Description Usage Arguments Details Value Author(s) Examples
View source: R/stats_functions.R
Compare the likelihood ratio test statistic to its ecdf under the null for two mutated genes/pathways in clones of patients.
1 2  ecdf_lr_test_clon_excl_avg_rate(entA, entB, clone_tbl, avg_rates_m, ecdf_list,
alternative)

entA 
One gene/pathway of the pair. 
entB 
The other gene/pathway of the pair. 
clone_tbl 
The clone tibble as generated with

avg_rates_m 
The average rates of clonal exclusivity for each patient. The name of each rate is the respective patient_id. 
ecdf_list 
The list of ECDF's of the test statistic under the
null distribution. Can be generated with

alternative 
The character indicating whether pairs should only be tested if delta > 0 or if all pairs should be tested. Can be one of "greater" or "two.sided". 
Tests whether the observed number of clonal exclusivities of mutated entities (genes or pathways) A and B in clones of patients is significantly different from what would be expected given the average clonal exclusivity rates. The observed test statistic is compared to the ecdf of the test statistic under the null hypothesis.
Returns list(p_val, num_patients, mle_delta, test_statistic), i.e. a list with the pvalue, the number of patients in which both of the genes/pathways were mutated, the maximum likelihood estimate of the delta, and the test statistic.
Ariane L. Moore
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32  clone_tbl < dplyr::tibble("file_name"=
rep(c(rep(c("fn1", "fn2"), each=3)), 2),
"patient_id"=rep(c(rep(c("pat1", "pat2"), each=3)), 2),
"altered_entity"=c(rep(c("geneA", "geneB", "geneC"), 4)),
"clone1"=c(0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0),
"clone2"=c(1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1),
"tree_id"=c(rep(5, 6), rep(10, 6)))
clone_tbl_pat1 < dplyr::filter(clone_tbl, patient_id == "pat1")
clone_tbl_pat2 < dplyr::filter(clone_tbl, patient_id == "pat2")
rates_exmpl_1 < compute_rates_clon_excl(clone_tbl_pat1)
rates_exmpl_2 < compute_rates_clon_excl(clone_tbl_pat2)
avg_rates_m < apply(cbind(rates_exmpl_1, rates_exmpl_2), 2, mean)
names(avg_rates_m) < c(names(rates_exmpl_1)[1],
names(rates_exmpl_2)[1])
values_clon_excl_num_trees_pat1 < get_hist_clon_excl(clone_tbl_pat1)
values_clon_excl_num_trees_pat2 < get_hist_clon_excl(clone_tbl_pat2)
list_of_num_trees_all_pats <
list(pat1=values_clon_excl_num_trees_pat1[[1]],
pat2=values_clon_excl_num_trees_pat2[[1]])
list_of_clon_excl_all_pats <
list(pat1=values_clon_excl_num_trees_pat1[[2]],
pat2=values_clon_excl_num_trees_pat2[[2]])
num_pat_pair_max < 2
num_pairs_sim < 10
ecdf_list < generate_ecdf_test_stat(avg_rates_m,
list_of_num_trees_all_pats,
list_of_clon_excl_all_pats,
num_pat_pair_max,
num_pairs_sim)
ecdf_lr_test_clon_excl_avg_rate("geneA", "geneB", clone_tbl,
avg_rates_m,
ecdf_list, "greater")

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