## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set(collapse = TRUE) library("dplyr") library("kableExtra") library("knitr") library("midasHLA") ## ----load_pheno, echo=TRUE, warning=FALSE------------------------------------- pheno_file <- system.file("extdata", "MiDAS_tut_pheno.txt", package = "midasHLA") pheno <- read.table(pheno_file, header = TRUE, stringsAsFactors = FALSE) ## ----show_pheno, echo=FALSE, warning=FALSE------------------------------------ pheno %>% head(10) %>% kable() %>% kable_styling(bootstrap_options = c("striped", "hover", "condensed")) ## ----load_hla, echo=TRUE, warning=FALSE--------------------------------------- # HLA calls can be loaded using the readHlaCalls function with the desired resolution hla_calls_file <- system.file("extdata", "MiDAS_tut_HLA.txt", package = "midasHLA") hla_calls <- readHlaCalls(hla_calls_file, resolution = 4) ## ----show_hla, echo=FALSE, warning=FALSE-------------------------------------- hla_calls %>% head(10) %>% kable() %>% kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>% scroll_box(width = "100%", height = "200px") ## ----load_kir, echo=TRUE, warning=FALSE--------------------------------------- # KIR calls (currently presence/absence calls, no allele-level resolution) can be loaded using the readKirCalls function kir_calls_file <- system.file("extdata", "MiDAS_tut_KIR.txt", package = "midasHLA") kir_calls <- readKirCalls(kir_calls_file) ## ----show_kir, echo=FALSE, warning=FALSE-------------------------------------- kir_calls %>% head(10) %>% kable() %>% kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>% scroll_box(width = "100%", height = "200px") ## ----test_data, echo=TRUE, warning=FALSE-------------------------------------- HLA <- reduceHlaCalls(MiDAS_tut_HLA, resolution = 4) KIR <- MiDAS_tut_KIR pheno <- MiDAS_tut_pheno ## ----creating_midas_data_set, echo=TRUE, warning=FALSE------------------------ midas <- prepareMiDAS( hla_calls = HLA, kir_calls = KIR, colData = pheno, experiment = c("hla_alleles", "hla_aa") ) ## ----get_freq, echo=TRUE, warning=FALSE--------------------------------------- freq <- getFrequencies( object = midas, carrier_frequency = FALSE, experiment = "hla_alleles", compare = TRUE ) ## ----show_freq, echo=FALSE, warning=FALSE------------------------------------- kable(freq) %>% kable_styling(bootstrap_options = c("striped", "hover", "condensed")) %>% scroll_box(width = "100%", height = "200px") ## ----filter_freq, echo=TRUE, warning=FALSE------------------------------------ midas <- filterByFrequency( object = midas, experiment = "hla_alleles", lower_frequency_cutoff = 0.01 ) ## ----model definition, echo=TRUE, warning=FALSE------------------------------- # Logistic regression object <- glm(disease ~ term, data = midas, family = binomial(link = "logit")) ## ----association_analysis, echo=TRUE, warning=FALSE--------------------------- results <- runMiDAS( object = object, experiment = "hla_alleles", inheritance_model = "dominant", conditional = FALSE, omnibus = FALSE, lower_frequency_cutoff = 0.05 ) kableResults(results)