<?xml version='1.0' encoding='utf-8'?>
<tool name="bcftools @EXECUTABLE@" id="bcftools_@EXECUTABLE@" version="@VERSION@.0">
    <description>Copy number variation caller, requires Illumina's B-allele frequency (BAF) and Log R Ratio intensity (LRR)</description>
    <macros>
        <token name="@EXECUTABLE@">cnv</token>
        <import>macros.xml</import>
    </macros>
    <expand macro="requirements" />
    <expand macro="version_command" />
    <command detect_errors="aggressive"><![CDATA[
@PREPARE_ENV@
@PREPARE_INPUT_FILE@
#set $section = $sec_restrict
@PREPARE_TARGETS_FILE@

bcftools @EXECUTABLE@

--output-dir cnv_tmp

## General section
#set $section = $sec_general
#if $section.control_sample:
  --control-sample "${section.control_sample}"
#end if
#if $section.query_sample:
  --query-sample "${section.query_sample}"
#end if
@AF_FILE@

#if $section.plot_threshold:
  --plot-threshold "${section.plot_threshold}"
#end if

## HMM section
#set $section = $sec_hmm
#if $section.aberrant_query or $section.aberrant_control:
  #set $query_val = #if $section.aberrant_query then $section.aberrant_query else '1.0'#
  #set $control_val = #if $section.aberrant_control then $section.aberrant_control else '1.0'#
  --aberrant "${query_val},${control_val}"
#end if
#if $section.BAF_weight:
  --BAF-weight "${section.BAF_weight}"
#end if
#if $section.BAF_dev_query or $section.BAF_dev_control:
  #set $query_val = #if $section.BAF_dev_query then $section.BAF_dev_query else '1.0'#
  #set $control_val = #if $section.BAF_dev_control then $section.BAF_dev_control else '1.0'#
  --BAF-dev "${query_val},${control_val}"
#end if
#if $section.LRR_weight:
  --LRR-weight "${section.LRR_weight}"
#end if
#if $section.LRR_dev_query or $section.LRR_dev_control:
  #set $query_val = #if $section.LRR_dev_query then $section.LRR_dev_query else '1.0'#
  #set $control_val = #if $section.LRR_dev_control then $section.LRR_dev_control else '1.0'#
  --LRR-dev "${query_val},${control_val}"
#end if
#if $section.LRR_smooth_win:
  --LRR-smooth-win "${section.LRR_smooth_win}"
#end if
#if $section.optimize:
  --optimize "${section.optimize}"
#end if
#if $section.same_prob:
  --same-prob "${section.same_prob}"
#end if
#if $section.err_prob:
  --err-prob "${section.err_prob}"
#end if
#if $section.xy_prob:
  --xy-prob "${section.xy_prob}"
#end if

## Filter section
#set $section = $sec_restrict
@REGIONS@
@TARGETS@

## Primary Input/Outputs
@INPUT_FILE@
&& mv $output_dir/cn.*.tab "$output_cn"
&& mv $output_dir/dat.*.tab "$output_dat"
&& mv $output_dir/summary.*.tab "$output_summary"
## && python $output_dir/plot.*.py
]]>
    </command>
    <inputs>
        <param name="output_dir" type="hidden" value="cnv_tmp"/>
        <expand macro="macro_input" />
        <section name="sec_restrict" expanded="false" title="Restrict to">
            <expand macro="macro_regions" />
            <expand macro="macro_targets" />
        </section>
        <param name="reference_fasta" type="data" format="fasta" label="Reference Fasta" />
        <section name="sec_general" expanded="true" title="General Options">
            <param name="query_sample" type="text" label="Query Sample" optional="True" help="Query samply name" />
            <param name="control_sample" type="text" label="Control Sample" optional="True" help="Optional control sample name to highlight differences" />
            <expand macro="macro_AF_file" />
            <param name="plot_threshold" type="float" label="Plot Threshold" optional="True" help="Plot aberrant chromosomes with quality at least 'float'" />
        </section>
        <section name="sec_hmm" expanded="false" title="HMM Options">
            <param name="err_prob" type="float" value="1e-4" label="Err Prob" optional="True" help="Uniform error probability" />
            <param name="optimize" type="float" value="" min="0." max="1." label="Optimize" optional="True" >
                <help>
                  Iteratively estimate the fraction of aberrant cells, down to the given fraction. 
                  Lowering this value from the default 1.0 to say, 0.3, can help discover more events but also increases noise.
                </help>
            </param>
            <param name="same_prob" type="float" value="" min="0." max="1." label="Same Prob" optional="True">
                <help>
                    The prior probability of the query and the control sample being the same. 
                    Setting to 0 calls both independently, setting to 1 forces the same copy number state in both.
                </help>
            </param>
            <param name="xy_prob" type="float" min="0." max="1." label="Xy Prob" value="1e-9" optional="True">
                <help>
                    The HMM probability of transition to another copy number state. 
                    Increasing this value leads to smaller and more frequent calls. 
                </help>
            </param>

            <param name="aberrant_query" type="float" value="" min="0." max="1." label="Aberrant Query" optional="true" 
                   help="Fraction of aberrant cells in query, defaults to 1." />
            <param name="aberrant_control" type="float" value="" min="0." max="1." label="Aberrant Control" optional="true" 
                   help="Fraction of aberrant cells in control, defaults to 1." />
            <param name="BAF_weight" type="float" value="1." min="0." max="1." label="Baf Weight" optional="True" help="relative contribution from BAF" />

            <param name="BAF_dev_query" type="float" value="" min="0." max="1." label="Baf Query Deviation" optional="true" 
                   help="Expected BAF deviation in query, defaults to: 0.04" />
            <param name="BAF_dev_control" type="float" value="" min="0." max="1." label="Baf Control Deviation" optional="true" 
                   help="Expected BAF deviation in control, defaults to: 0.04" />

            <param name="LRR_weight" type="float" label="LRR Weight" optional="True" >
                <help>
                    Relative contribution from LRR.  
                    With noisy data, this option can have big effect on the number of calls produced. 
                    In truly random noise (such as in simulated data), the value should be set high (1.0), i
                    but in the presence of systematic noise when LRR are not informative, lower values result in cleaner calls (0.2).
                </help>
            </param>
            <param name="LRR_dev_query" type="float" value="" min="0." max="1." label="LRR Query Deviation" 
                   help="Expected LRR deviation in query, default is: 0.2" />
            <param name="LRR_dev_control" type="float" value="" min="0." max="1." label="LRR Control Deviation" 
                   help="Expected LRR deviation in control, default is: 0.2" />
            <param name="LRR_smooth_win" type="integer" label="Lrr Smooth Win" value="10" optional="True" 
                   help="Window of LRR moving average smoothing" />

        </section>
    </inputs>
    <outputs>
        <data name="output_cn" format="tabular" label="${input_file.name.rsplit('.',1)[0]}.cn"/>
        <data name="output_dat" format="tabular" label="${input_file.name.rsplit('.',1)[0]}.dat"/>
        <data name="output_summary" format="tabular" label="${input_file.name.rsplit('.',1)[0]}.summary"/>
        <!-- add plot output -->
        <!-- script has png per chr, html of images or collect into pdf?
        <data name="output_plots" format="" />
         -->
    </outputs>
    <tests />
    <help><![CDATA[
=====================================
 bcftools @EXECUTABLE@
=====================================

Copy number variation caller, requires Illumina's B-allele frequency (BAF) and Log R Ratio intensity (LRR). 
The HMM considers the following copy number states: CN 2 (normal), 1 (single-copy loss), 0 (complete loss), 3 (single-copy gain)

@REGIONS_HELP@
@TARGETS_HELP@

@BCFTOOLS_MANPAGE@#@EXECUTABLE@

@BCFTOOLS_WIKI@
]]>
    </help>
    <expand macro="citations" />
</tool>