linted flexible data input

Author: ctastad

scripts/atac-multi-wnn.R

@@ -31,6 +31,7 @@ load(paste0(out_path, "tmp/preamble_image.RData"))
 # reference <- LoadH5Seuerat(params["clust.ref", ])
 
 for (i in 1:nrow(samples)) {
+  name <- samples$name[i]
   # the 10x hdf5 file contains both data types.
   x <- Read10X_h5(
     paste0(
@@ -101,7 +102,7 @@ for (i in 1:nrow(samples)) {
 
   save_figure(
     p1,
-    paste0(samples$name[i], "_counts_vln")
+    paste0(name, "_counts_vln")
   )
 
   # compute nucleosome signal score per cell
@@ -130,7 +131,7 @@ for (i in 1:nrow(samples)) {
 
   save_figure(
     p1,
-    paste0(samples$name[i], "_tss")
+    paste0(name, "_tss")
   )
 
   x$nucleosome_group <- ifelse(
@@ -146,7 +147,7 @@ for (i in 1:nrow(samples)) {
 
   save_figure(
     p1,
-    paste0(samples$name[i], "_frag_histogram")
+    paste0(name, "_frag_histogram")
   )
 
   p1 <- VlnPlot(
@@ -163,7 +164,7 @@ for (i in 1:nrow(samples)) {
 
   save_figure(
     p1,
-    paste0(samples$name[i], "_atac_vln")
+    paste0(name, "_atac_vln")
   )
 
   x <- subset(
@@ -241,7 +242,7 @@ for (i in 1:nrow(samples)) {
 
   save_figure(
     p1,
-    paste0(samples$name[i], "_mapping_dim")
+    paste0(name, "_mapping_dim")
   )
 
   save_H5object(refquery, "refquery_object")
@@ -260,7 +261,7 @@ for (i in 1:nrow(samples)) {
 
   save_figure(
     p1,
-    paste0(samples$name[i], "_depth")
+    paste0(name, "_depth")
   )
 
   x <- RunUMAP(
@@ -331,7 +332,7 @@ for (i in 1:nrow(samples)) {
 
   save_figure(
     p1 + p2 + p3,
-    paste0(samples$name[i], "_clustered"),
+    paste0(name, "_clustered"),
     width = 18,
     height = 6
   )
@@ -361,7 +362,7 @@ for (i in 1:nrow(samples)) {
 
   save_figure(
     p1,
-    paste0(samples$name[i], "_coverage")
+    paste0(name, "_coverage")
   )
 
   # Get a list of motif position frequency matrices from the JASPAR database
@@ -401,11 +402,11 @@ for (i in 1:nrow(samples)) {
 
   warnings()
 
-  x@meta.data$object <- samples$name[i]
+  x@meta.data$object <- name
   x@meta.data$group <- samples$group[i]
 
   assign( # giving names to objects
-    samples$name[i],
+    name,
     x
   )
 }

scripts/create-object.R

@@ -14,40 +14,60 @@ out_path <- paste0(args[1], "/")
 objects <- list()
 
 load(paste0(out_path, "tmp/preamble_image.RData"))
+print(samples)
 
 for (i in 1:nrow(samples)) {
   if (dir.exists(samples$dir[i])) {
+    name <- samples$name[i]
     x <- Read10X( # pulling data with no filter
       data.dir = samples$dir[i]
     )
     str_section_head("Raw Object") # logging
+    message("check 0")
 
     x <- CreateSeuratObject( # certain data will gen null matrix sans filters
       counts = x,
       project = samples$project[i],
       min.cells = params["min.cells", ],
       min.features = params["min.features", ]
     )
+    message("check 1")
 
+    print(samples$name[i])
     x@meta.data$object <- samples$name[i]
     x@meta.data$group <- samples$group[i]
+    print(unique(x$object))
+    message("check 2")
   } else {
     # TODO add compatibility with hdf5 format
 
     # it's assumed preformed objs have group and name metadata vars
     x <- readRDS(samples$dir[i])
+    x
+    message("check 3")
   }
 
+  message("check 4")
   objects <- c(objects, x)
+  print(objects)
+  message("check 5")
+  print(objects)
 }
 
-for (i in lenght(objects)) {
+length(objects)
+
+for (i in 1:length(objects)) {
   x <- objects[[i]]
+  message("check 6")
+  print(x)
+  name <- unique(x$object)
+  print(name)
 
   x[["percent.mt"]] <- PercentageFeatureSet(
     x,
     pattern = "(?i)^MT-"
   )
+  message("check 7")
 
   p1 <- VlnPlot(
     x,
@@ -61,10 +81,11 @@ for (i in lenght(objects)) {
 
   save_figure(
     p1,
-    paste0(unique(x[[i]]$object), "_unfilt_vln"),
+    paste0(name, "_unfilt_vln"),
     width = 12,
     height = 6
   )
+  message("check 8")
 
   p1 <- FeatureScatter(
     x,
@@ -80,10 +101,11 @@ for (i in lenght(objects)) {
 
   save_figure(
     (p1 + p2),
-    paste0(unique(x[[i]]$object), "_unfilt_scatter"),
+    paste0(name, "_unfilt_scatter"),
     width = 12,
     height = 6
   )
+  message("check 9")
 
   str_section_head("Base Seurat Object") # logging
 
@@ -96,6 +118,7 @@ for (i in lenght(objects)) {
       percent.mt < params["max.percent.mt", ] &
       percent.mt > params["min.percent.mt", ]
   )
+  message("check 10")
 
   # norm, dimred, and clustering
 
@@ -136,7 +159,7 @@ for (i in lenght(objects)) {
 
   save_figure(
     (p1 + p2),
-    paste0(unique(x[[i]]$object), "_var_features"),
+    paste0(name, "_var_features"),
     width = 12,
     height = 6
   )
@@ -155,7 +178,7 @@ for (i in lenght(objects)) {
 
   save_figure(
     (p1 + p2),
-    paste0(unique(x[[i]]$object), "individual_dimplot"),
+    paste0(name, "_individual_dimplot"),
     width = 12,
     height = 6
   )

scripts/preamble.R

@@ -56,7 +56,7 @@ str_section_head <- function(title) {
   message(strrep("=", 80))
   message(strrep("=", 80))
   message("")
-  message(paste(samples$name[i], title))
+  message(paste(name, title))
   message("")
   message(strrep("=", 80))
   message(strrep("=", 80))