Dev kadm

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: kimma
 Type: Package
 Title: Kinship In Mixed Model Analysis of RNA-seq
-Version: 1.6.1
+Version: 1.6.3
 Author: Kim Dill-McFarland
 Maintainer: Kim Dill-McFarland <kadm@uw.edu>
 Description: Linear mixed effects models with pairwise kinship for RNA-seq data.
@@ -16,7 +16,6 @@ Imports:
     data.table,
     doParallel,
     dplyr,
-    edgeR,
     emmeans,
     forcats,
     foreach,
@@ -30,9 +29,10 @@ Imports:
     tibble,
     tidyr,
     tidyselect
-RoxygenNote: 7.2.1
+RoxygenNote: 7.3.1
 Depends: 
-    R (>= 4.2)
+    R (>= 4.4)
 Suggests: 
-    testthat (>= 3.0.0)
+    testthat (>= 3.0.0),
+    edgeR
 Config/testthat/edition: 3

NAMESPACE

@@ -5,7 +5,9 @@ export(extract_lmFit)
 export(kmFit)
 export(kmFit_eQTL)
 export(summarise_kmFit)
+export(summarise_lmFit)
 export(summarize_kmFit)
+export(summarize_lmFit)
 importFrom(foreach,"%dopar%")
 importFrom(magrittr,"%>%")
 importFrom(tidyselect,vars_select_helpers)

R/kmFit.R

@@ -167,7 +167,9 @@ kmFit <- function(dat=NULL, kin=NULL, patientID="ptID", libraryID="libID",
   if(!is.null(subset_var) & is.null(subset_lvl)){
     stop("Sample subsetting has been selected. Please also provide subset_lvl")}
   if(run_lmerel & !grepl("\\|", model)){
-    stop("Kinship models require a random effect in the model as in (1 | ptID)")}
+    stop("Kinship models require a random effect in the model as in (1 | patientID)")}
+  if(run_lme & !grepl("\\|", model)){
+    stop("LME models require a random effect in the model")}
   if(is.null(kin) & run_lmerel){
     stop("Kinship matrix is required to run lmerel")}
   if(!run_lm & !run_lme & !run_lmerel & !run_contrast){
@@ -201,16 +203,16 @@ kmFit <- function(dat=NULL, kin=NULL, patientID="ptID", libraryID="libID",
   #Make formulae. as.formula does not work
   if(grepl("\\|", model)){
     model.temp <- strsplit(gsub(" ", "", model), split = "\\+\\(1")[[1]][1]
-    model.lm <- paste("expression", model.temp, sep="")
+    model_lm <- paste("expression", model.temp, sep="")
   } else {
-    model.lm <- paste("expression", model, sep="")
-    model.lm <- gsub(" ","",model.lm)
+    model_lm <- paste("expression", model, sep="")
+    model_lm <- gsub(" ","",model_lm)
   }
-  model.lme <- paste("expression", gsub(" ", "", model), sep="")
+  model_lme <- paste("expression", gsub(" ", "", model), sep="")
 
   #Model message
-  if(run_lm){ message(paste("lm model:",model.lm))}
-  if(run_lme | run_lmerel){ message(paste("lme/lmerel model:",model.lme))}
+  if(run_lm){ message(paste("lm model:",model_lm))}
+  if(run_lme | run_lmerel){ message(paste("lme/lmerel model:",model_lme))}
 
   #If no contrast variable set, as all
   if(run_contrast & is.null(contrast_var)){
@@ -257,7 +259,7 @@ kmFit <- function(dat=NULL, kin=NULL, patientID="ptID", libraryID="libID",
           stop(paste("Contrast variable", v, "is numeric. Please specify only character/factor contrasts."))
         }
       } else {
-        v.class <- class(meta.temp[,v])
+        v.class <- class(unlist(meta.temp[,v]))
         if(v.class %in% c("numeric","integer","double")){
           stop(paste("Contrast variable", v, "is numeric. Please specify only character/factor contrasts."))
         }
@@ -269,7 +271,7 @@ kmFit <- function(dat=NULL, kin=NULL, patientID="ptID", libraryID="libID",
   to.model.ls <- kimma_cleaning(dat, kin, patientID, libraryID,
                                 counts, meta, genes, weights,
                                 subset_var, subset_lvl, subset_genes,
-                                model.lm, genotype_name, run_lmerel)
+                                model_lm, genotype_name, run_lmerel)
 
   ###### Run models ######
   #create blank df to hold results
@@ -297,7 +299,7 @@ kmFit <- function(dat=NULL, kin=NULL, patientID="ptID", libraryID="libID",
     if(run_lm){
     #Wrap model run in error catch to allow loop to continue even if a single model fails
      results.lm.ls <- tryCatch({
-       kimma_lm(model.lm, to.model.gene, gene, use_weights, metrics)
+       kimma_lm(model_lm, to.model.gene, gene, use_weights, metrics)
      }, error=function(e){
        results.lm.ls[["error"]] <- data.frame(model="lm",
                                                gene=gene,
@@ -311,7 +313,7 @@ kmFit <- function(dat=NULL, kin=NULL, patientID="ptID", libraryID="libID",
     if(run_lme){
       #Wrap model run in error catch to allow loop to continue even if a single model fails
       results.lme.ls <- tryCatch({
-        kimma_lme(model.lme, to.model.gene, gene, use_weights, metrics)
+        kimma_lme(model_lme, to.model.gene, gene, use_weights, metrics)
         }, error=function(e){
           results.lme.ls[["error"]] <- data.frame(model="lme",
                                                   gene=gene,
@@ -325,7 +327,7 @@ kmFit <- function(dat=NULL, kin=NULL, patientID="ptID", libraryID="libID",
     if(run_lmerel){
       #Wrap model run in error catch to allow loop to continue even if a single model fails
       results.kin.ls <- tryCatch({
-        kimma_lmerel(model.lme, to.model.gene, gene, to.model.ls[["kin.subset"]],
+        kimma_lmerel(model_lme, to.model.gene, gene, to.model.ls[["kin.subset"]],
                      use_weights, patientID, metrics)
         }, error=function(e){
           results.kin.ls[["error"]] <- data.frame(model="lmerel",

R/summarise_kmFit.R

@@ -181,5 +181,9 @@ summarise_kmFit <- function(fdr, fdr_cutoff = c(0.05,0.1,0.2,0.3,0.4,0.5),
 #' @rdname summarise_kmFit
 #' @export
 summarize_kmFit <- summarise_kmFit
+#' @rdname summarise_kmFit
+#' @export
 summarise_lmFit <- summarise_kmFit
+#' @rdname summarise_kmFit
+#' @export
 summarize_lmFit <- summarise_kmFit