Subset Genes in Genomic Data

The 'subsetGenes' function selects and retains genes from 'mockObj' that match the genes specified in 'l_genes'.

Usage

subsetGenes(l_genes, mockObj)

Arguments

l_genes

A character vector specifying the genes to be retained in the dataset.

mockObj

An object containing relevant genomic information to be filtered.

Value

A modified version of the 'mockObj' data object, with genes filtered according to 'l_genes'.

Details

This function filters and adjusts genomic data within the Roxygeb project, based on a specified list of genes.

Examples

N_GENES = 100
MAX_REPLICATES = 5
MIN_REPLICATES = 5
input_var_list <- init_variable(name = "varA", sd = 0.1, level = 3)
#> Variable name should not contain digits, spaces, or special characters.
#> If any of these are present, they will be removed from the variable name.
mock_data <- mock_rnaseq(input_var_list, N_GENES,
                        min_replicates = MIN_REPLICATES, 
                        max_replicates = MAX_REPLICATES)
#> Building mu_ij matrix
#> INFO: 8 genes have all(mu_ij) < 1, indicating very low counts. Consider removing them for future analysis using prepareData2fit with row_threshold = 10. To detect them in future experiment, try increasing sequencing depth.
#> k_ij ~ Nbinom(mu_ij, dispersion)
#> Counts simulation: Done
subset_mockobj <- subsetGenes(mock_data, l_genes = c("gene1", "gene4"))