# HG changeset patch
# User mingchen0919
# Date 1502210111 14400
# Node ID 2f4df2be05724ecd22c32a02d3e430eec10dfe46
# Parent 0ac073bef19d2a32d490940065fc02c34260e690
planemo upload for repository https://github.com/statonlab/docker-GRReport/tree/master/my_tools/rmarkdown_wgcna commit d91f269e8bc09a488ed2e005122bbb4a521f44a0-dirty
diff -r 0ac073bef19d -r 2f4df2be0572 01_evaluation_overview.Rmd
--- a/01_evaluation_overview.Rmd Tue Aug 08 11:45:41 2017 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,123 +0,0 @@
----
-title: "Evaluation Overview"
-output: html_document
----
-
-```{r setup, include=FALSE, warning=FALSE, message=FALSE}
-knitr::opts_chunk$set(echo = ECHO)
-```
-
-```{bash 'copy data from datasets directory to working directory', echo=FALSE}
-# Copy uploaded data to the working directory
-for f in $(echo READS | sed "s/,/ /g")
-do
- cp $f ./
-done
-```
-
-```{bash 'run fastqc', echo=FALSE}
-# run fastqc and place outputs into the report directory
-for r in $(ls *.dat)
-do
- fastqc -o REPORT_OUTPUT_DIR $r > /dev/null 2>&1
-done
-```
-
-```{bash 'parse fastqc results', echo=FALSE}
-##==== copy fastqc generated zip files from report output directory to job work directory ==
-cp -r REPORT_OUTPUT_DIR/*zip ./
-
-# create a file to store data file paths
-echo "sample_id,file_path" > PWF_file_paths.txt # Pass, Warning, Fail
-echo "sample_id,file_path" > PBQS_file_paths.txt # Per Base Quality Score
-echo "sample_id,file_path" > PSQS_file_paths.txt # Per Sequence Quality Score
-echo "sample_id,file_path" > PSGC_file_paths.txt # Per Sequence GC Content
-echo "sample_id,file_path" > PBSC_file_paths.txt # Per Base Sequence Content
-echo "sample_id,file_path" > PBNC_file_paths.txt # Per Base N Content
-echo "sample_id,file_path" > SDL_file_paths.txt # Sequence Duplication Level
-echo "sample_id,file_path" > SLD_file_paths.txt # Sequence Length Distribution
-echo "sample_id,file_path" > KMC_file_paths.txt # Kmer Content
-
-for i in $(ls *.zip)
-do
- BASE=$(echo $i | sed 's/\(.*\)\.zip/\1/g')
- echo $BASE
- unzip ${BASE}.zip > /dev/null 2>&1
-
- ##====== pass,warning,fail (WSF) =============
- awk '/^>>/ {print}' "$BASE"/fastqc_data.txt | grep -v 'END_MODULE' | sed 's/>>//' > "$BASE"-PWF.txt
- echo "${BASE},${BASE}-PWF.txt" >> PWF_file_paths.txt
-
- ##====== per base quality scores (PBQS) ======
- awk '/^>>Per base sequence quality/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-PBQS.txt
- echo "${BASE},${BASE}-PBQS.txt" >> PBQS_file_paths.txt
-
- ##====== per sequence quality scores (PSQS)
- awk '/^>>Per sequence quality scores/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-PSQS.txt
- echo "${BASE},${BASE}-PSQS.txt" >> PSQS_file_paths.txt
-
- ##====== Per sequence GC content (PSGC)
- awk '/^>>Per sequence GC content/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-PSGC.txt
- echo "${BASE},${BASE}-PSGC.txt" >> PSGC_file_paths.txt
-
- ##====== Per Base Sequence Content (PBSC)
- awk '/^>>Per base sequence content/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-PBSC.txt
- echo "${BASE},${BASE}-PBSC.txt" >> PBSC_file_paths.txt
-
- ##====== Per Base N Content (PBNC)
- awk '/^>>Per base N content/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-PBNC.txt
- echo "${BASE},${BASE}-PBNC.txt" >> PBNC_file_paths.txt
-
- ##====== Sequence Duplication Level (SDL)
- awk '/^>>Sequence Duplication Levels/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-SDL.txt
- echo "${BASE},${BASE}-SDL.txt" >> SDL_file_paths.txt
-
- ##====== Sequence Length Distribution (SLD)
- awk '/^>>Sequence Length Distribution/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-SLD.txt
- echo "${BASE},${BASE}-SLD.txt" >> SLD_file_paths.txt
-
- ##====== Kmer Content ============
- awk '/^>>Kmer Content/ {flag=1; next} /END_MODULE/ {flag=0} flag' "$BASE"/fastqc_data.txt >"$BASE"-KMC.txt
- echo "${BASE},${BASE}-KMC.txt" >> KMC_file_paths.txt
-
-done
-```
-
-
-## Evaluation Overview
-
-```{r 'overview'}
-PWF_file_paths = read.csv('PWF_file_paths.txt',
- header = TRUE, stringsAsFactors = FALSE)
-rm('PWF_df')
-for(i in 1:nrow(PWF_file_paths)) {
- file_path = PWF_file_paths[i,2]
- pwf_df = read.csv(file_path,
- sep='\t', header=FALSE, stringsAsFactors = FALSE)
- colnames(pwf_df) = c('item', PWF_file_paths[i,1])
- if (!exists('PWF_df')) {
- PWF_df = pwf_df
- } else {
- PWF_df = cbind(PWF_df, pwf_df[,2,drop=FALSE])
- }
-}
-```
-
-
-```{r}
-my_icon = c('ok', 'remove', 'star')
-names(my_icon) = c('pass', 'fail', 'warn')
-evaluate_list = list()
-for (i in colnames(PWF_df)[-1]) {
- evaluate_list[[i]] = formatter(
- "span",
- style = x ~ style("background-color" = ifelse(x =='pass', '#9CD027', ifelse(x == 'fail', '#CC0000', '#FF4E00')),
- "color" = "white",
- "width" = "50px",
- "float" = "left",
- "padding-right" = "5px")
- )
-}
-
-formattable(PWF_df, evaluate_list)
-```
\ No newline at end of file
diff -r 0ac073bef19d -r 2f4df2be0572 02_fastqc_original_reports.Rmd
--- a/02_fastqc_original_reports.Rmd Tue Aug 08 11:45:41 2017 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,20 +0,0 @@
----
-title: "FastQC original reports"
-output: html_document
----
-
-```{r 'FastQC original reports', include=FALSE, warning=FALSE, message=FALSE}
-knitr::opts_chunk$set(echo = ECHO)
-```
-
-
-Below are links to ***Fastqc*** original html reports.
-
-```{r 'html report links'}
-html_report_list = list()
-html_files = list.files('REPORT_OUTPUT_DIR', pattern = '.*html')
-for (i in html_files) {
- html_report_list[[i]] = tags$li(tags$a(href=i, i))
-}
-tags$ul(html_report_list)
-```
\ No newline at end of file
diff -r 0ac073bef19d -r 2f4df2be0572 1_per_base_quality_scores.Rmd
--- a/1_per_base_quality_scores.Rmd Tue Aug 08 11:45:41 2017 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,62 +0,0 @@
----
-title: "Per Base Quality Scores"
-output: html_document
----
-
-```{r setup, include=FALSE, warning=FALSE, message=FALSE}
-knitr::opts_chunk$set(echo = ECHO)
-```
-
-
-## Per Base Quality Scores
-
-```{r}
-PBQS_df = data.frame()
-PBQS_file_paths = read.csv('PBQS_file_paths.txt',
- header = TRUE, stringsAsFactors = FALSE)
-for(i in 1:nrow(PBQS_file_paths)) {
- # file_path = paste0('REPORT_OUTPUT_DIR/', PBQS_file_paths[i,2])
- file_path = PBQS_file_paths[i,2]
- pbqs_df = read.csv(file_path,
- sep='\t', header=TRUE, stringsAsFactors = FALSE) %>%
- mutate(Base1=as.numeric(str_split_fixed(X.Base, '-', 2)[,1]),
- Base2=as.numeric(str_split_fixed(X.Base, '-', 2)[,2])) %>%
- (function (df) {
- df1 = select(df, -Base2)
- df2 = select(df, -Base1) %>% filter(Base2 != '')
- colnames(df1) = c(colnames(df1)[1:7], 'Base')
- colnames(df2) = c(colnames(df2)[1:7], 'Base')
- res = rbind(df1, df2) %>% arrange(Base)
- return(res)
- })
- pbqs_df$sample_id = rep(PBQS_file_paths[i,1], nrow(pbqs_df))
- PBQS_df = rbind(PBQS_df, pbqs_df)
-}
-```
-
-
-```{r}
-# datatable(PBQS_df)
-max_phred = max(PBQS_df$Mean) + 10
-hchart(PBQS_df, "line", hcaes(x = Base, y = Mean, group = sample_id)) %>%
- hc_title(
- text = "Per Base Quality Score"
- ) %>%
- hc_yAxis(
- title = list(text = "Mean Base Quality Score"),
- min = 0,
- max = max_phred,
- plotLines = list(
- list(label = list(text = "Phred Score = 27"),
- width = 2,
- dashStyle = "dash",
- color = "green",
- value = 27),
- list(label = list(text = "Phred Score = 20"),
- width = 2,
- color = "red",
- value = 20)
- )
- ) %>%
- hc_exporting(enabled = TRUE)
-```
diff -r 0ac073bef19d -r 2f4df2be0572 2_per_base_N_content.Rmd
--- a/2_per_base_N_content.Rmd Tue Aug 08 11:45:41 2017 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,58 +0,0 @@
----
-title: "Per Base N Content"
-output: html_document
----
-
-```{r setup, include=FALSE, warning=FALSE, message=FALSE}
-knitr::opts_chunk$set(echo = ECHO)
-```
-
-## Per Base N Content
-
-```{r}
-PBNC_df = data.frame()
-PBNC_file_paths = read.csv('PBNC_file_paths.txt',
- header = TRUE, stringsAsFactors = FALSE)
-for(i in 1:nrow(PBNC_file_paths)) {
- # file_path = paste0('REPORT_OUTPUT_DIR/', PBNC_file_paths[i,2])
- file_path = PBNC_file_paths[i,2]
- pbnc_df = read.csv(file_path,
- sep='\t', header=TRUE, stringsAsFactors = FALSE) %>%
- mutate(Base1=as.numeric(str_split_fixed(X.Base, '-', 2)[,1]),
- Base2=as.numeric(str_split_fixed(X.Base, '-', 2)[,2])) %>%
- (function (df) {
- df1 = select(df, -Base2)
- df2 = select(df, -Base1) %>% filter(Base2 != '')
- colnames(df1) = c(colnames(df1)[1:2], 'Base')
- colnames(df2) = c(colnames(df2)[1:2], 'Base')
- res = rbind(df1, df2) %>% arrange(Base)
- return(res)
- })
- pbnc_df$sample_id = rep(PBNC_file_paths[i,1], nrow(pbnc_df))
- PBNC_df = rbind(PBNC_df, pbnc_df)
-}
-```
-
-
-```{r}
-PBNC_df$N.Count = PBNC_df$N.Count * 100
-max_phred = max(PBNC_df$N.Count) + 5
-hchart(PBNC_df, "line", hcaes(x = as.character(Base), y = N.Count, group = sample_id)) %>%
- hc_title(
- text = "Per Base N Content"
- ) %>%
- hc_xAxis(
- title = list(text = "Base Position")
- ) %>%
- hc_yAxis(
- title = list(text = "N %"),
- plotLines = list(
- list(label = list(text = "N = 5%"),
- width = 2,
- dashStyle = "dash",
- color = "red",
- value = 5)
- )
- ) %>%
- hc_exporting(enabled = TRUE)
-```
diff -r 0ac073bef19d -r 2f4df2be0572 3_per_sequence_quality_scores.Rmd
--- a/3_per_sequence_quality_scores.Rmd Tue Aug 08 11:45:41 2017 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,50 +0,0 @@
----
-title: "Per Sequence Quality Scores"
-output: html_document
----
-
-```{r setup, include=FALSE, warning=FALSE, message=FALSE}
-knitr::opts_chunk$set(echo = ECHO)
-```
-
-## Per Sequence Quality Scores
-
-```{r}
-PSQS_df = data.frame()
-PSQS_file_paths = read.csv('PSQS_file_paths.txt',
- header = TRUE, stringsAsFactors = FALSE)
-for(i in 1:nrow(PSQS_file_paths)) {
- # file_path = paste0('REPORT_OUTPUT_DIR/', PSQS_file_paths[i,2])
- file_path = PSQS_file_paths[i,2]
- psqs_df = read.csv(file_path,
- sep='\t', header=TRUE, stringsAsFactors = FALSE)
- psqs_df$sample_id = rep(PSQS_file_paths[i,1], nrow(psqs_df))
- PSQS_df = rbind(PSQS_df, psqs_df)
-}
-```
-
-
-```{r}
-max_phred = max(PSQS_df$X.Quality) + 5
-hchart(PSQS_df, "line", hcaes(x = X.Quality, y = Count, group = sample_id)) %>%
- hc_title(
- text = "Per Sequence Quality Score"
- ) %>%
- hc_xAxis(
- title = list(text = "Mean Sequence Quality Score"),
- min = 0,
- max = max_phred,
- plotLines = list(
- list(label = list(text = "Phred Score = 27"),
- width = 2,
- dashStyle = "dash",
- color = "green",
- value = 27),
- list(label = list(text = "Phred Score = 20"),
- width = 2,
- color = "red",
- value = 20)
- )
- ) %>%
- hc_exporting(enabled = TRUE)
-```
diff -r 0ac073bef19d -r 2f4df2be0572 4_per_sequence_GC_content.Rmd
--- a/4_per_sequence_GC_content.Rmd Tue Aug 08 11:45:41 2017 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,38 +0,0 @@
----
-title: "Per Sequence GC Content"
-output: html_document
----
-
-```{r setup, include=FALSE, warning=FALSE, message=FALSE}
-knitr::opts_chunk$set(echo = ECHO)
-```
-
-## Per Sequence GC Content
-
-
-```{r}
-PSGC_df = data.frame()
-PSGC_file_paths = read.csv('PSGC_file_paths.txt',
- header = TRUE, stringsAsFactors = FALSE)
-for(i in 1:nrow(PSGC_file_paths)) {
- # file_path = paste0('REPORT_OUTPUT_DIR/', PSGC_file_paths[i,2])
- file_path = PSGC_file_paths[i,2]
- psgc_df = read.csv(file_path,
- sep='\t', header=TRUE, stringsAsFactors = FALSE)
- psgc_df$sample_id = rep(PSGC_file_paths[i,1], nrow(psgc_df))
- PSGC_df = rbind(PSGC_df, psgc_df)
-}
-```
-
-
-```{r}
-max_phred = max(PSGC_df$Count) + 5
-hchart(PSGC_df, "line", hcaes(x = X.GC.Content, y = Count, group = sample_id)) %>%
- hc_title(
- text = "Per Sequence GC Content"
- ) %>%
- hc_xAxis(
- title = list(text = "% GC")
- ) %>%
- hc_exporting(enabled = TRUE)
-```
diff -r 0ac073bef19d -r 2f4df2be0572 5_per_base_sequence_content.Rmd
--- a/5_per_base_sequence_content.Rmd Tue Aug 08 11:45:41 2017 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,45 +0,0 @@
----
-title: "Per Base Sequence Content"
-output: html_document
----
-
-```{r setup, include=FALSE, warning=FALSE, message=FALSE}
-knitr::opts_chunk$set(echo = ECHO)
-```
-
-## Per Base Sequence Content
-
-```{r}
-PBSC_df = data.frame()
-PBSC_file_paths = read.csv('PBSC_file_paths.txt',
- header = TRUE, stringsAsFactors = FALSE)
-for(i in 1:nrow(PBSC_file_paths)) {
- # file_path = paste0('REPORT_OUTPUT_DIR/', PBSC_file_paths[i,2])
- file_path = PBSC_file_paths[i,2]
- pbsc_df = read.csv(file_path,
- sep='\t', header=TRUE, stringsAsFactors = FALSE) %>%
- mutate(Base1=as.numeric(str_split_fixed(X.Base, '-', 2)[,1]),
- Base2=as.numeric(str_split_fixed(X.Base, '-', 2)[,2])) %>%
- (function (df) {
- df1 = select(df, -Base2)
- df2 = select(df, -Base1) %>% filter(Base2 != '')
- colnames(df1) = c(colnames(df1)[1:5], 'Base')
- colnames(df2) = c(colnames(df2)[1:5], 'Base')
- res = rbind(df1, df2) %>% arrange(Base)
- return(res)
- })
- pbsc_df$sample_id = rep(PBSC_file_paths[i,1], nrow(pbsc_df))
- PBSC_df = rbind(PBSC_df, pbsc_df)
-}
-```
-
-
-```{r out.width="100%"}
-PBSC_df_2 = select(PBSC_df, -X.Base) %>%
- melt(id = c('Base', 'sample_id'), value.name = 'base_percentage')
-p = ggplot(data = PBSC_df_2, aes(x = Base, y = base_percentage, group = variable, color = variable)) +
- geom_line() +
- facet_wrap(~ sample_id)
-ggplotly(p)
-```
-
diff -r 0ac073bef19d -r 2f4df2be0572 _site.yml
--- a/_site.yml Tue Aug 08 11:45:41 2017 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,29 +0,0 @@
-name: "FastQC Website"
-output_dir: "my_site"
-navbar:
- title: "FastQC"
- type: inverse
- left:
- - text: "Home"
- icon: fa-home
- href: index.html
- - text: "Evaluation Overview"
- href: 01_evaluation_overview.html
- - text: "Evaluation Items"
- menu:
- - text: "Per Base Quality Scores"
- href: 1_per_base_quality_scores.html
- - text: "Per Base N Content"
- href: 2_per_base_N_content.html
- - text: "Per Sequence Quality Scores"
- href: 3_per_sequence_quality_scores.html
- - text: "Per Sequence GC Content"
- href: 4_per_sequence_GC_content.html
- - text: "Per Base Sequence Content"
- href: 5_per_base_sequence_content.html
- - text: "Original FastQC Reports"
- href: 02_fastqc_original_reports.html
-output:
- html_document:
- theme: cosmo
- highlight: textmate
\ No newline at end of file
diff -r 0ac073bef19d -r 2f4df2be0572 fastqc_site.xml
--- a/fastqc_site.xml Tue Aug 08 11:45:41 2017 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,124 +0,0 @@
-
-
- bioconductor-deseq2
- r-getopt
- r-rmarkdown
- r-plyr
- r-stringr
- r-highcharter
- r-dt
- r-reshape2
- r-plotly
- r-formattable
- r-htmltools
- fastqc
-
-
- Implements FastQC analysis and display results in R Markdown website.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
- @misc{bioinformatics2014fastqc,
- title={FastQC},
- author={Bioinformatics, Babraham},
- year={2014}
- }
-
-
- @article{allaire2016rmarkdown,
- title={rmarkdown: Dynamic Documents for R, 2016},
- author={Allaire, J and Cheng, Joe and Xie, Yihui and McPherson, Jonathan and Chang, Winston and Allen, Jeff and Wickham, Hadley and Atkins, Aron and Hyndman, Rob},
- journal={R package version 0.9},
- volume={6},
- year={2016}
- }
-
-
- @book{xie2015dynamic,
- title={Dynamic Documents with R and knitr},
- author={Xie, Yihui},
- volume={29},
- year={2015},
- publisher={CRC Press}
- }
-
-
- @misc{plotly2017,
- title = {plotly: Create Interactive Web Graphics via 'plotly.js'},
- author = {Carson Sievert and Chris Parmer and Toby Hocking and Scott Chamberlain and Karthik Ram and Marianne Corvellec and Pedro Despouy},
- year = {2017},
- note = {R package version 4.6.0},
- url = {https://CRAN.R-project.org/package=plotly},
- }
-
-
- @misc{highcharter2017,
- title = {highcharter: A Wrapper for the 'Highcharts' Library},
- author = {Joshua Kunst},
- year = {2017},
- note = {R package version 0.5.0},
- url = {https://CRAN.R-project.org/package=highcharter},
- }
-
-
- @misc{formattable2016,
- title = {formattable: Create 'Formattable' Data Structures},
- author = {Kun Ren and Kenton Russell},
- year = {2016},
- note = {R package version 0.2.0.1},
- url = {https://CRAN.R-project.org/package=formattable},
- }
-
-
-
\ No newline at end of file
diff -r 0ac073bef19d -r 2f4df2be0572 fastqc_site_render.R
--- a/fastqc_site_render.R Tue Aug 08 11:45:41 2017 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,195 +0,0 @@
-##======= Handle arguments from command line ========
-# setup R error handline to go to stderr
-options(show.error.messages=FALSE,
- error=function(){
- cat(geterrmessage(), file=stderr())
- quit("no", 1, F)
- })
-
-# we need that to not crash galaxy with an UTF8 error on German LC settings.
-loc = Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
-
-# suppress warning
-options(warn = -1)
-
-options(stringsAsFactors=FALSE, useFancyQuotes=FALSE)
-args = commandArgs(trailingOnly=TRUE)
-
-suppressPackageStartupMessages({
- library(getopt)
- library(tools)
-})
-
-# column 1: the long flag name
-# column 2: the short flag alias. A SINGLE character string
-# column 3: argument mask
-# 0: no argument
-# 1: argument required
-# 2: argument is optional
-# column 4: date type to which the flag's argument shall be cast.
-# possible values: logical, integer, double, complex, character.
-spec_list=list()
-
-##------- 1. input data ---------------------
-spec_list$READS = c('reads', 'r', '1', 'character')
-spec_list$ECHO = c('echo', 'e', '1', 'character')
-
-##--------2. output report and report site directory --------------
-spec_list$FASTQC_SITE = c('fastqc_site', 'o', '1', 'character')
-spec_list$FASTQC_SITE_DIR = c('fastqc_site_dir', 'd', '1', 'character')
-
-##--------3. Rmd templates sitting in the tool directory ----------
-
- ## _site.yml and index.Rmd files
- spec_list$SITE_YML = c('site_yml', 's', 1, 'character')
- spec_list$INDEX_Rmd = c('index_rmd', 'i', 1, 'character')
-
- ## other Rmd body template files
- spec_list$x01 = c('x01_evaluation_overview', 'p', '1', 'character')
- spec_list$x02 = c('x02_fastqc_original_reports', 'a', '1', 'character')
- spec_list$x1 = c('x1_per_base_quality_scores', 'b', '1', 'character')
- spec_list$x2 = c('x2_per_base_N_content', 'c', '1', 'character')
- spec_list$x3 = c('x3_per_sequence_quality_scores', 'f', '1', 'character')
- spec_list$x4 = c('x4_per_sequence_GC_content', 'g', '1', 'character')
- spec_list$x5 = c('x5_per_base_sequence_content', 'h', '1', 'character')
-
-##------------------------------------------------------------------
-
-spec = t(as.data.frame(spec_list))
-opt = getopt(spec)
-# arguments are accessed by long flag name (the first column in the spec matrix)
-# NOT by element name in the spec_list
-# example: opt$help, opt$expression_file
-##====== End of arguments handling ==========
-
-#------ Load libraries ---------
-library(rmarkdown)
-library(plyr)
-library(stringr)
-library(dplyr)
-library(highcharter)
-library(DT)
-library(reshape2)
-library(plotly)
-library(formattable)
-library(htmltools)
-
-
-#----- 1. create the report directory ------------------------
-paste0('mkdir -p ', opt$fastqc_site_dir) %>%
- system()
-
-#----- 2. generate Rmd files with Rmd templates --------------
-# a. templates without placeholder variables:
-# copy templates from tool directory to the working directory.
-# b. templates with placeholder variables:
-# substitute variables with user input values and place them in the working directory.
-
-
- #----- Copy index.Rmd and _site.yml files to job working direcotry -----
- file.copy(opt$index_rmd, 'index.Rmd', recursive=TRUE)
- file.copy(opt$site_yml, '_site.yml', recursive=TRUE)
- #---------------------------------------------------------
-
- #----- 01_evaluation_overview.Rmd -----------------------
- readLines(opt$x01_evaluation_overview) %>%
- (function(x) {
- gsub('ECHO', opt$echo, x)
- }) %>%
- (function(x) {
- gsub('READS', opt$reads, x)
- }) %>%
- (function(x) {
- gsub('REPORT_OUTPUT_DIR', opt$fastqc_site_dir, x)
- }) %>%
- (function(x) {
- fileConn = file('01_evaluation_overview.Rmd')
- writeLines(x, con=fileConn)
- close(fileConn)
- })
-
- #----- 1_per_base_quality_scores.Rmd --------------------
- readLines(opt$x1_per_base_quality_scores) %>%
- (function(x) {
- gsub('ECHO', opt$echo, x)
- }) %>%
- (function(x) {
- fileConn = file('1_per_base_quality_scores.Rmd')
- writeLines(x, con=fileConn)
- close(fileConn)
- })
-
- #----- 2_per_base_N_content.Rmd -------------------------
- readLines(opt$x2_per_base_N_content) %>%
- (function(x) {
- gsub('ECHO', opt$echo, x)
- }) %>%
- (function(x) {
- fileConn = file('2_per_base_N_content.Rmd')
- writeLines(x, con=fileConn)
- close(fileConn)
- })
-
- #----- 3_per_sequence_quality_scores.Rmd ----------------
- readLines(opt$x3_per_sequence_quality_scores) %>%
- (function(x) {
- gsub('ECHO', opt$echo, x)
- }) %>%
- (function(x) {
- fileConn = file('3_per_sequence_quality_scores.Rmd')
- writeLines(x, con=fileConn)
- close(fileConn)
- })
-
-
- #----- 4_per_sequence_GC_content.Rmd --------------------
- readLines(opt$x4_per_sequence_GC_content) %>%
- (function(x) {
- gsub('ECHO', opt$echo, x)
- }) %>%
- (function(x) {
- fileConn = file('4_per_sequence_GC_content.Rmd')
- writeLines(x, con=fileConn)
- close(fileConn)
- })
-
-
- #----- 5_per_base_sequence_content.Rmd ------------------
- readLines(opt$x5_per_base_sequence_content) %>%
- (function(x) {
- gsub('ECHO', opt$echo, x)
- }) %>%
- (function(x) {
- fileConn = file('5_per_base_sequence_content.Rmd')
- writeLines(x, con=fileConn)
- close(fileConn)
- })
-
- #----- 02_fastqc_original_reports.Rmd -------------------
- readLines(opt$x02_fastqc_original_reports) %>%
- (function(x) {
- gsub('ECHO', opt$echo, x)
- }) %>%
- (function(x) {
- gsub('REPORT_OUTPUT_DIR', opt$fastqc_site_dir, x)
- }) %>%
- (function(x) {
- fileConn = file('02_fastqc_original_reports.Rmd')
- writeLines(x, con=fileConn)
- close(fileConn)
- })
-
-
-
-#------ 3. render all Rmd files with render_site() --------
-render_site()
-
-
-#-------4. manipulate outputs -----------------------------
-# a. copy index.html to the report output path
-# b. copy all files in 'my_site' to the report output directory
-file.copy('my_site/index.html', opt$fastqc_site, recursive=TRUE)
-paste0('cp -r my_site/* ', opt$fastqc_site_dir) %>%
- system()
-
-
diff -r 0ac073bef19d -r 2f4df2be0572 index.Rmd
--- a/index.Rmd Tue Aug 08 11:45:41 2017 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,20 +0,0 @@
----
-title: "FastQC Report"
-output: html_document
----
-
-```{r setup, include=FALSE, warning=FALSE, message=FALSE}
-knitr::opts_chunk$set(echo = TRUE)
-```
-
-
-
-## References
-
-* Andrews, Simon. "FastQC: a quality control tool for high throughput sequence data." (2010): 175-176.
-* Goecks, Jeremy, Anton Nekrutenko, and James Taylor. "Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences." Genome biology 11.8 (2010): R86.
-* Afgan, Enis, et al. "The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update." Nucleic acids research (2016): gkw343.
-* Highcharts. https://www.highcharts.com/. (access by May 26, 2017).
-* R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
-* Joshua Kunst (2017). highcharter: A Wrapper for the 'Highcharts' Library. R package version 0.5.0. https://CRAN.R-project.org/package=highcharter
-* Carson Sievert, Chris Parmer, Toby Hocking, Scott Chamberlain, Karthik Ram, Marianne Corvellec and Pedro Despouy (2017). plotly: Create Interactive Web Graphics via 'plotly.js'. R package version 4.6.0. https://CRAN.R-project.org/package=plotly
diff -r 0ac073bef19d -r 2f4df2be0572 wgcna_construct_network.Rmd
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/wgcna_construct_network.Rmd Tue Aug 08 12:35:11 2017 -0400
@@ -0,0 +1,178 @@
+---
+title: 'WGCNA: construct network'
+output:
+ html_document:
+ number_sections: true
+ toc: true
+ theme: cosmo
+ highlight: tango
+---
+
+```{r setup, include=FALSE, warning=FALSE, message=FALSE}
+knitr::opts_chunk$set(
+ echo = ECHO
+)
+```
+
+# Import workspace
+
+This step imports workspace from the **WGCNA: preprocessing** step.
+
+```{r}
+fcp = file.copy("PREPROCESSING_WORKSPACE", "deseq.RData")
+load("deseq.RData")
+```
+
+
+# Processing outliers {.tabset}
+
+## Before removing outliers
+
+```{r}
+plot(sampleTree, main = "Sample clustering to detect outliers", sub="", xlab="", cex.lab = 1.5,
+ cex.axis = 1, cex.main = 1, cex = 0.5)
+if(!is.na(HEIGHT_CUT)) {
+ # plot a line to show the cut
+ abline(h = HEIGHT_CUT, col = "red")
+ # determine cluster under the line
+ clust = cutreeStatic(sampleTree, cutHeight = HEIGHT_CUT, minSize = 10)
+ keepSamples = (clust==1)
+ expression_data = expression_data[keepSamples, ]
+}
+```
+
+## After removing outliers
+
+```{r}
+sampleTree = hclust(dist(expression_data), method = "average");
+plot(sampleTree, main = "Sample clustering to detect outliers", sub="", xlab="",
+ cex.axis = 1, cex.main = 1, cex = 0.5)
+```
+
+
+# Trait data {.tabeset}
+
+If trait data is provided, the first 100 rows from the data will be displayed here. A plot consisting of sample cluster dendrogram and trait heatmap will also be gerenated.
+
+## Trait data table
+
+```{r}
+trait_data = data.frame()
+if ("TRAIT_DATA" != 'None') {
+ trait_data = read.csv("TRAIT_DATA", header = TRUE, row.names = 1)
+ # form a data frame analogous to expression data that will hold the traits.
+ sample_names = rownames(expression_data)
+ trait_rows = match(sample_names, rownames(trait_data))
+ trait_data = trait_data[trait_rows, ]
+ datatable(head(trait_data, 100), style="bootstrap", filter = 'top',
+ class="table-condensed", options = list(dom = 'tp', scrollX = TRUE))
+}
+```
+
+## Dendrogram and heatmap
+
+```{r fig.align='center', fig.width=8, fig.height=9}
+if (nrow(trait_data) != 0) {
+ traitColors = numbers2colors(trait_data, signed = FALSE)
+ plotDendroAndColors(sampleTree, traitColors,
+ groupLabels = names(trait_data),
+ main = "Sample dendrogram and trait heatmap",
+ cex.dendroLabels = 0.5)
+}
+```
+
+
+# The thresholding power
+
+```{r}
+powers = c(1:10, seq(12, 20, 2))
+soft_threshold = pickSoftThreshold(expression_data, powerVector = powers, verbose = 5)
+```
+
+```{r fig.align='center'}
+par(mfrow=c(1,2))
+plot(soft_threshold$fitIndices[,1], -sign(soft_threshold$fitIndices[,3])*soft_threshold$fitIndices[,2],
+ xlab="Soft Threshold (power)",
+ ylab="Scale Free Topology Model Fit,signed R^2",type="n",
+ main = paste("Scale independence"),
+ cex.lab = 0.5);
+text(soft_threshold$fitIndices[,1], -sign(soft_threshold$fitIndices[,3])*soft_threshold$fitIndices[,2],
+ labels=powers,cex=0.5,col="red");
+
+# calculate soft threshold power
+y = -sign(soft_threshold$fitIndices[,3])*soft_threshold$fitIndices[,2]
+r2_cutoff = 0.9
+for(i in 1:length(powers)) {
+ if(y[i] > r2_cutoff) {
+ soft_threshold_power = soft_threshold$fitIndices[,1][i]
+ r2_cutoff_new = y[i]
+ break
+ }
+ soft_threshold_power = soft_threshold$fitIndices[,1][length(powers)]
+}
+abline(h=r2_cutoff, col="red")
+abline(v=soft_threshold_power, col="blue")
+text(soft_threshold_power+1, r2_cutoff-0.1,
+ paste0('R^2 cutoff = ', round(r2_cutoff_new,2)),
+ cex = 0.5, col = "red")
+
+plot(soft_threshold$fitIndices[,1], soft_threshold$fitIndices[,5],
+ xlab="Soft Threshold (power)",ylab="Mean Connectivity", type="n",
+ main = paste("Mean connectivity"),
+ cex.lab = 0.5)
+text(soft_threshold$fitIndices[,1], soft_threshold$fitIndices[,5], labels=powers, cex=0.5,col="red")
+par(mfrow=c(1,1))
+```
+
+
+# Construct network
+
+The gene network is constructed based on **soft threshold power = `r soft_threshold_power`**
+
+```{r}
+gene_network = blockwiseModules(expression_data, power = soft_threshold_power,
+ TOMType = "unsigned", minModuleSize = 30,
+ reassignThreshold = 0, mergeCutHeight = 0.25,
+ numericLabels = TRUE, pamRespectsDendro = FALSE,
+ verbose = 3)
+```
+
+
+# Gene modules {.tabset}
+
+## Idenfity gene modules
+
+```{r}
+modules = table(gene_network$colors)
+n_modules = length(modules) - 1
+module_size_upper = modules[2]
+module_size_lower = modules[length(modules)]
+
+module_table = data.frame(model_label = c(0, 1:n_modules),
+ gene_size = as.vector(modules))
+datatable(t(module_table))
+```
+
+The results above indicates that there are **`r n_modules` gene modules**, labeled 1 through `r length(n_modules)` in order of descending size. The largest module has **`r module_size_upper` genes**, and the smallest module has **`r module_size_lower` genes**. The label 0 is reserved for genes outside of all modules.
+
+
+## Dendrogram and module plot
+
+```{r}
+# Convert labels to colors for plotting
+module_colors = labels2colors(gene_network$colors)
+# Plot the dendrogram and the module colors underneath
+plotDendroAndColors(gene_network$dendrograms[[1]], module_colors[gene_network$blockGenes[[1]]],
+ "Module colors",
+ dendroLabels = FALSE, hang = 0.03,
+ addGuide = TRUE, guideHang = 0.05)
+```
+
+
+```{r echo=FALSE}
+# save workspace
+rm("opt")
+save(list=ls(all.names = TRUE), file='CONSTRUCT_NETWORK_WORKSPACE')
+```
+
+
diff -r 0ac073bef19d -r 2f4df2be0572 wgcna_construct_network.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/wgcna_construct_network.xml Tue Aug 08 12:35:11 2017 -0400
@@ -0,0 +1,105 @@
+
+
+ r-getopt
+ r-rmarkdown
+ r-plyr
+ r-highcharter
+ r-dt
+ r-htmltools
+ r-wgcna
+
+
+ Construct gene network.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ @article{langfelder2008wgcna,
+ title={WGCNA: an R package for weighted correlation network analysis},
+ author={Langfelder, Peter and Horvath, Steve},
+ journal={BMC bioinformatics},
+ volume={9},
+ number={1},
+ pages={559},
+ year={2008},
+ publisher={BioMed Central}
+ }
+
+
+ @article{allaire2016rmarkdown,
+ title={rmarkdown: Dynamic Documents for R, 2016},
+ author={Allaire, J and Cheng, Joe and Xie, Yihui and McPherson, Jonathan and Chang, Winston and Allen, Jeff and Wickham, Hadley and Atkins, Aron and Hyndman, Rob},
+ journal={R package version 0.9},
+ volume={6},
+ year={2016}
+ }
+
+
+ @book{xie2015dynamic,
+ title={Dynamic Documents with R and knitr},
+ author={Xie, Yihui},
+ volume={29},
+ year={2015},
+ publisher={CRC Press}
+ }
+
+
+
\ No newline at end of file
diff -r 0ac073bef19d -r 2f4df2be0572 wgcna_construct_network_render.R
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/wgcna_construct_network_render.R Tue Aug 08 12:35:11 2017 -0400
@@ -0,0 +1,112 @@
+##======= Handle arguments from command line ========
+# setup R error handline to go to stderr
+options(show.error.messages=FALSE,
+ error=function(){
+ cat(geterrmessage(), file=stderr())
+ quit("no", 1, F)
+ })
+
+# we need that to not crash galaxy with an UTF8 error on German LC settings.
+loc = Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
+
+# suppress warning
+options(warn = -1)
+
+options(stringsAsFactors=FALSE, useFancyQuotes=FALSE)
+args = commandArgs(trailingOnly=TRUE)
+
+suppressPackageStartupMessages({
+ library(getopt)
+ library(tools)
+})
+
+# column 1: the long flag name
+# column 2: the short flag alias. A SINGLE character string
+# column 3: argument mask
+# 0: no argument
+# 1: argument required
+# 2: argument is optional
+# column 4: date type to which the flag's argument shall be cast.
+# possible values: logical, integer, double, complex, character.
+spec_list=list()
+
+##------- 1. input data ---------------------
+spec_list$ECHO = c('echo', 'e', '1', 'character')
+spec_list$PREPROCESSING_WORKSPACE = c('preprocessing_workspace', 'w', '1', 'character')
+spec_list$HEIGHT_CUT = c('height_cut', 'h', '2', 'double')
+spec_list$TRAIT_DATA = c('trait_data', 't', '2', 'character')
+
+
+##--------2. output report and report site directory --------------
+spec_list$OUTPUT_HTML = c('wgcna_construct_network_html', 'o', '1', 'character')
+spec_list$OUTPUT_DIR = c('wgcna_construct_network_dir', 'd', '1', 'character')
+spec_list$CONSTRUCT_NETWORK_WORKSPACE = c('construct_network_workspace', 'W', '1', 'character')
+
+
+##--------3. Rmd templates in the tool directory ----------
+
+spec_list$WGCNA_PREPROCESSING_RMD = c('wgcna_construct_network_rmd', 'M', '1', 'character')
+
+
+
+##------------------------------------------------------------------
+
+spec = t(as.data.frame(spec_list))
+opt = getopt(spec)
+# arguments are accessed by long flag name (the first column in the spec matrix)
+# NOT by element name in the spec_list
+# example: opt$help, opt$expression_file
+##====== End of arguments handling ==========
+
+#------ Load libraries ---------
+library(rmarkdown)
+library(WGCNA)
+library(DT)
+library(htmltools)
+library(ggplot2)
+
+
+#----- 1. create the report directory ------------------------
+system(paste0('mkdir -p ', opt$wgcna_construct_network_dir))
+
+
+#----- 2. generate Rmd files with Rmd templates --------------
+# a. templates without placeholder variables:
+# copy templates from tool directory to the working directory.
+# b. templates with placeholder variables:
+# substitute variables with user input values and place them in the working directory.
+
+
+#----- 01 wgcna_construct_network.Rmd -----------------------
+readLines(opt$wgcna_construct_network_rmd) %>%
+ (function(x) {
+ gsub('ECHO', opt$echo, x)
+ }) %>%
+ (function(x) {
+ gsub('PREPROCESSING_WORKSPACE', opt$preprocessing_workspace, x)
+ }) %>%
+ (function(x) {
+ gsub('HEIGHT_CUT', opt$height_cut, x)
+ }) %>%
+ (function(x) {
+ gsub('TRAIT_DATA', opt$trait_data, x)
+ }) %>%
+ (function(x) {
+ gsub('OUTPUT_DIR', opt$wgcna_construct_network_dir, x)
+ }) %>%
+ (function(x) {
+ gsub('CONSTRUCT_NETWORK_WORKSPACE', opt$construct_network_workspace, x)
+ }) %>%
+ (function(x) {
+ fileConn = file('wgcna_construct_network.Rmd')
+ writeLines(x, con=fileConn)
+ close(fileConn)
+ })
+
+
+#------ 3. render all Rmd files --------
+render('wgcna_construct_network.Rmd', output_file = opt$wgcna_construct_network_html)
+
+#-------4. manipulate outputs -----------------------------
+
+
diff -r 0ac073bef19d -r 2f4df2be0572 wgcna_eigengene_visualization.Rmd
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/wgcna_eigengene_visualization.Rmd Tue Aug 08 12:35:11 2017 -0400
@@ -0,0 +1,121 @@
+---
+title: 'WGCNA: eigengene visualization'
+output:
+ html_document:
+ number_sections: true
+ toc: true
+ theme: cosmo
+ highlight: tango
+---
+
+```{r setup, include=FALSE, warning=FALSE, message=FALSE}
+knitr::opts_chunk$set(
+ echo = ECHO
+)
+```
+
+# Import workspace
+
+This step imports workspace from the **WGCNA: construct network** step.
+
+```{r}
+fcp = file.copy("CONSTRUCT_NETWORK_WORKSPACE", "deseq.RData")
+load("deseq.RData")
+```
+
+
+# Gene modules {.tabset}
+
+```{r}
+if(!is.na(SOFT_THRESHOLD_POWER)) soft_threshold_power = SOFT_THRESHOLD_POWER
+```
+
+## Identify gene modules
+
+The gene network is constructed based on **soft threshold power = `r soft_threshold_power`**
+
+```{r}
+gene_network = blockwiseModules(expression_data, power = soft_threshold_power,
+ TOMType = "unsigned", minModuleSize = 30,
+ reassignThreshold = 0, mergeCutHeight = 0.25,
+ numericLabels = TRUE, pamRespectsDendro = FALSE,
+ verbose = 3)
+```
+
+
+```{r}
+modules = table(gene_network$colors)
+n_modules = length(modules) - 1
+module_size_upper = modules[2]
+module_size_lower = modules[length(modules)]
+
+module_table = data.frame(model_label = c(0, 1:n_modules),
+ gene_size = as.vector(modules))
+datatable(t(module_table))
+```
+
+The results above indicates that there are **`r n_modules` gene modules**, labeled 1 through `r length(n_modules)` in order of descending size. The largest module has **`r module_size_upper` genes**, and the smallest module has **`r module_size_lower` genes**. The label 0 is reserved for genes outside of all modules.
+
+
+## Dendrogram and module plot
+
+```{r}
+# Convert labels to colors for plotting
+module_colors = labels2colors(gene_network$colors)
+# Plot the dendrogram and the module colors underneath
+plotDendroAndColors(gene_network$dendrograms[[1]], module_colors[gene_network$blockGenes[[1]]],
+ "Module colors",
+ dendroLabels = FALSE, hang = 0.03,
+ addGuide = TRUE, guideHang = 0.05)
+```
+
+
+# Gene module correlation
+
+We can calculate eigengenes and use them as representative profiles to quantify similarity of found gene modules.
+
+```{r}
+n_genes = ncol(expression_data)
+n_samples = nrow(expression_data)
+```
+
+```{r}
+diss_tom = 1-TOMsimilarityFromExpr(expression_data, power = soft_threshold_power)
+set.seed(123)
+select_genes = sample(n_genes, size = PLOT_GENES)
+select_diss_tom = diss_tom[select_genes, select_genes]
+
+# calculate gene tree on selected genes
+select_gene_tree = hclust(as.dist(select_diss_tom), method = 'average')
+select_module_colors = module_colors[select_genes]
+
+# transform diss_tom with a power to make moderately strong connections more visiable in the heatmap.
+plot_diss_tom = select_diss_tom^7
+# set diagonal to NA for a nicer plot
+diag(plot_diss_tom) = NA
+```
+
+
+```{r fig.align='center'}
+TOMplot(plot_diss_tom, select_gene_tree, select_module_colors, main = "Network heatmap")
+```
+
+
+# Eigengene visualization {.tabset}
+
+## Eigengene dendrogram
+
+```{r fig.align='center'}
+module_eigengenes = moduleEigengenes(expression_data, module_colors)$eigengenes
+plotEigengeneNetworks(module_eigengenes, "Eigengene dendrogram",
+ plotHeatmaps = FALSE)
+```
+
+## Eigengene adjacency heatmap
+
+```{r fig.align='center'}
+plotEigengeneNetworks(module_eigengenes, "Eigengene adjacency heatmap",
+ marHeatmap = c(2, 3, 2, 2),
+ plotDendrograms = FALSE, xLabelsAngle = 90)
+```
+
diff -r 0ac073bef19d -r 2f4df2be0572 wgcna_eigengene_visualization.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/wgcna_eigengene_visualization.xml Tue Aug 08 12:35:11 2017 -0400
@@ -0,0 +1,100 @@
+
+
+ r-getopt
+ r-rmarkdown
+ r-plyr
+ r-highcharter
+ r-dt
+ r-htmltools
+ r-wgcna
+
+
+ Eigengene visualization.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ @article{langfelder2008wgcna,
+ title={WGCNA: an R package for weighted correlation network analysis},
+ author={Langfelder, Peter and Horvath, Steve},
+ journal={BMC bioinformatics},
+ volume={9},
+ number={1},
+ pages={559},
+ year={2008},
+ publisher={BioMed Central}
+ }
+
+
+ @article{allaire2016rmarkdown,
+ title={rmarkdown: Dynamic Documents for R, 2016},
+ author={Allaire, J and Cheng, Joe and Xie, Yihui and McPherson, Jonathan and Chang, Winston and Allen, Jeff and Wickham, Hadley and Atkins, Aron and Hyndman, Rob},
+ journal={R package version 0.9},
+ volume={6},
+ year={2016}
+ }
+
+
+ @book{xie2015dynamic,
+ title={Dynamic Documents with R and knitr},
+ author={Xie, Yihui},
+ volume={29},
+ year={2015},
+ publisher={CRC Press}
+ }
+
+
+
\ No newline at end of file
diff -r 0ac073bef19d -r 2f4df2be0572 wgcna_eigengene_visualization_render.R
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/wgcna_eigengene_visualization_render.R Tue Aug 08 12:35:11 2017 -0400
@@ -0,0 +1,109 @@
+##======= Handle arguments from command line ========
+# setup R error handline to go to stderr
+options(show.error.messages=FALSE,
+ error=function(){
+ cat(geterrmessage(), file=stderr())
+ quit("no", 1, F)
+ })
+
+# we need that to not crash galaxy with an UTF8 error on German LC settings.
+loc = Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
+
+# suppress warning
+options(warn = -1)
+
+options(stringsAsFactors=FALSE, useFancyQuotes=FALSE)
+args = commandArgs(trailingOnly=TRUE)
+
+suppressPackageStartupMessages({
+ library(getopt)
+ library(tools)
+})
+
+# column 1: the long flag name
+# column 2: the short flag alias. A SINGLE character string
+# column 3: argument mask
+# 0: no argument
+# 1: argument required
+# 2: argument is optional
+# column 4: date type to which the flag's argument shall be cast.
+# possible values: logical, integer, double, complex, character.
+spec_list=list()
+
+##------- 1. input data ---------------------
+spec_list$ECHO = c('echo', 'e', '1', 'character')
+spec_list$CONSTRUCT_NETWORK_WORKSPACE = c('construct_network_workspace', 'w', '1', 'character')
+spec_list$SOFT_THRESHOLD_POWER = c('soft_threshold_power', 'p', '2', 'double')
+spec_list$PLOT_GENES = c('plot_genes', 'n', '1', 'integer')
+
+
+##--------2. output report and report site directory --------------
+spec_list$OUTPUT_HTML = c('wgcna_eigengene_visualization_html', 'o', '1', 'character')
+spec_list$OUTPUT_DIR = c('wgcna_eigengene_visualization_dir', 'd', '1', 'character')
+
+
+
+##--------3. Rmd templates in the tool directory ----------
+
+spec_list$WGCNA_EIGENGENE_VISUALIZATION_RMD = c('wgcna_eigengene_visualization_rmd', 'M', '1', 'character')
+
+
+
+##------------------------------------------------------------------
+
+spec = t(as.data.frame(spec_list))
+opt = getopt(spec)
+# arguments are accessed by long flag name (the first column in the spec matrix)
+# NOT by element name in the spec_list
+# example: opt$help, opt$expression_file
+##====== End of arguments handling ==========
+
+#------ Load libraries ---------
+library(rmarkdown)
+library(WGCNA)
+library(DT)
+library(htmltools)
+library(ggplot2)
+
+
+#----- 1. create the report directory ------------------------
+system(paste0('mkdir -p ', opt$wgcna_eigengene_visualization_dir))
+
+
+#----- 2. generate Rmd files with Rmd templates --------------
+# a. templates without placeholder variables:
+# copy templates from tool directory to the working directory.
+# b. templates with placeholder variables:
+# substitute variables with user input values and place them in the working directory.
+
+
+#----- 01 wgcna_eigengene_visualization.Rmd -----------------------
+readLines(opt$wgcna_eigengene_visualization_rmd) %>%
+ (function(x) {
+ gsub('ECHO', opt$echo, x)
+ }) %>%
+ (function(x) {
+ gsub('CONSTRUCT_NETWORK_WORKSPACE', opt$construct_network_workspace, x)
+ }) %>%
+ (function(x) {
+ gsub('SOFT_THRESHOLD_POWER', opt$soft_threshold_power, x)
+ }) %>%
+ (function(x) {
+ gsub('PLOT_GENES', opt$plot_genes, x)
+ }) %>%
+ (function(x) {
+ gsub('OUTPUT_DIR', opt$wgcna_eigengene_visualization_dir, x)
+ }) %>%
+ (function(x) {
+ fileConn = file('wgcna_eigengene_visualization.Rmd')
+ writeLines(x, con=fileConn)
+ close(fileConn)
+ })
+
+
+#------ 3. render all Rmd files --------
+render('wgcna_eigengene_visualization.Rmd', output_file = opt$wgcna_eigengene_visualization_html)
+
+#-------4. manipulate outputs -----------------------------
+
+
diff -r 0ac073bef19d -r 2f4df2be0572 wgcna_preprocessing.Rmd
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/wgcna_preprocessing.Rmd Tue Aug 08 12:35:11 2017 -0400
@@ -0,0 +1,76 @@
+---
+title: 'WGCNA: data preprocessing'
+output:
+ html_document:
+ number_sections: true
+ toc: true
+ theme: cosmo
+ highlight: tango
+---
+
+```{r setup, include=FALSE, warning=FALSE, message=FALSE}
+knitr::opts_chunk$set(
+ echo = ECHO
+)
+```
+
+```{r}
+str(opt)
+```
+
+# Import data
+
+Each row represents a gene and each column represents a sample.
+
+```{r}
+expression_data = read.csv('EXPRESSION_DATA', header = TRUE, row.names = 1)
+```
+
+Display the first 100 genes.
+
+```{r}
+datatable(head(expression_data, 100), style="bootstrap", filter = 'top',
+ class="table-condensed", options = list(dom = 'tp', scrollX = TRUE))
+```
+
+Transpose expression data matrix so that each row represents a sample and each column represents a gene.
+
+```{r}
+expression_data = as.data.frame(t(expression_data))
+```
+
+# Checking data
+
+Checking data for excessive missing values and identification of outlier microarray samples.
+
+```{r}
+gsg = goodSamplesGenes(expression_data, verbose = 3)
+if (!gsg$allOK) {
+ # Optionally, print the gene and sample names that were removed:
+ if (sum(!gsg$goodGenes)>0)
+ printFlush(paste("Removing genes:", paste(names(expression_data)[!gsg$goodGenes], collapse = ", ")));
+ if (sum(!gsg$goodSamples)>0)
+ printFlush(paste("Removing samples:", paste(rownames(expression_data)[!gsg$goodSamples], collapse = ", ")));
+ # Remove the offending genes and samples from the data:
+ expression_data = expression_data[gsg$goodSamples, gsg$goodGenes]
+} else {
+ print('all genes are OK!')
+}
+```
+
+# Clustering samples
+
+If there are any outliers, choose a height cut that will remove the offending sample. Remember this number since you will need this number in further analysis.
+
+```{r fig.align='center'}
+sampleTree = hclust(dist(expression_data), method = "average");
+plot(sampleTree, main = "Sample clustering to detect outliers", sub="", xlab="",
+ cex.axis = 1, cex.main = 1, cex = 0.5)
+```
+
+
+```{r echo=FALSE}
+rm("opt")
+save(list=ls(all.names = TRUE), file='PREPROCESSING_WORKSPACE')
+```
+
diff -r 0ac073bef19d -r 2f4df2be0572 wgcna_preprocessing.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/wgcna_preprocessing.xml Tue Aug 08 12:35:11 2017 -0400
@@ -0,0 +1,96 @@
+
+
+ r-getopt
+ r-rmarkdown
+ r-plyr
+ r-highcharter
+ r-dt
+ r-htmltools
+ r-wgcna
+
+
+ Data clearning and preprocessing.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ @article{langfelder2008wgcna,
+ title={WGCNA: an R package for weighted correlation network analysis},
+ author={Langfelder, Peter and Horvath, Steve},
+ journal={BMC bioinformatics},
+ volume={9},
+ number={1},
+ pages={559},
+ year={2008},
+ publisher={BioMed Central}
+ }
+
+
+ @article{allaire2016rmarkdown,
+ title={rmarkdown: Dynamic Documents for R, 2016},
+ author={Allaire, J and Cheng, Joe and Xie, Yihui and McPherson, Jonathan and Chang, Winston and Allen, Jeff and Wickham, Hadley and Atkins, Aron and Hyndman, Rob},
+ journal={R package version 0.9},
+ volume={6},
+ year={2016}
+ }
+
+
+ @book{xie2015dynamic,
+ title={Dynamic Documents with R and knitr},
+ author={Xie, Yihui},
+ volume={29},
+ year={2015},
+ publisher={CRC Press}
+ }
+
+
+
\ No newline at end of file
diff -r 0ac073bef19d -r 2f4df2be0572 wgcna_preprocessing_render.R
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/wgcna_preprocessing_render.R Tue Aug 08 12:35:11 2017 -0400
@@ -0,0 +1,102 @@
+##======= Handle arguments from command line ========
+# setup R error handline to go to stderr
+options(show.error.messages=FALSE,
+ error=function(){
+ cat(geterrmessage(), file=stderr())
+ quit("no", 1, F)
+ })
+
+# we need that to not crash galaxy with an UTF8 error on German LC settings.
+loc = Sys.setlocale("LC_MESSAGES", "en_US.UTF-8")
+
+# suppress warning
+options(warn = -1)
+
+options(stringsAsFactors=FALSE, useFancyQuotes=FALSE)
+args = commandArgs(trailingOnly=TRUE)
+
+suppressPackageStartupMessages({
+ library(getopt)
+ library(tools)
+})
+
+# column 1: the long flag name
+# column 2: the short flag alias. A SINGLE character string
+# column 3: argument mask
+# 0: no argument
+# 1: argument required
+# 2: argument is optional
+# column 4: date type to which the flag's argument shall be cast.
+# possible values: logical, integer, double, complex, character.
+spec_list=list()
+
+##------- 1. input data ---------------------
+spec_list$ECHO = c('echo', 'e', '1', 'character')
+spec_list$EXPRESSION_DATA = c('expression_data', 'E', '1', 'character')
+
+
+##--------2. output report and report site directory --------------
+spec_list$OUTPUT_HTML = c('wgcna_preprocessing_html', 'o', '1', 'character')
+spec_list$OUTPUT_DIR = c('wgcna_preprocessing_dir', 'd', '1', 'character')
+spec_list$PREPROCESSING_WORKSPACE = c('preprocessing_workspace', 'w', '1', 'character')
+
+##--------3. Rmd templates sitting in the tool directory ----------
+
+spec_list$WGCNA_PREPROCESSING_RMD = c('wgcna_preprocessing_rmd', 'D', '1', 'character')
+
+
+
+##------------------------------------------------------------------
+
+spec = t(as.data.frame(spec_list))
+opt = getopt(spec)
+# arguments are accessed by long flag name (the first column in the spec matrix)
+# NOT by element name in the spec_list
+# example: opt$help, opt$expression_file
+##====== End of arguments handling ==========
+
+#------ Load libraries ---------
+library(rmarkdown)
+library(WGCNA)
+library(DT)
+library(htmltools)
+
+
+#----- 1. create the report directory ------------------------
+system(paste0('mkdir -p ', opt$wgcna_preprocessing_dir))
+
+
+#----- 2. generate Rmd files with Rmd templates --------------
+# a. templates without placeholder variables:
+# copy templates from tool directory to the working directory.
+# b. templates with placeholder variables:
+# substitute variables with user input values and place them in the working directory.
+
+
+#----- 01 wgcna_preprocessing.Rmd -----------------------
+readLines(opt$wgcna_preprocessing_rmd) %>%
+ (function(x) {
+ gsub('ECHO', opt$echo, x)
+ }) %>%
+ (function(x) {
+ gsub('EXPRESSION_DATA', opt$expression_data, x)
+ }) %>%
+ (function(x) {
+ gsub('OUTPUT_DIR', opt$wgcna_preprocessing_dir, x)
+ }) %>%
+ (function(x) {
+ gsub('PREPROCESSING_WORKSPACE', opt$preprocessing_workspace, x)
+ }) %>%
+ (function(x) {
+ fileConn = file('wgcna_preprocessing.Rmd')
+ writeLines(x, con=fileConn)
+ close(fileConn)
+ })
+
+
+#------ 3. render all Rmd files --------
+render('wgcna_preprocessing.Rmd', output_file = opt$wgcna_preprocessing_html)
+
+#-------4. manipulate outputs -----------------------------
+
+