<?xml version="1.0"?>
<tool id="xmfa2tbl" name="Convert XMFA to percent identity table" version="19.1.0.0">
	<description></description>
	<macros>
		<import>macros.xml</import>
		<import>cpt-macros.xml</import>
	</macros>
	<expand macro="requirements"/>
	<command detect_errors="aggressive"><![CDATA[
python $__tool_directory__/xmfa2tbl.py
$dice
@XMFA_INPUT@
@XMFA_FA_INPUT@

> $output
]]></command>
	<inputs>
		<expand macro="xmfa_input" />
		<expand macro="xmfa_fa_input" />
		<param type="boolean" label="use dice method in percent similarity calculation"
			truevalue="--dice" falsevalue="" name="dice" help="The dice method alters the total similarity calculation to reflect the length of both sequences. The default for this option is true."/>
	</inputs>
	<outputs>
		<data format="tabular" name="output" />
	</outputs>
	<tests>
		<test>
			<param name="xmfa" value="test.xmfa"/>
			<param name="sequences" value="test.fa" />
			<output name="output" file="xmfa2tbl_out.tsv"/>
		</test>
		<test>
			<param name="dice" value="true"/>
			<param name="xmfa" value="test.xmfa"/>
			<param name="sequences" value="test.fa" />
			<output name="output" file="xmfa2tbl_out_dice.tsv"/>
		</test>
	</tests>
	<help><![CDATA[
**What it does**

This tool compares nucleotide sequences within an input XMFA file and outputs a table reflecting 
the percent nucleotide identity between every sequence pair. Total similarity is based on 
regions of similarity called locally collinear blocks, or LCBs. There is no penalty for gaps.

**Options**
The dice method uses the following formula to normalize considering both sequences in the pairwise comparison::

	2 * number of identical matches / (query sequence length + subject sequence length)

]]></help>
		<expand macro="citations-2020" />
</tool>