# HG changeset patch
# User jowong
# Date 1542619194 18000
# Node ID 39519109479fd88e501c4e94e85b9faad2c47655

planemo upload

diff -r 000000000000 -r 39519109479f kwip.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/kwip.xml	Mon Nov 19 04:19:54 2018 -0500
@@ -0,0 +1,48 @@
+<tool id="kwip" name="kwip" version="1.1.0">
+    <description>Calculates CNV of genomic data based on template</description>
+    <requirements>
+        <requirement type="package" version="0.2.0">kwip</requirement>
+    </requirements>
+    <command detect_errors="exit_code"><![CDATA[
+        kwip -h
+    ]]></command>
+    <inputs>
+        <param type="data" name="input1" format="txt" />
+    </inputs>
+    <outputs>
+        <data name="output1" format="txt" />
+    </outputs>
+    <tests>
+        <test>
+            <param name="input1" value="prince_input.txt"/>
+            <output name="output1" file="prince_output.txt"/>
+        </test>
+    </tests>
+    <help><![CDATA[
+        usage: prince [-h] [-bo BOOST_OUTPUT] [-to TARGET_OUTPUT] [-tmp TEMPLATES] [-tf TARGET_FILE] [-bf BOOSTING_FILE] [-k K] [-cn COPYNUMBER]
+
+	Prince Options.
+
+	optional arguments:
+	  -h, --help            Show this help message and exit
+	  -bo, --boost_output   Output file for training data / training data used to predict copy numbers for queries
+          -to, --target_output  Output file for query copy number predictions
+          -tmp, --templates     VNTR templates. Default is for M.TB
+          -tf, --target_file    Target genome names in a text file
+          -bf, --boosting_file  Training genome file names in a text file
+          -k, --k               Kmer size used during read recruitment
+          -cn, --copynumber     Copy number used for training genome
+
+    ]]></help>
+    <citations>
+        <citation type="bibtex">
+@misc{githubPythonPRINCE,
+  author = {Booth, Julian},
+  year = {2018},
+  title = {PythonPRINCE},
+  publisher = {GitHub},
+  journal = {GitHub repository},
+  url = {https://github.com/WGS-TB/PythonPRINCE},
+}</citation>
+    </citations>
+</tool>
diff -r 000000000000 -r 39519109479f tool_dependencies.xml
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/tool_dependencies.xml	Mon Nov 19 04:19:54 2018 -0500
@@ -0,0 +1,24 @@
+<?xml version="1.0"?>
+<tool_dependency>
+    <package name="kwip" version="0.2.0">
+        <install version="1.0">
+            <actions_group>
+                <actions architecture="x86_64" os="linux">
+                    <action type="download_by_url">https://github.com/kdmurray91/kWIP/releases/download/0.2.0/kwip-binaries_0.2.0.tar.gz</action>
+                    <action type="move_directory_files">
+                        <source_directory>.</source_directory>
+                        <destination_directory>$INSTALL_DIR</destination_directory>
+                    </action>
+                </actions>
+                <action type="set_environment">
+                    <environment_variable action="prepend_to" name="PATH">$INSTALL_DIR/bin</environment_variable>
+                </action>
+            </actions_group>
+        </install>
+        <readme>
+<![CDATA[
+kWIP works by decomposing sequencing reads to short k-mers, hashing these k-mers and performing pairwise distance calculation between these sample k-mer hashes. We use khmer from the DIB lab, UC Davis to hash sequencing reads. KWIP calculates the distance between samples in a computationally efficient manner, and generates a distance matrix which may be used by downstream tools. The power of kWIP comes from the weighting applied across different hash values, which decreases the effect of erroneous, rare or over-abundant k-mers while focusing on k-mers which give the most insight into the similarity of samples.
+]]>
+        </readme>
+    </package>
+</tool_dependency>