each_group_to_the_rest_for_norm_ma_with_limma`, `load_dataset_10Xdata`

### Examples

    # From data frames (or a matrix for counts) :
    demo_se <- load_se_from_tables(counts_matrix=demo_counts_matrix,
                                   cell_info_table=demo_cell_info_table)
    demo_se <- load_se_from_tables(counts_matrix=demo_counts_matrix,
                                   cell_info_table=demo_cell_info_table,
                                   gene_info_table=demo_gene_info_table)

    # Or from data files :
    counts_filepath    <- system.file("extdata", "sim_query_counts.tab",    package = "celaref")
    cell_info_filepath <- system.file("extdata", "sim_query_cell_info.tab", package = "celaref")
    gene_info_filepath <- system.file("extdata", "sim_query_gene_info.tab", package = "celaref")

    demo_se <- load_se_from_files(counts_file=counts_filepath, cell_info_file=cell_info_filepath)
    demo_se <- load_se_from_files(counts_file=counts_filepath, cell_info_file=cell_info_filepath,
                                  gene_info_file=gene_info_filepath )

[Package celaref version 1.2.0 Index]