# HG changeset patch
# User kkonganti
# Date 1657658223 14400
# Node ID 2376aae1acabdeeddd4ed4a51ac198832d07112d
# Parent  ae89554cbe714d0d501bb9ff7009fc4759edc521
"planemo upload"

diff -r ae89554cbe71 -r 2376aae1acab cfsan_centriflaken.xml
--- a/cfsan_centriflaken.xml	Mon Jul 11 13:04:02 2022 -0400
+++ b/cfsan_centriflaken.xml	Tue Jul 12 16:37:03 2022 -0400
@@ -6,7 +6,7 @@
     </requirements>    
     <version_command>nextflow -version</version_command>
     <command detect_errors="exit_code"><![CDATA[
-	mkdir -p cpipes-input;
+	mkdir -p cpipes-input || exit 1;
 	#for $key in $input.keys()
 	    ln -sf '$input[$key]' './cpipes-input/$key';
 	#end for
@@ -114,9 +114,9 @@
 
 **Purpose**
 
-Centriflaken suite of automated data analysis pipelines are based on Nextflow DSL2 developed at CFSAN, FDA. These piepelines allow rapid 
+Centriflaken suite of automated data analysis pipelines are based on Nextflow DSL2 developed at CFSAN, FDA. These pipelines allow rapid 
 and effective construction of metagenomic assembled genomes (MAGs) to enable bacterial source-tracking. It is based on methods described in our 
-previous publication (https://doi.org/10.1371/journal.pone.0245172).
+previous publication ([Maguire *et al*, 2021](doi: https://doi.org/10.1371/journal.pone.0245172)).
 
 ----
 
@@ -127,7 +127,7 @@
 The CPIPES - Centriflaken Nextflow pipeline has been wrapped to make it work in Galaxy. It takes in either paired or unpaired short reads or long reads, generates MAGs and performs 
 in silico-based analysis (i.e., virulence gene finding). Additionally, AMR gene finding analysis is also included in Centriflaken and performed on MAGs 
 of interest. The final summary plots and tables can be downloaded from the provided MultiQC HTML report generated as part of the pipeline. 
-The Centriflaken pipeline was validated with data from our previously published method (Maguire et al, 2021) and was able to replicate the detection 
+The Centriflaken pipeline was validated with data from our previously published method ([Maguire *et al*, 2021](doi: https://doi.org/10.1371/journal.pone.0245172)) and was able to replicate the detection 
 and classification of STECs for each sample. We tested the pipeline with Nanopore data obtained from 21 additional enriched samples from 
 irrigation water and was able to perform the entire precision metagenomics analysis in less than 5 hours for all of them. All the original testing and validation was 
 done on the command line on the CFSAN Raven2 HPC Cluster.