t Merge branch 'master' of github.com:AlexanderLabWHOI/EUKulele

docs/source/databaseandconfig.rst

@@ -11,7 +11,7 @@ Four databases can be downloaded and formatted automatically when invoking ``EUK
 - `PhyloDB <https://drive.google.com/drive/u/0/folders/0B-BsLZUMHrDQfldGeDRIUHNZMEREY0g3ekpEZFhrTDlQSjQtbm5heC1QX2V6TUxBeFlOejQ>`_
 - `EukProt <https://figshare.com/articles/EukProt_a_database_of_genome-scale_predicted_proteins_across_the_diversity_of_eukaryotic_life/12417881/2>`_
 - `MMETSP <https://zenodo.org/record/1212585#.Xw3PoJNKhTZ>`_ 
-- `MMETSP <https://zenodo.org/record/1212585#.Xw3PoJNKhTZ>`_ and `MMETSP <https://mmp.sfb.uit.no/databases/marref/#/>`_ *Default*
+- `MMETSP <https://zenodo.org/record/1212585#.Xw3PoJNKhTZ>`_ and `MarRef <https://mmp.sfb.uit.no/databases/marref/#/>`_ *Default*
 - `EukZoo <https://github.com/zxl124/EukZoo-database>`_
 
 Note that the MMETSP database is generated using cleaned MMETSP assemblies originally derived from, but not identical to, the assemblies stored in full at the link above. In order to download the cleaned assemblies used to create the ``EUKulele`` MMETSP database, please follow the instructions recorded in `this Github repository <https://github.com/shu251/download-cleaned-mmetsp>`_.

scripts/process-output.R

@@ -0,0 +1,54 @@
+pacman::p_load(ggplot2,dplyr,data.table)
+
+## FUNCTIONS ##
+
+process_sub_eukulele <- function(eukulele_dir, label_out, all_results, salmon_dir,
+                               salmon_format="num", is_protein=FALSE) {
+    curr_dir = file.path(eukulele_dir,"taxonomy_estimation")
+    for (curr_file in list.files(curr_dir)) {
+        eukulele_estimates = data.frame(fread(file.path(curr_dir, curr_file), sep = "\t")) %>%
+                dplyr::mutate(full_classification=case_when(!is.na(full_classification)~full_classification,
+                                                            TRUE~"Unclassified")) %>%
+                tidyr::separate(full_classification, sep = ";",
+                                                     into = c("Domain","Supergroup","Phylum","Class","Order",
+                                                              "Family","Genus","Species"))%>% 
+                dplyr::mutate(Domain = unlist(lapply(as.character(EUKulele_out$Domain),trimws)))%>% 
+                dplyr::mutate(Supergroup = unlist(lapply(as.character(EUKulele_out$Supergroup),trimws)))%>% 
+                dplyr::mutate(Phylum = unlist(lapply(as.character(EUKulele_out$Phylum),trimws)))%>% 
+                dplyr::mutate(Class = unlist(lapply(as.character(EUKulele_out$Class),trimws)))%>% 
+                dplyr::mutate(Order = unlist(lapply(as.character(EUKulele_out$Order),trimws)))%>% 
+                dplyr::mutate(Family = unlist(lapply(as.character(EUKulele_out$Family),trimws)))%>% 
+                dplyr::mutate(Genus = unlist(lapply(as.character(EUKulele_out$Genus),trimws)))%>% 
+                dplyr::mutate(Species = unlist(lapply(as.character(EUKulele_out$Species),trimws)))
+
+        if (is_protein) {
+            eukulele_estimates = eukulele_estimates %>% tidyr::separate(transcript_name,sep="\\.p",
+                                                                        into=c("transcript_name",
+                                                                               "protein_id"))
+        }
+        number_file = unlist(strsplit(curr_file,"_"))[1]
+        salmon_file = read.csv(file.path(salmon_dir,paste0(salmon_format,as.character(number_file), "_quant"),
+                                 "quant.sf"), sep = "\t")
+        matched_file= salmon_file %>% dplyr::full_join(eukulele_estimates,by=c("Name"="transcript_name"))
+        matched_file["Sample"] = curr_file
+        matched_file["SplitSamp"] = number_file
+        matched_file["Type"] = label_out
+
+        matched_file =  matched_file %>%
+            tidyr::replace_na(list("Domain"="Uncertain",
+                                   "Supergroup"="Uncertain",
+                                   "Phylum"="Uncertain",
+                                   "Class"="Uncertain",
+                                   "Order"="Uncertain",
+                                   "Family"="Uncertain",
+                                   "Genus"="Uncertain",
+                                   "Species"="Uncertain"))
+        all_results = all_results %>% dplyr::bind_rows(matched_file)
+    }
+    return(all_results)
+}
+
+all_results=data.frame()
+all_results = process_sub_eukulele("CAG_eukulele_pleuro_metazoans", "Metazoan_DB", all_results, 
+                     "/vortexfs1/omics/alexander/akrinos/2021-remodeling-eukrhythmic/2021-09-ALOHA/intermediate-files/04-compare/09-CAG-mapping/salmon",
+                     salmon_format="num", is_protein=TRUE)