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1 <?xml version="1.0"?>
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2 <tool_dependency>
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3 <package name="kwip" version="0.2.0">
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4 <install version="1.0">
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5 <actions_group>
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6 <actions architecture="x86_64" os="linux">
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7 <action type="download_by_url">https://github.com/kdmurray91/kWIP/releases/download/0.2.0/kwip-binaries_0.2.0.tar.gz</action>
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8 <action type="move_directory_files">
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9 <source_directory>.</source_directory>
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10 <destination_directory>$INSTALL_DIR</destination_directory>
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11 </action>
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12 </actions>
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13 <action type="set_environment">
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14 <environment_variable action="prepend_to" name="PATH">$INSTALL_DIR/bin</environment_variable>
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15 </action>
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16 </actions_group>
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17 </install>
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18 <readme>
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19 <![CDATA[
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20 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.
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21 ]]>
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22 </readme>
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23 </package>
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24 </tool_dependency>
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