View source: R/get_sensitivity.R
get_sensitivity | R Documentation |
A helper function to allow user calculate specifity pvalue for a subset of its dataset. To calculate specifity pvalue for all data points set specificity = TRUE in im_syng_TCGA.
get_sensitivity( df_syng, method = "max", ndatamin = 8, N_iteration_sensitivity = 1000, sample_list )
df_syng |
a dataframe with 10 columns as outputed by im_syng_tcga. |
method |
A character string indicating which synergy score to be used. one of "max" or "independence". Default is "max". |
ndatamin |
minimum number of samples. Synergy score calculation will be skipped for matrices with number of rows less than ndatamin |
N_iteration_sensitivity |
Number of iterations for random sampling for sensitivity analysis. Default is 1000. |
sample_list |
An optional character vector of TCGA samples barcodes indicating a subset of samples within a cohort. |
A specificity p.value is computed using random sampling with replacement from two null models, generated from one of the two genes against a set of genes randomly selected from the genome. Two P-values are calculated for the synergistic interaction of the pair against the two null models. The highest of the two P-values is used to assess the specificity of the interaction against the whole genome. The number of randomly selected genes in each null model is determined by N_iteration_specificity.
All barcodes in sample_list must be 15 character long and belong to the same cohort. When sample_list is provided, cohort should be the disease cohort that they belong to, otherwise only the first element of the cohort list will be used.
Specificty pvalues for each row of dataframe
df <- im_syng_tcga(onco_gene=c("TGFB1","SERPINB9"), cohort=c("ucec"),specificity = F) df <- get_sensitivity(df)
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