gimme_PSI_expr_corr | R Documentation |
This function calculates the correlation between an alternative splicing event Percentage of Sequence Inclusion (PSI) with the expression levels (i.e. counts) of all genes present in the vast-tools expression table, after some basic filtering. The type of correlation can be either Spearman, Pearson, or Kendall. If using this type of correlation extra parameters can be passed to the cor()
R function used to calculate the correlations. The mapping of ENSEMBL gene IDs to gene names is available only if selecting best correlating genes. This is done in order to avoid to query ENSEMBL bioMart servers with a massive gene list.
gimme_PSI_expr_corr(
inclusion_tbl,
vst_id,
quality_thrshld = "N",
vst_expression_tbl,
min_mean_count = 5,
corr_method = c("spearman", "pearson", "kendall"),
num_genes = NULL,
map_ID_2_names = FALSE,
species,
verbose = FALSE,
...
)
inclusion_tbl |
path to vast-tools inclusion table that contains a vst_id event. |
vst_id |
vast-tools alternative splicing event to grep in the |
quality_thrshld |
vast-tools event quantification quality score threshold. Must be one of "N", "VLOW", "LOW", "OK", "SOK". For more info read the official documentation here under "Column 8, score 1". |
vst_expression_tbl |
Path to a vast-tools expression table (either cRPKM or TPM). |
min_mean_count |
Filter out low expressed genes in the table read from |
corr_method |
Either |
num_genes |
Return only the top and bottom number of genes. Integer number greater or equal than 1. Default is |
map_ID_2_names |
Logical. Whether or not to map the ENSEMBL gene IDs to gene names. Can be used only if |
species |
Species character to use to map the ENSEMBL gene ID. Used by |
verbose |
Print out information |
... |
Extra parameters passed to |
A tibble
# Return one PSI to all gene correlation
gimme_PSI_expr_corr(inclusion_tbl = psi_path, vst_id = "HsaEX0000001",
vst_expression_tbl = expr_path, corr_method = "spearman",
use = "complete.obs", verbose = TRUE ) -> corr_df
# Return one PSI to all genes correlation filtered for the top and bottom correlating genes and map the IDs to names.
gimme_PSI_expr_corr(inclusion_tbl = psi_path, vst_id = "HsaEX0000001",
quality_thrshld = "VLOW",
vst_expression_tbl = expr_path, min_mean_count = 100,
corr_method = "spearman", use = "complete.obs"
num_genes = 10, map_ID_2_names = T, species = "hsapiens",
verbose = TRUE ) -> best_corr_df
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