Merge pull request #49 from MoTrPAC/replace-aorta

aorta -> vena cava

.Rbuildignore

@@ -6,3 +6,4 @@
 ^docs$
 ^pkgdown$
 ^\.github$
+CODEOWNERS

CODEOWNERS

@@ -0,0 +1 @@
+* @nicolerg

DESCRIPTION

@@ -2,7 +2,7 @@ Type: Package
 Package: MotrpacRatTraining6moData
 Title: Data for analysis of the MoTrPAC endurance exercise training study
     in 6-month-old rats
-Version: 1.9.1
+Version: 2.0.0
 Authors@R: c(
     person("Nicole", "Gay", , "nicole.r.gay@gmail.com", role = c("cre", "aut")),
     person("Pierre", "Jean Beltran", , "pjeanbeltran@gmail.com", role = "aut"),

NEWS.md

@@ -1,3 +1,7 @@
+# MotrpacRatTraining6moData 2.0.0 (2023-11-08)
+
+* Replace all instances of `t65-aorta` with `t99-vena-cava`, and `Aorta` with `Vena Cava`.
+
 # MotrpacRatTraining6moData 1.9.1 (2023-06-02)
 
 * Update `MotrpacRatTraining6mo` version requirement.

data-raw/OUTLIERS.R

@@ -28,13 +28,13 @@ OUTLIERS[assay_code == "immunoassay-rat-mag27plex", assay_code := "immunoassay"]
 OUTLIERS[,group := gsub(",", "_", group)]
 
 # add all 1w, 2w vena cava samples
-venacv = data.table(PHENO[PHENO$specimen.processing.sampletypedescription == "Aorta",])
+venacv = data.table(PHENO[PHENO$specimen.processing.sampletypedescription == "Vena Cava",])
 table(venacv[,specimen.processing.sampletypedescription])
 venacv = venacv[sex == "female" & group %in% c("1w","2w")]
 venacv[,.(viallabel, sex, group)]
 out2 = data.table(viallabel = as.character(venacv[,viallabel]),
                   tissue = "VENACV",
-                  tissue_code = "t65-aorta",
+                  tissue_code = "t99-vena-cava",
                   pid = venacv[,pid],
                   group = sprintf("female_%s", venacv[,group]),
                   reason = "BAT contamination")

data-raw/outliers.tsv

@@ -21,8 +21,8 @@ viallabel	tissue	pid	group	platform	reason
 90439016105	t61-colon	10486003	male,2w	immunoassay-rat-mag27plex	large fraction of missing values: 0.7037037
 90449016105	t61-colon	10641858	male,2w	immunoassay-rat-mag27plex	large fraction of missing values: 0.8148148
 90292016105	t61-colon	10220917	male,4w	immunoassay-rat-mag27plex	large fraction of missing values: 0.7037037
-all	t65-aorta (vena cava)		female,1w	all	brown adipose contamination
-all	t65-aorta (vena cava)		female,2w	all	brown adipose contamination
+all	t99-vena-cava		female,1w	all	brown adipose contamination
+all	t99-vena-cava		female,2w	all	brown adipose contamination
 90406015204	t52-hippocampus,stanford	10306471	female,4w	epigen-atac-seq	PC1
 90423015204	t52-hippocampus,stanford	10424911	male,1w	epigen-atac-seq	PC1
 90217015204	t52-hippocampus,stanford	10023259	male,control	epigen-atac-seq	PC1
@@ -51,7 +51,7 @@ all	t65-aorta (vena cava)		female,2w	all	brown adipose contamination
 90571016002	t60-adrenal	10953744	female,1w	transcript-rna-seq	PC1
 90229016102	t61-colon	10026355	male,control	transcript-rna-seq	PC2
 90289016302	t63-testes	10185585	male,4w	transcript-rna-seq	PC2
-90564016502	t65-aorta	10833331	female,1w	transcript-rna-seq	PC2
+90564016502	t99-vena-cava	10833331	female,1w	transcript-rna-seq	PC2
 90441016702	t67-small-intestine	10502300	male,2w	transcript-rna-seq	PC3
 90218016803	t68-liver	10024735	male,8w	transcript-rna-seq	PC2
 90266016902	t69-brown-adipose	10046380	female,control	transcript-rna-seq	PC3

inst/scripts/replace_aorta.R

@@ -0,0 +1,96 @@
+library(data.table)
+library(devtools)
+load_all()
+
+# copied from MotrpacRatTraining6mo
+list_available_data = function(package=NULL){
+  res = utils::data(package=package)
+  obj = res$results[,3]
+  # remove objects that can't be called directly
+  obj = obj[!grepl("\\(", obj)]
+  return(obj)
+}
+
+# list all available data objects
+objs = list_available_data(package="MotrpacRatTraining6moData")
+
+# identify data objects with "aorta" in them
+has_aorta = c()
+for (obj in objs){
+  print(obj)
+  # skip ATAC data, which doesn't have vena cava data
+  if(grepl("ATAC", obj)){
+    next()
+  }
+  # skip GENE_UNIVERSES, which already uses VENACV
+  if(obj=="GENE_UNIVERSES"){
+    next()
+  }
+
+  data = get(obj)
+  if (is.data.frame(data)){
+    if (any(data == "t65-aorta", na.rm=TRUE)){
+      has_aorta = c(has_aorta, obj)
+    }
+    if (any(data == "aorta", na.rm=TRUE)){
+      has_aorta = c(has_aorta, obj)
+    }
+    if (any(data == "Aorta", na.rm=TRUE)){
+      has_aorta = c(has_aorta, obj)
+    }
+  }else if (is.vector(data)){
+    if("t65-aorta" %in% data){
+      has_aorta = c(has_aorta, obj)
+    }
+  }else{
+    print(sprintf("Not sure what type %s is", obj))
+  }
+}
+
+# manually edit data objects
+unique(has_aorta)
+
+data("METAB_VENACV_DA_METAREG")
+METAB_VENACV_DA_METAREG$tissue_code[METAB_VENACV_DA_METAREG$tissue_code == "t65-aorta"] = "t99-vena-cava"
+stopifnot(!any(METAB_VENACV_DA_METAREG == "t65-aorta", na.rm = TRUE))
+usethis::use_data(METAB_VENACV_DA_METAREG, overwrite = T)
+
+data("METAB_VENACV_DA")
+METAB_VENACV_DA$tissue_code[METAB_VENACV_DA$tissue_code == "t65-aorta"] = "t99-vena-cava"
+stopifnot(!any(METAB_VENACV_DA == "t65-aorta", na.rm = TRUE))
+usethis::use_data(METAB_VENACV_DA, overwrite = T)
+
+data("OUTLIERS")
+OUTLIERS$tissue_code[OUTLIERS$tissue_code == "t65-aorta"] = "t99-vena-cava"
+stopifnot(!any(OUTLIERS == "t65-aorta", na.rm = TRUE))
+usethis::use_data(OUTLIERS, overwrite = T)
+
+data("TISSUE_ABBREV_TO_CODE")
+TISSUE_ABBREV_TO_CODE[TISSUE_ABBREV_TO_CODE == "t65-aorta"] = "t99-vena-cava"
+stopifnot(!any(TISSUE_ABBREV_TO_CODE == "t65-aorta", na.rm = TRUE))
+usethis::use_data(TISSUE_ABBREV_TO_CODE, overwrite = T)
+
+data("TISSUE_CODE_TO_ABBREV")
+names(TISSUE_CODE_TO_ABBREV)[names(TISSUE_CODE_TO_ABBREV) == "t65-aorta"] = "t99-vena-cava"
+stopifnot(!any(TISSUE_CODE_TO_ABBREV == "t65-aorta", na.rm = TRUE))
+stopifnot(!any(names(TISSUE_CODE_TO_ABBREV) == "t65-aorta", na.rm = TRUE))
+usethis::use_data(TISSUE_CODE_TO_ABBREV, overwrite = T)
+
+data("TRAINING_REGULATED_FEATURES")
+TRAINING_REGULATED_FEATURES$tissue_code[TRAINING_REGULATED_FEATURES$tissue_code == "t65-aorta"] = "t99-vena-cava"
+stopifnot(!any(TRAINING_REGULATED_FEATURES == "t65-aorta", na.rm = TRUE))
+usethis::use_data(TRAINING_REGULATED_FEATURES, overwrite = T)
+
+data("TRNSCRPT_VENACV_DA")
+TRNSCRPT_VENACV_DA$tissue_code[TRNSCRPT_VENACV_DA$tissue_code == "t65-aorta"] = "t99-vena-cava"
+stopifnot(!any(TRNSCRPT_VENACV_DA == "t65-aorta", na.rm = TRUE))
+usethis::use_data(TRNSCRPT_VENACV_DA, overwrite = T)
+
+data("PHENO")
+PHENO[PHENO$tissue_code_no == "T65",]
+PHENO$tissue_code_no[PHENO$tissue_code_no == "T65"] = "T99"
+PHENO$tissue_description[PHENO$tissue_description == "Aorta"] = "Vena Cava"
+PHENO$specimen.processing.aliquotdescription = gsub("Aorta", "Vena Cava", PHENO$specimen.processing.aliquotdescription)
+PHENO$specimen.processing.sampletypedescription[PHENO$specimen.processing.sampletypedescription == "Aorta"] = "Vena Cava"
+stopifnot(!any(PHENO == "t65-aorta", na.rm = TRUE))
+usethis::use_data(PHENO, overwrite = T)

inst/scripts/save_sample_level_data_metabolomics.Rmd

@@ -339,7 +339,7 @@ separate(dataset,into=c("phase","tissue","ome","modality","platform"),
 #5. Remove vena cava contaminated samples---------------------------------------
 # First remove female 1w and 2w vena cava samples from data 
 mutate(data_for_dea = pmap(list(tissue,data_for_dea,pheno), function(tissue,dat,pheno){
-  if(tissue == "t65-aorta"){
+  if(tissue == "t99-vena-cava"){
     to_include <- pheno %>% filter(!((sex == "F") &
                                        (tr_group == "1_0" | tr_group == "2_0")))
     return(dat[,to_include$viallabel])

vignettes/MotrpacRatTraining6moData.Rmd

@@ -64,7 +64,7 @@ div.yellow {
 
 <div class = "yellow">
 
-This vignette is under construction. If something is unclear or obviously missing, 
+If you run into problems, 
 please submit an issue [here](https://github.com/MoTrPAC/MotrpacRatTraining6moData/issues). 
 
 </div>