diff --git a/bin/config_CP_input_dauer.R b/bin/config_CP_input_dauer.R
deleted file mode 100644
index 17e0690..0000000
--- a/bin/config_CP_input_dauer.R
+++ /dev/null
@@ -1,92 +0,0 @@
-#!/usr/bin/env Rscript
-library(dplyr)
-library(tidyr)
-library(tibble)
-library(stringr)
-library(readr)
-library(glue)
-library(purrr)
-library(data.table)
-
-#==============================================================================#
-# Arguments
-#==============================================================================#
-# 1 - full path to project directory
-# 2 - the path to the well_mask - HARDCODE NOW
-# 3 - the group argument from main.nf - default is "plate,well"
-# 4 - the edited pipeline path
-# 5 - the out path
-args <- commandArgs(trailingOnly = TRUE)
-
-#==============================================================================#
-# Make Metadata NEEDS TO BE ADAPATBLE TO MULTIPLE WAVELENGTHS
-#==============================================================================#
-projDir <- args[1]
-projName <- stringr::str_extract(projDir, pattern = "([^/]+$)")
-
-raw_imagesDir <- paste0(projDir, "/raw_images")
-
-# parse file names from directory - need wavelength in file name
-meta1 <- tibble::tibble(file = list.files(path = raw_imagesDir),
-                        file_path = list.files(path = raw_imagesDir, full.names = T)) %>%
-  dplyr::mutate(copy = file) %>%
-  tidyr::separate(col = copy, into = c("date","exp","plate","mag"), sep = "-") %>%
-  tidyr::separate(col = mag, into = c("mag","well", "wave"), sep = "_") %>%
-  tidyr::separate(col = wave, into = c("wave","TIF"), sep = "[.]") %>%
-  dplyr::select(-TIF) %>%
-  dplyr::mutate(row = stringr::str_extract(well, pattern = "[A-Z]"),
-                col = stringr::str_extract(well, pattern = "[0-9][0-9]"),
-                Image_PathName_wellmask_98.png = stringr::str_replace(args[2], pattern = "([^/]+$)", replacement = ""),
-                Image_FileName_wellmask_98.png = stringr::str_extract(args[2], pattern = "([^/]+$)"))
-
-# num of wavelengths - add logic for how to make metadata from multiple wavelengths
-n_wave <- length(unique(meta1$wave))
-
-# add group
-groups <- stringr::str_split(args[3], pattern = ",")[[1]]
-meta1$group <- apply( meta1[, groups], 1, paste, collapse = "_")
-
-# add image types and set metadata names - hardcode image names - needs to be flexible for multiple pipeline profiles
-meta2 <- meta1 %>%
-  tidyr::pivot_wider(names_from = wave, values_from = c(file, file_path)) %>%
-  dplyr::rename(Image_FileName_RawBF = file_w1,
-                Image_PathName_RawBF = file_path_w1,  
-                Image_FileName_RawRFP = file_w2,
-                Image_PathName_RawRFP = file_path_w2) %>%
-  dplyr::mutate(Image_PathName_RawRFP = stringr::str_replace(Image_PathName_RawRFP, pattern = "([^/]+$)", replacement = ""),
-                Image_PathName_RawBF = stringr::str_replace(Image_PathName_RawBF, pattern = "([^/]+$)", replacement = "")) %>%
-  dplyr::select(Metadata_Experiment = exp,
-                Metadata_Date = date,
-                Metadata_Plate = plate,
-                Metadata_Well = well,
-                #Metadata_Column = col,
-                #Metadata_Row = row,
-                Metadata_Group = group,
-                Metadata_Magnification = mag,
-                Image_FileName_RawBF,
-                Image_PathName_RawBF,
-                Image_FileName_RawRFP,
-                Image_PathName_RawRFP,
-                Image_FileName_wellmask_98.png,
-                Image_PathName_wellmask_98.png)
-
-write.table(meta2, file = glue::glue("metadata.csv"), quote=FALSE, sep=',', row.names = F)
-
-#==============================================================================#
-# Make groups.tsv file for runCP
-#==============================================================================#
-gs <- meta2 %>%
-  dplyr::distinct(Metadata_Group, .keep_all=T) %>%
-  dplyr::mutate(group = paste0("Metadata_Group=", Metadata_Group),
-                pipeline = args[4],
-                output = paste0(args[5], "/CP_output/", Metadata_Group)) %>%
-  dplyr::select(group:output)
-
-write.table(gs, file = glue::glue("groups.tsv"), quote=FALSE, sep='\t', row.names = F)
-
-#==============================================================================#
-# Make dirs for CP output
-#==============================================================================#
-for(i in unique(gs$output)){
-  dir.create(i, recursive = T)
-}
diff --git a/bin/config_CP_input_toxin.R b/bin/config_CP_input_toxin.R
deleted file mode 100644
index a169b0b..0000000
--- a/bin/config_CP_input_toxin.R
+++ /dev/null
@@ -1,80 +0,0 @@
-#!/usr/bin/env Rscript
-library(dplyr)
-library(tidyr)
-library(tibble)
-library(stringr)
-library(readr)
-library(glue)
-library(purrr)
-library(data.table)
-
-#==============================================================================#
-# Arguments
-#==============================================================================#
-# 1 - full path to project directory
-# 2 - the path to the well_mask - HARDCODE NOW
-# 3 - the group argument from main.nf - default is "plate,well"
-# 4 - the edited pipeline path
-# 5 - the out path
-# args <- c("/projects/b1059/projects/Tim/cellprofiler-nf/projects/20220128_GWA09", "/projects/b1059/projects/Tim/cellprofiler-nf/input_data/well_masks/wellmask_98.png",
-#          "plate,well", "/projects/b1059/projects/Tim/cellprofiler-nf/projects/20220128_GWA09/pipelines/pipeline.cppipe", "/projects/b1059/projects/Tim/cellprofiler-nf/projects/20220128_GWA09/CP_output")
-args <- commandArgs(trailingOnly = TRUE)
-
-#==============================================================================#
-# Make Metadata NEEDS TO BE ADAPATBLE TO MULTIPLE WAVELENGTHS
-#==============================================================================#
-projDir <- args[1]
-projName <- stringr::str_extract(projDir, pattern = "([^/]+$)")
-
-raw_imagesDir <- paste0(projDir, "/raw_images")
-
-# parse file names from directory - need wavelength in file name
-meta1 <- tibble::tibble(file = list.files(path = raw_imagesDir),
-                        file_path = list.files(path = raw_imagesDir, full.names = T)) %>%
-  dplyr::mutate(copy = file) %>%
-  tidyr::separate(col = copy, into = c("date","exp","plate","mag"), sep = "-") %>%
-  tidyr::separate(col = mag, into = c("mag","well"), sep = "_") %>%
-  tidyr::separate(col = well, into = c("well","TIF"), sep = "[.]") %>%
-  dplyr::select(-TIF) %>%
-  dplyr::mutate(row = stringr::str_extract(well, pattern = "[A-Z]"),
-                col = stringr::str_extract(well, pattern = "[0-9][0-9]"),
-                Image_PathName_wellmask_98.png = stringr::str_replace(args[2], pattern = "([^/]+$)", replacement = ""),
-                Image_FileName_wellmask_98.png = stringr::str_extract(args[2], pattern = "([^/]+$)"))
-
-# add group
-groups <- stringr::str_split(args[3], pattern = ",")[[1]]
-meta1$group <- apply( meta1[, groups], 1, paste, collapse = "_")
-
-meta2 <- meta1 %>%
-  dplyr::mutate(Image_PathName_RawBF = stringr::str_replace(file_path, pattern = "([^/]+$)", replacement = "")) %>%
-  dplyr::select(Metadata_Experiment = exp,
-                Metadata_Date = date,
-                Metadata_Plate = plate,
-                Metadata_Well = well,
-                Metadata_Group = group,
-                Metadata_Magnification = mag,
-                Image_FileName_RawBF = file,
-                Image_PathName_RawBF,
-                Image_FileName_wellmask_98.png,
-                Image_PathName_wellmask_98.png)
-
-write.table(meta2, file = glue::glue("metadata.csv"), quote=FALSE, sep=',', row.names = F)
-
-#==============================================================================#
-# Make groups.tsv file for runCP
-#==============================================================================#
-gs <- meta2 %>%
-  dplyr::distinct(Metadata_Group, .keep_all=T) %>%
-  dplyr::mutate(group = paste0("Metadata_Group=", Metadata_Group),
-                pipeline = args[4],
-                output = paste0(args[5], "/CP_output/", Metadata_Group)) %>%
-  dplyr::select(group:output)
-
-write.table(gs, file = glue::glue("groups.tsv"), quote=FALSE, sep='\t', row.names = F)
-
-#==============================================================================#
-# Make dirs for CP output
-#==============================================================================#
-for(i in unique(gs$output)){
-  dir.create(i, recursive = T)
-}
diff --git a/bin/makeMetadata_dauer.R b/bin/makeMetadata_dauer.R
new file mode 100755
index 0000000..0cba482
--- /dev/null
+++ b/bin/makeMetadata_dauer.R
@@ -0,0 +1,72 @@
+#!/usr/bin/env -S Rscript --vanilla
+library(dplyr)
+library(tidyr)
+library(tibble)
+library(stringr)
+library(readr)
+library(purrr)
+library(data.table)
+
+#==============================================================================#
+# Arguments
+#==============================================================================#
+# 1 - A list of input files
+# 2 - the path to the well_mask - HARDCODE NOW
+# 3 - the group argument from main.nf - default is "plate,well"
+# 4 - the edited pipeline path
+# 5 - the out path
+args <- commandArgs(trailingOnly = TRUE)
+#==============================================================================#
+# Make Metadata NEEDS TO BE ADAPATBLE TO MULTIPLE WAVELENGTHS
+#==============================================================================#
+# parse file names from directory - need wavelength in file name
+meta1 <- read_delim(
+  args[1], 
+  col_names = FALSE, 
+  delim = "\t") %>% 
+  select(file_path = X1) %>% 
+  extract(file_path, into = "file", remove = FALSE, regex = ".*/(.*)$") %>% 
+  extract(file, 
+          remove = FALSE, 
+          regex = "^(.*)-(.*)-(.*)-(.*)_(.*)_(.*)\\.(.*)$", 
+          into = c("date","exp","plate","mag","well","wave","TIF")) %>% 
+  select(-TIF) %>%
+  dplyr::mutate(row = stringr::str_extract(well, pattern = "[A-Z]"),
+                col = stringr::str_extract(well, pattern = "[0-9][0-9]"),
+                Image_PathName_wellmask_98.png = stringr::str_replace(args[2], pattern = "([^/]+$)", replacement = ""),
+                Image_FileName_wellmask_98.png = stringr::str_extract(args[2], pattern = "([^/]+$)"))
+
+# add group
+groups <- stringr::str_split(args[3], pattern = ",")[[1]]
+meta1$group <- apply( meta1[, groups], 1, paste, collapse = "_")
+
+# add image types and set metadata names - hardcode image names - needs to be flexible for multiple pipeline profiles
+meta2 <- meta1 %>%
+  tidyr::pivot_wider(names_from = wave, values_from = c(file, file_path), ) %>%
+  dplyr::rename(Image_FileName_RawBF = file_w1,
+                Image_PathName_RawBF = file_path_w1,  
+                Image_FileName_RawRFP = file_w2,
+                Image_PathName_RawRFP = file_path_w2) %>%
+  dplyr::mutate(
+    Image_PathName_RawRFP = stringr::str_replace(
+      Image_PathName_RawRFP, pattern = "([^/]+$)", replacement = ""
+    ),
+    Image_PathName_RawBF = stringr::str_replace(
+      Image_PathName_RawBF, pattern = "([^/]+$)", replacement = ""
+    )
+  ) %>%  
+  dplyr::select(
+    Metadata_Experiment = exp,
+    Metadata_Date = date,
+    Metadata_Plate = plate,
+    Metadata_Well = well,
+    Metadata_Group = group,
+    Metadata_Magnification = mag,
+    Image_FileName_RawBF,
+    Image_PathName_RawBF,
+    Image_FileName_RawRFP,
+    Image_PathName_RawRFP,
+    Image_FileName_wellmask_98.png,
+    Image_PathName_wellmask_98.png)
+
+write.table(meta2, file = "metadata.csv", quote=FALSE, sep=',', row.names = F)
\ No newline at end of file
diff --git a/bin/makeMetadata_toxin.R b/bin/makeMetadata_toxin.R
new file mode 100755
index 0000000..c4e70d0
--- /dev/null
+++ b/bin/makeMetadata_toxin.R
@@ -0,0 +1,58 @@
+#!/usr/bin/env -S Rscript --vanilla
+library(dplyr)
+library(tidyr)
+library(tibble)
+library(stringr)
+library(readr)
+library(purrr)
+library(data.table)
+
+#==============================================================================#
+# Arguments
+#==============================================================================#
+# 1 - A list of input files
+# 2 - the path to the well_mask - HARDCODE NOW
+# 3 - the group argument from main.nf - default is "plate,well"
+# 4 - the edited pipeline path
+# 5 - the out path
+args <- commandArgs(trailingOnly = TRUE)
+
+#==============================================================================#
+# Make Metadata NEEDS TO BE ADAPATBLE TO MULTIPLE WAVELENGTHS
+#==============================================================================#
+# parse file names from directory - need wavelength in file name
+meta1 <- read_delim(
+  args[1], 
+  col_names = FALSE, 
+  delim = "\t") %>% 
+  select(file_path = X1) %>% 
+  extract(file_path, into = "file", remove = FALSE, regex = ".*/(.*)$") %>% 
+  extract(file, 
+          remove = FALSE, 
+          regex = "^(.*)-(.*)-(.*)-(.*)_(.*)\\.(.*)$", 
+          into = c("date","exp","plate","mag","well","TIF")) %>% 
+  select(-TIF) %>%
+  dplyr::mutate(row = stringr::str_extract(well, pattern = "[A-Z]"),
+                col = stringr::str_extract(well, pattern = "[0-9][0-9]"),
+                Image_PathName_wellmask_98.png = stringr::str_replace(args[2], pattern = "([^/]+$)", replacement = ""),
+                Image_FileName_wellmask_98.png = stringr::str_extract(args[2], pattern = "([^/]+$)"))
+
+# add group
+groups <- stringr::str_split(args[3], pattern = ",")[[1]]
+meta1$group <- apply( meta1[, groups], 1, paste, collapse = "_")
+
+# add image types and set metadata names - hardcode image names - needs to be flexible for multiple pipeline profiles
+meta2 <- meta1 %>%
+  dplyr::mutate(Image_PathName_RawBF = stringr::str_replace(file_path, pattern = "([^/]+$)", replacement = "")) %>%
+  dplyr::select(Metadata_Experiment = exp,
+                Metadata_Date = date,
+                Metadata_Plate = plate,
+                Metadata_Well = well,
+                Metadata_Group = group,
+                Metadata_Magnification = mag,
+                Image_FileName_RawBF = file,
+                Image_PathName_RawBF,
+                Image_FileName_wellmask_98.png,
+                Image_PathName_wellmask_98.png)
+
+write.table(meta2, file = "metadata.csv", quote=FALSE, sep=',', row.names = F)
\ No newline at end of file
diff --git a/bin/proc_CP_output_dauer.R b/bin/proc_CP_output.R
old mode 100644
new mode 100755
similarity index 74%
rename from bin/proc_CP_output_dauer.R
rename to bin/proc_CP_output.R
index 92ad0b1..67ce906
--- a/bin/proc_CP_output_dauer.R
+++ b/bin/proc_CP_output.R
@@ -1,24 +1,25 @@
-# /usr/bin/Rscript
+#!/usr/bin/env -S Rscript --vanilla
 library(fs)
 library(dplyr)
 library(tidyr)
 library(tibble)
 library(stringr)
 library(readr)
-library(glue)
 library(purrr)
 
 #==============================================================================#
 # Arguments
 #==============================================================================#
 # 1 - out directory path
+# 2 - project name
+# 3 - run stamp
 args <- commandArgs(trailingOnly = TRUE)
 
 #==============================================================================#
 # Read CP output data
 #==============================================================================#
 # get the output for each model
-dir <- glue::glue("{args[1]}/processed_data")
+dir <- "processed_data"
 
 # read in files and manipulate with  
 model_df <- dir %>%
@@ -36,10 +37,7 @@ model_df_list <- split.data.frame(model_df, model_df$model)
 lapply(seq_along(model_df_list), function(i) assign(names(model_df_list)[i], model_df_list[[i]], envir = .GlobalEnv))
 
 # save as R.data
-proj_name <- stringr::str_extract(args[1], pattern = "[^\\/]+(?=(?:\\/[^\\/]+){1}$)")
-run_stamp <- stringr::str_extract(args[1], pattern = "([^/]+$)")
+proj_name <- args[1]
+run_stamp <- args[2]
 save(list = c(ls(pattern = "model.outputs")),
-     file = glue::glue("{args[1]}/processed_data/{proj_name}_{run_stamp}.RData"))
-
-# clean up extra CP_outputs for now
-system(command = glue::glue("if [ -d {args[1]}/CP_output ]; then rm -Rf {args[1]}/CP_output; fi"))
\ No newline at end of file
+     file = paste0("processed_data/", args[1], "_", args[2], ".RData"))
\ No newline at end of file
diff --git a/bin/proc_CP_output_toxin.R b/bin/proc_CP_output_toxin.R
deleted file mode 100644
index 92ad0b1..0000000
--- a/bin/proc_CP_output_toxin.R
+++ /dev/null
@@ -1,45 +0,0 @@
-# /usr/bin/Rscript
-library(fs)
-library(dplyr)
-library(tidyr)
-library(tibble)
-library(stringr)
-library(readr)
-library(glue)
-library(purrr)
-
-#==============================================================================#
-# Arguments
-#==============================================================================#
-# 1 - out directory path
-args <- commandArgs(trailingOnly = TRUE)
-
-#==============================================================================#
-# Read CP output data
-#==============================================================================#
-# get the output for each model
-dir <- glue::glue("{args[1]}/processed_data")
-
-# read in files and manipulate with  
-model_df <- dir %>%
-  fs::dir_ls(regexp = "\\.csv$") %>% # find paths to csvs in dir
-  purrr::map_dfr(readr::read_csv, .id = "model") %>%
-  dplyr::mutate(Metadata_Date = as.integer(Metadata_Date), 
-                model = stringr::str_remove(fs::path_file(as.character(model)), pattern = ".csv"),
-                model = paste0(model, ".model.outputs")) %>%
-  dplyr::arrange(model, ImageNumber)
-
-# split to list
-model_df_list <- split.data.frame(model_df, model_df$model)
-
-# export list items to global env
-lapply(seq_along(model_df_list), function(i) assign(names(model_df_list)[i], model_df_list[[i]], envir = .GlobalEnv))
-
-# save as R.data
-proj_name <- stringr::str_extract(args[1], pattern = "[^\\/]+(?=(?:\\/[^\\/]+){1}$)")
-run_stamp <- stringr::str_extract(args[1], pattern = "([^/]+$)")
-save(list = c(ls(pattern = "model.outputs")),
-     file = glue::glue("{args[1]}/processed_data/{proj_name}_{run_stamp}.RData"))
-
-# clean up extra CP_outputs for now
-system(command = glue::glue("if [ -d {args[1]}/CP_output ]; then rm -Rf {args[1]}/CP_output; fi"))
\ No newline at end of file
diff --git a/input_data/CP_pipelines/dauer-nf.cppipe b/input_data/CP_pipelines/dauer-nf.cppipe
old mode 100644
new mode 100755
index efc0392..0536a9c
--- a/input_data/CP_pipelines/dauer-nf.cppipe
+++ b/input_data/CP_pipelines/dauer-nf.cppipe
@@ -6,8 +6,8 @@ ModuleCount:31
 HasImagePlaneDetails:False
 
 LoadData:[module_num:1|svn_version:'Unknown'|variable_revision_number:6|show_window:True|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
-    Input data file location:Elsewhere...|METADATA_DIR
-    Name of the file:METADATA_CSV_FILE
+    Input data file location:Elsewhere...|.
+    Name of the file:metadata.csv
     Load images based on this data?:Yes
     Base image location:Elsewhere...|
     Process just a range of rows?:No
@@ -167,8 +167,8 @@ UntangleWorms:[module_num:10|svn_version:'Unknown'|variable_revision_number:2|sh
     Overlap style:Both
     Name the output overlapping worm objects:dauerMod_OverlappingWorms
     Name the output non-overlapping worm objects:dauerMod_NonOverlappingWorms
-    Training set file location:Elsewhere...|WORM_MODEL_DIR
-    Training set file name:MODEL1_XML_FILE
+    Training set file location:Elsewhere...|input_data/worm_models
+    Training set file name:dauerMod.xml
     Use training set weights?:Yes
     Overlap weight:5.0
     Leftover weight:10.0
@@ -199,8 +199,8 @@ UntangleWorms:[module_num:11|svn_version:'Unknown'|variable_revision_number:2|sh
     Overlap style:Both
     Name the output overlapping worm objects:nondauerMod_OverlappingWorms
     Name the output non-overlapping worm objects:nondauerMod_NonOverlappingWorms
-    Training set file location:Elsewhere...|WORM_MODEL_DIR
-    Training set file name:MODEL2_XML_FILE
+    Training set file location:Elsewhere...|input_data/worm_models
+    Training set file name:nondauerMod.xml
     Use training set weights?:Yes
     Overlap weight:5.0
     Leftover weight:10.0
@@ -230,8 +230,8 @@ StraightenWorms:[module_num:12|svn_version:'Unknown'|variable_revision_number:3|
     Select the input untangled worm objects:dauerMod_NonOverlappingWorms
     Name the output straightened worm objects:dauerMod_StraightenedWorms
     Worm width:20
-    Training set file location:Elsewhere...|WORM_MODEL_DIR
-    Training set file name:MODEL1_XML_FILE
+    Training set file location:Elsewhere...|input_data/worm_models
+    Training set file name:dauerMod.xml
     Image count:1
     Measure intensity distribution?:Yes
     Number of transverse segments:1
@@ -245,8 +245,8 @@ StraightenWorms:[module_num:13|svn_version:'Unknown'|variable_revision_number:3|
     Select the input untangled worm objects:nondauerMod_NonOverlappingWorms
     Name the output straightened worm objects:nondauerMod_StraightenedWorms
     Worm width:20
-    Training set file location:Elsewhere...|WORM_MODEL_DIR
-    Training set file name:MODEL2_XML_FILE
+    Training set file location:Elsewhere...|input_data/worm_models
+    Training set file name:nondauerMod.xml
     Image count:1
     Measure intensity distribution?:Yes
     Number of transverse segments:1
diff --git a/input_data/CP_pipelines/toxin-nf.cppipe b/input_data/CP_pipelines/toxin-nf.cppipe
old mode 100644
new mode 100755
index 070fb30..7e580b7
--- a/input_data/CP_pipelines/toxin-nf.cppipe
+++ b/input_data/CP_pipelines/toxin-nf.cppipe
@@ -6,8 +6,8 @@ ModuleCount:22
 HasImagePlaneDetails:False
 
 LoadData:[module_num:1|svn_version:'Unknown'|variable_revision_number:6|show_window:False|notes:[]|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False]
-    Input data file location:Elsewhere...|METADATA_DIR
-    Name of the file:METADATA_CSV_FILE
+    Input data file location:Elsewhere...|.
+    Name of the file:metadata.csv
     Load images based on this data?:Yes
     Base image location:Default Input Folder|
     Process just a range of rows?:No
@@ -159,8 +159,8 @@ UntangleWorms:[module_num:9|svn_version:'Unknown'|variable_revision_number:2|sho
     Overlap style:Both
     Name the output overlapping worm objects:L4_N2_HB101_100w_OverlappingWorms
     Name the output non-overlapping worm objects:L4_N2_HB101_100w_NonOverlappingWorms
-    Training set file location:Elsewhere...|WORM_MODEL_DIR
-    Training set file name:MODEL1_XML_FILE
+    Training set file location:Elsewhere...|input_data/worm_models
+    Training set file name:L4_N2_HB101_100w.xml
     Use training set weights?:Yes
     Overlap weight:5.0
     Leftover weight:10.0
@@ -191,8 +191,8 @@ UntangleWorms:[module_num:10|svn_version:'Unknown'|variable_revision_number:2|sh
     Overlap style:Both
     Name the output overlapping worm objects:L2L3_N2_HB101_100w_OverlappingWorms
     Name the output non-overlapping worm objects:L2L3_N2_HB101_100w_NonOverlappingWorms
-    Training set file location:Elsewhere...|WORM_MODEL_DIR
-    Training set file name:MODEL2_XML_FILE
+    Training set file location:Elsewhere...|input_data/worm_models
+    Training set file name:L2L3_N2_HB101_100w.xml
     Use training set weights?:Yes
     Overlap weight:5.0
     Leftover weight:10.0
@@ -223,8 +223,8 @@ UntangleWorms:[module_num:11|svn_version:'Unknown'|variable_revision_number:2|sh
     Overlap style:Both
     Name the output overlapping worm objects:L1_N2_HB101_100w_OverlappingWorms
     Name the output non-overlapping worm objects:L1_N2_HB101_100w_NonOverlappingWorms
-    Training set file location:Elsewhere...|WORM_MODEL_DIR
-    Training set file name:MODEL3_XML_FILE
+    Training set file location:Elsewhere...|input_data/worm_models
+    Training set file name:L1_N2_HB101_100w.xml
     Use training set weights?:Yes
     Overlap weight:5.0
     Leftover weight:10.0
@@ -255,8 +255,8 @@ UntangleWorms:[module_num:12|svn_version:'Unknown'|variable_revision_number:2|sh
     Overlap style:Both
     Name the output overlapping worm objects:MDHD_OverlappingWorms
     Name the output non-overlapping worm objects:MDHD_NonOverlappingWorms
-    Training set file location:Elsewhere...|WORM_MODEL_DIR
-    Training set file name:MODEL4_XML_FILE
+    Training set file location:Elsewhere...|input_data/worm_models
+    Training set file name:MDHD.xml
     Use training set weights?:Yes
     Overlap weight:5.0
     Leftover weight:10.0
diff --git a/main.nf b/main.nf
index 6ad3fdc..ed08ab4 100644
--- a/main.nf
+++ b/main.nf
@@ -1,7 +1,7 @@
 #!/usr/bin/env nextflow
 
-// Use DSL2
-nextflow.preview.dsl=2
+// Using DSL-2
+nextflow.enable.dsl=2
 
 // QUEST nextflow version message
 if( !nextflow.version.matches('>20.0') ) {
@@ -10,63 +10,66 @@ if( !nextflow.version.matches('>20.0') ) {
     exit 1
 }
 
+// INCLUDE modules
+// include {
+//     dauer_workflow
+// } from './modules/dauerWorkflow.nf'
+// include {
+//     toxin_workflow
+// } from './modules/toxinWorkflow.nf'
+
 /*
 ~ ~ ~ > * PARAMETERS SETUP
 */
 
 // Variables
 date = new Date().format('yyyyMMdd')
-// model_name = "NonOverlappingWorms" // JUST FOR NOW
 
 // Setup pipeline parameter
 params.pipeline = null
-if("${params.pipeline}" == "dauer") {
-    pipe = "dauer-nf"
-    worm_model1 = "dauerMod.xml"
-    worm_model2 = "nondauerMod.xml"
-    model_name1 = "dauerMod_NonOverlappingWorms"
-    model_name2 = "nondauerMod_NonOverlappingWorms"
-} else if( "${params.pipeline}" == "toxin" ) {
-    pipe = "toxin-nf"
-    worm_model1 = "L4_N2_HB101_100w.xml"
-    worm_model2 = "L2L3_N2_HB101_100w.xml"
-    worm_model3 = "L1_N2_HB101_100w.xml"
-    worm_model4 = "MDHD.xml"
-    model_name1 = "L4_N2_HB101_100w_NonOverlappingWorms"
-    model_name2 = "L2L3_N2_HB101_100w_NonOverlappingWorms"
-    model_name3 = "L1_N2_HB101_100w_NonOverlappingWorms"
-    model_name4 = "MDHD_NonOverlappingWorms"
-} else if(!params.pipeline) {
+if(!params.pipeline) {
     println """
             Error: pipeline parameter not specified. Please enter --pipeline dauer or --pipeline toxin in command.
             """
             System.exit(1)
-} else if("${params.pipeline}" != "toxin" || "${params.pipeline}" != "dauer" ) {
+} else if(params.pipeline != "toxin" && params.pipeline != "dauer" ) {
     println """
             Error: pipeline (${params.pipeline}) does not match expected value. Please enter either dauer or toxin.
             """
             System.exit(1)
 }
 
-// Configure other parameters
+date = new Date().format('yyyyMMdd')
+
+// Help:
 params.help = null
-params.debug = null
+// project directory
 params.project = null
+// Groups to use
 params.groups = "plate,well"
+// directory with input data
 params.data_dir = "${workflow.projectDir}/input_data" // this is different for gcp
-params.bin_dir = "${workflow.projectDir}/bin" // this is different for gcp
-params.well_mask = "${params.data_dir}/well_masks/wellmask_98.png"
+// mask for the well
+params.well_mask = "input_data/well_masks/wellmask_98.png"
+// location to put output files
 params.out = "${params.project}/Analysis-${date}"
-params.raw_pipe_dir = "${params.data_dir}/CP_pipelines"
-params.raw_pipe = "${params.raw_pipe_dir}/${pipe}.cppipe"
-params.edited_pipe = "${params.out}/pipeline/pipeline.cppipe"
-params.metadata_dir = "${params.out}/metadata"
-params.metadata = "metadata.csv"
-params.worm_model_dir = "${params.data_dir}/worm_models"
 
-/*
-~ ~ ~ > * LOG AND HELP MESSAGE SETUP
-*/
+params.project_name = params.project.split("/").last()
+params.project_tag = "Analysis-${date}"
+
+params.container__general = "docker://andersenlab/nemascan:20220411181933701519"
+params.container__cellprofiler = "cellprofiler/cellprofiler:4.2.1"
+
+include {
+    listFiles
+    makeMetadata
+} from './modules/process_input.nf'
+include {
+    runCP
+} from './modules/cellprofiler.nf'
+include {
+    proc_CP_output
+} from './modules/process_output.nf'
 
 if (!params.help) {
 log.info '''
@@ -74,7 +77,8 @@ C E L L P R O F I L E R - N F   P I P E L I N E
 ===============================================
 '''
     log.info ""
-    log.info "Project           = ${params.project}"
+    log.info "Projcect          = ${params.project_name}"
+    log.info "Project Dir       = ${params.project}"
     log.info "CP pipeline       = ${params.pipeline}"
     log.info "Groups            = ${params.groups}"
     log.info "Output            = ${params.out}"
@@ -93,256 +97,37 @@ C E L L P R O F I L E R - N F   P I P E L I N E
     log.info "--pipeline                     The CP pipeline to use: toxin, dauer"
     log.info ""
     log.info "Optional arguments:"
-    log.info "--groups                       comma separated metadata groupings for CellProfiler, default is plate,well"
-    log.info "--outdir                       Output directory to place files, default is project/Analysis-{current date}"
+    log.info "--project_name                 A name for the project.  Default detects from the project directory."
+    log.info "--groups                       Comma separated metadata groupings for CellProfiler, default is plate,well"
+    log.info "--out                          Output directory to place files, default is project/Analysis-{current date}"
     log.info "--help                         This usage statement."
         exit 1
     }
 
-/*
-~ ~ ~ > * WORKFLOW
-*/
-
 workflow {
-    
-    if("${params.pipeline}" == "dauer") {
-    // configure inputs for CellProfiler ONLY FOR DAUER NOW NEED TO CHANGE MODELS IF OTHER
-    config_cp = Channel.fromPath("${params.raw_pipe}")
-        .combine(Channel.from("${params.metadata_dir}"))
-        .combine(Channel.from("${params.metadata}"))
-        .combine(Channel.from("${params.worm_model_dir}"))
-        .combine(Channel.from(worm_model1)) // edit here
-        .combine(Channel.from(worm_model2)) // edit here
-        .combine(Channel.fromPath("${params.bin_dir}/config_CP_input_dauer.R"))
-        .combine(Channel.from("${params.project}"))
-        .combine(Channel.from("${params.well_mask}"))
-        .combine(Channel.from("${params.groups}"))
-        .combine(Channel.from("${params.edited_pipe}"))
-        .combine(Channel.from("${params.out}")) | config_CP_input_dauer
-        //.view()
-
-     // Run CellProfiler
-    groups = config_CP_input_dauer.out.groups_file
-        .splitCsv(header:true, sep: "\t")
-        .map { row ->
-                [row.group, file("${row.pipeline}"), file("${row.output}")]
-            }
-        //.view()
-    
-    runCP(groups)
-    
-    // Preprocess CellProfiler output files
-    proc_cp = runCP.out.cp_output
-        .last() // This ensures that all items are emitted from runCP
-        .combine(Channel.from("${params.out}"))
-        .combine(Channel.from(model_name1)) // HARDCODE VARIABLE NOW MAKE DEPENDENT ON PROFILE
-        .combine(Channel.from(model_name2)) // HARDCODE VARIABLE NOW MAKE DEPENDENT ON PROFILE
-        .combine(Channel.fromPath("${params.bin_dir}/proc_CP_output_dauer.R"))
-        //.view()
-
-    proc_CP_output_dauer(proc_cp)
-    }
-
-    if("${params.pipeline}" == "toxin") {
-    // configure inputs for CellProfiler ONLY FOR DAUER NOW NEED TO CHANGE MODELS IF OTHER
-    config_cp = Channel.fromPath("${params.raw_pipe}")
-        .combine(Channel.from("${params.metadata_dir}"))
-        .combine(Channel.from("${params.metadata}"))
-        .combine(Channel.from("${params.worm_model_dir}"))
-        .combine(Channel.from(worm_model1)) // edit here
-        .combine(Channel.from(worm_model2)) // edit here
-        .combine(Channel.from(worm_model3)) // edit here
-        .combine(Channel.from(worm_model4)) // edit here
-        .combine(Channel.fromPath("${params.bin_dir}/config_CP_input_toxin.R"))
-        .combine(Channel.from("${params.project}"))
-        .combine(Channel.from("${params.well_mask}"))
-        .combine(Channel.from("${params.groups}"))
-        .combine(Channel.from("${params.edited_pipe}"))
-        .combine(Channel.from("${params.out}")) | config_CP_input_toxin
-        //.view()
-
-    // Run CellProfiler
-    groups = config_CP_input_toxin.out.groups_file
-        .splitCsv(header:true, sep: "\t")
-        .map { row ->
-                [row.group, file("${row.pipeline}"), file("${row.output}")]
-            }
-        //.view()
-    
-    runCP(groups)
-    
-    // Preprocess CellProfiler output files
-    proc_cp = runCP.out.cp_output
-        .last() // This ensures that all items are emitted from runCP
-        .combine(Channel.from("${params.out}"))
-        .combine(Channel.from(model_name1)) // HARDCODE VARIABLE NOW MAKE DEPENDENT ON PROFILE
-        .combine(Channel.from(model_name2)) // HARDCODE VARIABLE NOW MAKE DEPENDENT ON PROFILE
-        .combine(Channel.from(model_name3)) // HARDCODE VARIABLE NOW MAKE DEPENDENT ON PROFILE
-        .combine(Channel.from(model_name4)) // HARDCODE VARIABLE NOW MAKE DEPENDENT ON PROFILE
-        .combine(Channel.fromPath("${params.bin_dir}/proc_CP_output_toxin.R")) | proc_CP_output_toxin
-        //.view()
-    }
-}
-
-/*
-~ ~ ~ > * CONFIGURE FILES FOR CELLPROFILER
-*/
-
-process config_CP_input_dauer {
-    publishDir "${params.out}/pipeline", mode: 'copy', pattern: "*.cppipe"
-    publishDir "${params.out}/metadata", mode: 'copy', pattern: "metadata.csv"
-    publishDir "${params.out}/groups", mode: 'copy', pattern: "groups.tsv"
-
-    input:
-        tuple file(raw_pipe), val(meta_dir), val(meta), val(model_dir), val(model1), val(model2),
-        file(config_script), val(project), val(mask), val(group), val(edited_pipe), val(out)
-
-    output:
-        path "*.cppipe", emit: cp_pipeline_file
-        path "metadata.csv", emit: metadata_file
-        path "groups.tsv", emit: groups_file
-        
-
-    """
-        # Configure the raw pipeline for CellProfiler
-        awk '{gsub(/METADATA_DIR/,"${meta_dir}"); print}' ${raw_pipe} | \\
-        awk '{gsub(/METADATA_CSV_FILE/,"${meta}"); print}' | \\
-        awk '{gsub(/WORM_MODEL_DIR/,"${model_dir}"); print}' | \\
-        awk '{gsub(/MODEL1_XML_FILE/,"${model1}"); print}' | \\
-        awk '{gsub(/MODEL2_XML_FILE/,"${model2}"); print}' > pipeline.cppipe
-
-        # Configure metadata and groups for CellProfiller with config_CP_input.R
-        Rscript --vanilla ${config_script} ${project} ${mask} ${group} ${edited_pipe} ${out}
-
-    """
-}
-
-process config_CP_input_toxin {
-    publishDir "${params.out}/pipeline", mode: 'copy', pattern: "*.cppipe"
-    publishDir "${params.out}/metadata", mode: 'copy', pattern: "metadata.csv"
-    publishDir "${params.out}/groups", mode: 'copy', pattern: "groups.tsv"
-
-    input:
-        tuple file(raw_pipe), val(meta_dir), val(meta), val(model_dir), val(model1), val(model2), val(model3), val(model4),
-        file(config_script), val(project), val(mask), val(group), val(edited_pipe), val(out)
-
-    output:
-        path "*.cppipe", emit: cp_pipeline_file
-        path "metadata.csv", emit: metadata_file
-        path "groups.tsv", emit: groups_file
-        
-
-    """
-        # Configure the raw pipeline for CellProfiler
-        awk '{gsub(/METADATA_DIR/,"${meta_dir}"); print}' ${raw_pipe} | \\
-        awk '{gsub(/METADATA_CSV_FILE/,"${meta}"); print}' | \\
-        awk '{gsub(/WORM_MODEL_DIR/,"${model_dir}"); print}' | \\
-        awk '{gsub(/MODEL1_XML_FILE/,"${model1}"); print}' | \\
-        awk '{gsub(/MODEL2_XML_FILE/,"${model2}"); print}' | \\
-        awk '{gsub(/MODEL3_XML_FILE/,"${model3}"); print}' | \\
-        awk '{gsub(/MODEL4_XML_FILE/,"${model4}"); print}' > pipeline.cppipe
-
-        # Configure metadata and groups for CellProfiller with config_CP_input.R
-        Rscript --vanilla ${config_script} ${project} ${mask} ${group} ${edited_pipe} ${out}
-
-    """
-}
-
-/*
-~ ~ ~ > * RUN CELLPROFILER
-*/
-
-process runCP {
-
-    label "cellpro"
-
-    input:
-        tuple val(group), file(pipeline), file(output)
-
-    output:
-        stdout emit: cp_output //tuple file("*.csv"), file("*.png"), emit: cp_output
-
-    """
-        # Run cellprofiler headless
-        cellprofiler -c -r -p ${pipeline} \
-        -g ${group} \
-        -o ${output}
-
-    """
+    in_data_dir = Channel.fromPath("${params.project}")
+
+    listFiles(in_data_dir)
+    makeMetadata(listFiles.out)
+    groups = makeMetadata.out
+        .splitCsv(header: true)
+        .map {
+            row -> ["${row.Metadata_Group}", 
+                "input_data/CP_pipelines/${params.pipeline}-nf.cppipe"]
+        }
+    runCP_input = groups
+        .combine(in_data_dir)
+        .combine(
+            Channel.fromPath(
+                "${workflow.projectDir}/input_data"
+            )
+        )
+        .combine(makeMetadata.out)
+    runCP(runCP_input)
+    concat_outputs = runCP.out.output_files.toList()
+    proc_CP_output(concat_outputs)
 }
 
-/*
-~ ~ ~ > * PROCESS CELLPROFILER OUTPUTS
-*/
-
-process proc_CP_output_dauer {
-
-    //publishDir "${params.out}/processed_data", mode: 'copy', pattern: "*.RData"
-    
-    input:
-        tuple val(cp_output), val(out_dir), val(model_name1), val(model_name2), file(proc_CP_out_script)
-
-    output:
-        //path "*.RData", emit: cp_out_dat
-
-    """
-        # remove exisitng directories if present and make fresh
-        if [ -d ${out_dir}/processed_data ]; then rm -Rf ${out_dir}/processed_data; fi
-        mkdir ${out_dir}/processed_data
-        if [ -d ${out_dir}/processed_images ]; then rm -Rf ${out_dir}/processed_images; fi
-        mkdir ${out_dir}/processed_images
-        # find .csv files, concatenate them, and write new file
-        find ${out_dir}/CP_output -type f -name '${model_name1}.csv' -print0 | xargs -0 awk 'FNR>1 || NR==1 {print}' > ${out_dir}/processed_data/${model_name1}.csv
-        
-        # find .csv files, concatenate them, and write new file
-        find ${out_dir}/CP_output -type f -name '${model_name2}.csv' -print0 | xargs -0 awk 'FNR>1 || NR==1 {print}' > ${out_dir}/processed_data/${model_name2}.csv
-        
-        # move all the output images to process_images directory END WITH /?
-        find ${out_dir}/CP_output -name '*.png' -exec mv {} ${out_dir}/processed_images \\;
-        # Process the CellProfiler output with proc_CP_output.R
-        Rscript --vanilla ${proc_CP_out_script} ${out_dir}
-
-    """
-}
-
-process proc_CP_output_toxin {
-
-    //publishDir "${params.out}/processed_data", mode: 'copy', pattern: "*.RData"
-    
-    input:
-        tuple val(cp_output), val(out_dir), val(model_name1), val(model_name2),
-        val(model_name3), val(model_name4), file(proc_CP_out_script)
-
-    output:
-        //path "*.RData", emit: cp_out_dat
-
-    """
-        # remove exisitng directories if present and make fresh
-        if [ -d ${out_dir}/processed_data ]; then rm -Rf ${out_dir}/processed_data; fi
-        mkdir ${out_dir}/processed_data
-        if [ -d ${out_dir}/processed_images ]; then rm -Rf ${out_dir}/processed_images; fi
-        mkdir ${out_dir}/processed_images
-        # find .csv files, concatenate them, and write new file
-        find ${out_dir}/CP_output -type f -name '${model_name1}.csv' -print0 | xargs -0 awk 'FNR>1 || NR==1 {print}' > ${out_dir}/processed_data/${model_name1}.csv
-        
-        # find .csv files, concatenate them, and write new file
-        find ${out_dir}/CP_output -type f -name '${model_name2}.csv' -print0 | xargs -0 awk 'FNR>1 || NR==1 {print}' > ${out_dir}/processed_data/${model_name2}.csv
-        # find .csv files, concatenate them, and write new file
-        find ${out_dir}/CP_output -type f -name '${model_name3}.csv' -print0 | xargs -0 awk 'FNR>1 || NR==1 {print}' > ${out_dir}/processed_data/${model_name3}.csv
-        # find .csv files, concatenate them, and write new file
-        find ${out_dir}/CP_output -type f -name '${model_name4}.csv' -print0 | xargs -0 awk 'FNR>1 || NR==1 {print}' > ${out_dir}/processed_data/${model_name4}.csv
-        
-        # move all the output images to process_images directory END WITH /?
-        find ${out_dir}/CP_output -name '*.png' -exec mv {} ${out_dir}/processed_images \\;
-        # Process the CellProfiler output with proc_CP_output.R
-        Rscript --vanilla ${proc_CP_out_script} ${out_dir}
-
-    """
-}
-
-/*
-~ ~ ~ > * GENERATE REPORT
-*/
 workflow.onComplete {
 
     summary = """
@@ -357,7 +142,8 @@ workflow.onComplete {
     Git info: $workflow.repository - $workflow.revision [$workflow.commitId]
     { Parameters }
     ---------------------------
-    Project                                 = ${params.project}
+    Project                                 = ${params.project_name}
+    Project Dir                             = ${params.project}
     Pipeline Used                           = ${params.pipeline}
     Result Directory                        = ${params.out}
     """
diff --git a/modules/cellprofiler.nf b/modules/cellprofiler.nf
new file mode 100644
index 0000000..1f626ac
--- /dev/null
+++ b/modules/cellprofiler.nf
@@ -0,0 +1,28 @@
+#!/usr/bin/env nextflow
+
+// Using DSL-2
+nextflow.enable.dsl=2
+
+process runCP {
+    container "${params.container__cellprofiler}"
+    label "cellpro"
+
+    input:
+    tuple val(group), 
+        val(pipeline),
+        path(input_data),
+        path("input_data"),
+        path("metadata.csv")
+
+    output:
+        stdout emit: cp_output
+        path "${group}", emit: output_files
+    //tuple file("*.csv"), file("*.png"), emit: cp_output
+
+    // publishDir "${params.out}/${params.project}/Analysis-${date}", 
+    //     mode: 'copy', 
+    //     pattern: "CP_output/${group}"
+
+    script:
+    template 'runCP.sh'
+}
\ No newline at end of file
diff --git a/modules/process_input.nf b/modules/process_input.nf
new file mode 100644
index 0000000..350d57a
--- /dev/null
+++ b/modules/process_input.nf
@@ -0,0 +1,33 @@
+#!/usr/bin/env nextflow
+
+// Using DSL-2
+nextflow.enable.dsl=2
+
+process listFiles {
+    container "${params.container__general}"
+    input: 
+    path input_dir
+
+    output:
+    path "fileList.txt"
+
+    script:
+    template 'listFiles.sh'
+}
+
+process makeMetadata {
+    container "${params.container__general}"
+
+    input:
+    path in_fileList
+
+    output:
+    path "metadata.csv"
+
+    publishDir "${params.out}/metadata", 
+        mode: 'copy', 
+        pattern: "metadata.csv"
+
+    script:
+    template 'makeMetadata.sh'
+}
diff --git a/modules/process_output.nf b/modules/process_output.nf
new file mode 100644
index 0000000..971e506
--- /dev/null
+++ b/modules/process_output.nf
@@ -0,0 +1,22 @@
+#!/usr/bin/env nextflow
+
+// Using DSL-2
+nextflow.enable.dsl=2
+
+process proc_CP_output {
+    container "${params.container__general}"
+
+    publishDir "${params.out}", 
+        mode: 'copy', 
+        pattern: "processed_{data,images}"
+    
+    input:
+    path cp_output
+
+    output:
+        path "processed_data", emit: proc_dat
+        path "processed_images", emit: proc_img
+
+    script:
+    template "proc_output_${params.pipeline}.sh"
+}
\ No newline at end of file
diff --git a/nextflow.config b/nextflow.config
index 4f46da7..634a662 100644
--- a/nextflow.config
+++ b/nextflow.config
@@ -21,6 +21,7 @@ timeline {
 }
 
 executor {
+    name='slurm'
     queueSize = 5000
     submitRateLimit = 10
 }
@@ -29,22 +30,14 @@ singularity {
     pullTimeout = '45 min'
     enabled = true
     autoMounts = true
-    cacheDir = "/projects/b1059/singularity" // this is QUEST specific still
-    
 }
 
 process {
     executor = 'slurm'
-    queue = 'genomicsguestA'
-    clusterOptions = '-A b1042 -t 04:00:00 -e errlog.txt'
-    container = 'andersenlab/nemascan:20220407173056db3227' // still need to make cp docker img
     errorStrategy='retry'
     maxRetries=3
 
     withLabel: cellpro {
-        container = 'cellprofiler/cellprofiler:4.2.1'
-        queue = 'genomicsguestA'
-        clusterOptions = '-A b1042'
         memory = { 8.GB * task.attempt }
         time = { 15.min * task.attempt }
         errorStrategy='retry'
diff --git a/templates/listFiles.sh b/templates/listFiles.sh
new file mode 100644
index 0000000..b5eb3aa
--- /dev/null
+++ b/templates/listFiles.sh
@@ -0,0 +1,7 @@
+#!/bin/bash
+
+set -e
+set -o pipefail
+set -x
+
+ls -1 ${input_dir}/raw_images/* > fileList.txt
\ No newline at end of file
diff --git a/templates/makeMetadata.sh b/templates/makeMetadata.sh
new file mode 100644
index 0000000..7fe6758
--- /dev/null
+++ b/templates/makeMetadata.sh
@@ -0,0 +1,11 @@
+#!/bin/bash
+
+set -e
+set -o pipefail
+set -x
+
+makeMetadata_${params.pipeline}.R \\
+${in_fileList}  \\
+${params.well_mask} \\
+${params.groups}
+echo "done"
\ No newline at end of file
diff --git a/templates/proc_output_dauer.sh b/templates/proc_output_dauer.sh
new file mode 100644
index 0000000..808a383
--- /dev/null
+++ b/templates/proc_output_dauer.sh
@@ -0,0 +1,30 @@
+#!/bin/bash
+
+set -e
+set -o pipefail
+set -x
+
+# remove exisitng directories if present and make fresh
+mkdir processed_data
+
+
+# find .csv files, concatenate them, and write new file
+for model_name in dauerMod_NonOverlappingWorms nondauerMod_NonOverlappingWorms; do
+first_line=TRUE
+for fIter in \$(ls -1 */\${model_name}.csv); do
+if [ "\${first_line}" = "TRUE" ]; then 
+cat \${fIter} > processed_data/\${model_name}.csv
+else 
+tail -n +2 \${fIter} >> processed_data/\${model_name}.csv
+fi
+done
+done
+
+mkdir processed_images
+# move all the output images to process_images directory END WITH /?
+cp */*.png processed_images/
+
+# Process the CellProfiler output with proc_CP_output.R
+proc_CP_output.R \\
+${params.project_name} \\
+${params.project_tag}
\ No newline at end of file
diff --git a/templates/proc_output_toxin.sh b/templates/proc_output_toxin.sh
new file mode 100644
index 0000000..b4f7f43
--- /dev/null
+++ b/templates/proc_output_toxin.sh
@@ -0,0 +1,30 @@
+#!/bin/bash
+
+set -e
+set -o pipefail
+set -x
+
+# remove exisitng directories if present and make fresh
+mkdir processed_data
+
+# find .csv files, concatenate them, and write new file
+for model_name in L4_N2_HB101_100w_NonOverlappingWorms L2L3_N2_HB101_100w_NonOverlappingWorms L1_N2_HB101_100w_NonOverlappingWorms MDHD_NonOverlappingWorms; do
+first_line=TRUE
+for fIter in \$(ls -1 */\${model_name}.csv); do
+if [ "\${first_line}" = "TRUE" ]; then 
+cat \${fIter} > processed_data/\${model_name}.csv
+else 
+tail -n +2 \${fIter} >> processed_data/\${model_name}.csv
+fi
+done
+done
+
+mkdir processed_images
+
+# move all the output images to process_images directory END WITH /?
+cp */*.png processed_images/
+
+# Process the CellProfiler output with proc_CP_output.R
+proc_CP_output.R \\
+${params.project_name} \\
+${params.project_tag}
\ No newline at end of file
diff --git a/templates/runCP.sh b/templates/runCP.sh
new file mode 100644
index 0000000..bb73e03
--- /dev/null
+++ b/templates/runCP.sh
@@ -0,0 +1,22 @@
+#!/bin/bash
+
+set -e
+set -o pipefail
+set -x
+
+pwd
+ls -lh
+
+chmod a+x ${pipeline}
+export MPLCONFIGDIR=cellProfiler_tmp
+
+mkdir cellProfiler_tmp
+mkdir -p ${group}
+
+# Run cellprofiler headless
+cellprofiler -c -r \\
+-i \$(pwd) \\
+-p ${pipeline} \\
+-g Metadata_Group=${group} \\
+-o ${group} \\
+-t cellProfiler_tmp
\ No newline at end of file