comparison cloudmap.xml @ 0:aa82b2e54055 draft

planemo upload for repository https://github.com/wm75/mimodd_galaxy_wrappers commit b36048cd608ede0ec6f6559648525c9350caae34-dirty

0:aa82b2e54055

<tool id="mimodd_map" name="MiModD NacreousMap" version="@MIMODD_WRAPPER_VERSION@">
    <description>maps phenotypically selected variants by multi-variant linkage analysis</description>
    <macros>
        <import>macros.xml</import>
        <macro name="svd_unconditional">
            <expand macro="hidden_algo_params" />
            <expand macro="seqdict_param" />
            <expand macro="bins" />
            <conditional name="plotopts">
                <param name="plots" type="select" label="graphical output settings">
                    <option value="-p">Give me graphics.</option>
                    <option value="">Do not generate graphs.</option>
                </param>
                <when value="">
                </when>
                <when value="-p">
                    <expand macro="scatter_default" />
                    <param name="show_kde" type="boolean" truevalue="" falsevalue="--no-kde" checked="true"
                    label="show kde line in histogram plots"
                    help="The tool can calculate a kernel density estimate for the linkage data based on a bin size of 10 kilobases and display it as a solid line in the histogram plots." />
                    <param name="hylim" type="text" 
                    label="upper limit for the histogram y-axis (leave blank for automatic scaling)" />
                    <param name="xlim" type="select" label="x-axis scaling">
                        <option value="">preserve relative contig sizes</option>
                        <option value="--fit-width">scale each contig to fit the plot width</option>
                    </param>
                    <expand macro="hist_colors" />
                </when>
            </conditional>
        </macro>
        <macro name="vaf_unconditional">
            <expand macro="bins" />
            <conditional name="plotopts">
                <param name="plots" type="select" label="graphical output settings">
                    <option value="-p">Give me everything (scatter plots and histograms)</option>
                    <option value="--no-scatter -p">Generate only histograms</option>
                    <option value="--no-hist -p">Generate only scatter plots</option>
                    <option value="">Do not generate graphs.</option>
                </param>
                <when value="">
                </when>
                <when value="--no-scatter -p">
                    <expand macro="scatter_default" />
                    <param name="show_kde" type="boolean" truevalue="" falsevalue="--no-kde" checked="true"
                    label="show kde line in histogram plots"
                    help="The tool can calculate a kernel density estimate for the linkage data based on a bin size of 10 kilobases and display it as a solid line in the histogram plots." />
                    <param name="hylim" type="text" 
                    label="upper limit for the histogram y-axis (leave blank for automatic scaling)" />
                    <param name="xlim" type="select" label="x-axis scaling">
                        <option value="">preserve relative contig sizes</option>
                        <option value="--fit-width">scale each contig to fit the plot width</option>
                    </param>
                    <expand macro="hist_colors" />
                </when>
                <when value="--no-hist -p">
                    <expand macro="hist_default" />
                    <param name="sylim" type="text" 
                    label="upper limit for the scatter plot y-axis (default: 1)" />
                    <param name="xlim" type="select" label="x-axis scaling">
                        <option value="">preserve relative contig sizes</option>
                        <option value="--fit-width">scale each contig to fit the plot width</option>
                    </param>
                    <param name="span" type="text" 
                    label="span value to be used in calculating the Loess regression line through the scatter data (default=0.1, specify 0 to prevent calculation)" 
                    help="smaller values give a more responsive curve that often picks up local evidence for tight linkage better, but too small values lead to plotting failures (in that case just rerun the tool with a larger value)." />
                    <expand macro="scatter_colors" />
                </when>
                <when value="-p">
                    <expand macro="plot_all" />
                </when>
            </conditional>
        </macro>
        <macro name="vac_unconditional">
            <expand macro="bins" />
            <conditional name="plotopts">
                <param name="plots" type="select" label="graphical output settings">
                    <option value="--no-scatter -p">Give me graphical output</option>
                    <option value="">Do not generate graphs.</option>
                </param>
                <when value="">
                </when>
                <when value="--no-scatter -p">
                    <expand macro="scatter_default" />
                    <param name="show_kde" type="boolean" truevalue="" falsevalue="--no-kde" checked="true"
                    label="show kde line in histogram plots"
                    help="The tool can calculate a kernel density estimate for the linkage data based on a bin size of 10 kilobases and display it as a solid line in the histogram plots." />
                    <param name="hylim" type="text" 
                    label="upper limit for the histogram y-axis (leave blank for automatic scaling)" />
                    <param name="xlim" type="select" label="x-axis scaling">
                        <option value="">preserve relative contig sizes</option>
                        <option value="--fit-width">scale each contig to fit the plot width</option>
                    </param>
                    <expand macro="hist_colors" />
                </when>
            </conditional>
        </macro>
        <macro name="hidden_algo_params">
            <param name="sample" type="hidden" value="" />
            <expand macro="hidden_vaf_algo_params" />
            <param name="contrast_sample" type="hidden" value="" />
        </macro>
        <macro name="hidden_vaf_algo_params">
            <param name="related_parent_sample" type="hidden" value="" />
            <param name="unrelated_parent_sample" type="hidden" value="" />
            <param name="infer_missing" type="hidden" value="" />
        </macro>
        <macro name="bins">
            <repeat name="bin_sizes" default="0" min="0" title="bin sizes to analyze variants in (defaults to: 1Mb and 500Kb)" 
            help="Values can be entered in bases (e.g., 1000000), kilobases (e.g., 500Kb) or megabases (e.g., 1Mb), but must be integral, i.e. no decimal numbers are allowed.">
                <param name="bin_size" type="text" />
            </repeat>
        </macro>
        <macro name="scatter_default">
            <param name="sylim" type="hidden" value="" />
            <param name="span" type="hidden" value="" />
            <param name="pcols" type="hidden" value="" />
            <param name="lcols" type="hidden" value="" />
        </macro>
        <macro name="hist_default">
            <param name="show_kde" type="hidden" value="" />
            <param name="hylim" type="hidden" value="" />
            <param name="hcols" type="hidden" value="" />
        </macro>
        <macro name="hist_colors">
            <repeat name="hcols" default="0" min="0" title="histogram colors"
            help="For each bin size chosen above a histogram will be generated with its color selected from the list provided here (defaults to alternating darkgrey, red).">
                <param name="hcolor" type="color" value="darkgrey">
                    <sanitizer><valid><add value="#" /></valid></sanitizer>
                </param>
            </repeat>
        </macro>
        <macro name="scatter_colors">
            <repeat name="pcols" default="0" min="0" title="data point colors"
            help="Series of data points will be plotted based on the colors selected here.">
                <param name="pcol" type="color" value="black">
                    <sanitizer><valid><add value="#" /></valid></sanitizer>
                </param>
            </repeat>
            <repeat name="lcols" default="0" min="0"
            title="regression line colors"
            help="Regression lines through series of data will be plotted in the colors selected here.">
                <param name="lcol" type="color" value="red">
                    <sanitizer><valid><add value="#" /></valid></sanitizer>
                </param>
            </repeat>
        </macro>
        <macro name="plot_all">
            <param name="show_kde" type="boolean" truevalue="" falsevalue="--no-kde" checked="true"
            label="show kde line in histogram plots"
            help="The tool can calculate a kernel density estimate for the linkage data based on a bin size of 10 kilobases and display it as a solid line in the histogram plots." />
            <param name="hylim" type="text" 
            label="upper limit for the histogram y-axis (leave blank for automatic scaling)" />
            <param name="sylim" type="text" 
            label="upper limit for the scatter plot y-axis (default: 1)" />
            <param name="xlim" type="select" label="x-axis scaling">
                <option value="">preserve relative contig sizes</option>
                <option value="--fit-width">scale each contig to fit the plot width</option>
            </param>
            <param name="span" type="text" 
            label="span value to be used in calculating the Loess regression line through the scatter data (default=0.1, specify 0 to prevent calculation)" 
            help="smaller values give a more responsive curve that often picks up local evidence for tight linkage better, but too small values lead to plotting failures (in that case just rerun the tool with a larger value)." />
            <expand macro="hist_colors" />
            <expand macro="scatter_colors" />
        </macro>
        <macro name="seqdict_param">
            <conditional name="seqinfo_external">
                <param name="source" type="select"
                label="does this input provide contig name and size information?"
                help="ALWAYS select 'yes' here if the input dataset was generated with MiModD. Input generated with third-party tools may or may not provide the information. If in doubt, execute the job with 'yes' selected and see if you are getting a corresponding error message.">
                    <option value="">Yes</option>
                    <option value="fasta">No, get the information from a reference genome in my history</option>
                    <option value="cached">No, get the information from a built-in genome</option>
                    <option value="seqdict">No, get the information from a CloudMap-style sequence dictionary in my history</option>
                </param>
                <when value="fasta">
                    <param name="seqinfo" type="data" format="fasta"
                    label="Reference genome to extract contig info from" />
                </when>
                <when value="cached">
                    <param name="seqinfo" type="select"
                    label="Reference genome to extract contig info from">
                        <options from_data_table="all_fasta" />
                    </param>
                </when>
                <when value="seqdict">
                    <param name="seqinfo" type="data" format="tabular"
                    label="CloudMap-style sequence dictionary to extract contig info from" />
                </when>
                <when value="">
                </when>
            </conditional>
        </macro>
        <macro name="test_tabular_out">
            <output name="ofile" ftype="tabular">
                <assert_contents>
                    <has_text text="chrI" />
                    <has_text text="chrII" />
                    <has_text text="chrIII" />
                    <has_text text="chrIV" />
                    <has_text text="chrV" />
                    <has_text text="chrX" />
                    <has_text text="MtDNA" />
                </assert_contents>
            </output>
        </macro>
    </macros>
    <expand macro="requirements" />
    <expand macro="stdio" />
    <expand macro="version_command" />
    <command><![CDATA[
    mimodd map ${opt.mode} "${opt.source.ifile}"
      #if $str($opt.source.sample):
        -m '${opt.source.sample}'
      #end if
      #if $str($opt.source.related_parent_sample):
        -r '${opt.source.related_parent_sample}'
      #end if
      #if $str($opt.source.unrelated_parent_sample):
        -u '${opt.source.unrelated_parent_sample}'
      #end if
      #if $str($opt.source.contrast_sample):
        -c '${opt.source.contrast_sample}'
      #end if
        $opt.source.infer_missing
        -o '$ofile'
      #if $str($opt.source.seqinfo_external.source) in ("fasta", "seqdict"):
        -s '${opt.source.seqinfo_external.seqinfo}'
      #else if $str($opt.source.seqinfo_external.source) == "cached":
        -s '${opt.source.seqinfo_external.seqinfo.fields.path}'
      #end if
      #if $len($opt.source.bin_sizes):
        --bin-sizes
        #for $size in $opt.source.bin_sizes:
          '${size.bin_size}'
        #end for
      #end if
      #if $str($opt.source.tabfile):
        $str($opt.source.tabfile) '$tfile'
      #end if
      #if $str($opt.source.plotopts.plots):
        $str($opt.source.plotopts.plots) '$pfile'
        $opt.source.plotopts.show_kde
        $str($opt.source.plotopts.xlim)
        #if $str($opt.source.plotopts.hylim):
          --ylim-hist $str($opt.source.plotopts.hylim)
        #end if
        #if $str($opt.source.plotopts.hcols) and $len($opt.source.plotopts.hcols):
          --hist-colors
          #for $color in $opt.source.plotopts.hcols:
            '${color.hcolor}'
          #end for
        #end if
        #if $str($opt.source.plotopts.sylim):
          --ylim-scatter $str($opt.source.plotopts.sylim)
        #end if
        #if $str($opt.source.plotopts.pcols) and $len($opt.source.plotopts.pcols):
          --points-colors 
          #for $color in $opt.source.plotopts.pcols:
            '${color.pcol}'
          #end for
        #end if
        #if $str($opt.source.plotopts.lcols) and $len($opt.source.plotopts.lcols):
          --loess-colors
          #for $color in $opt.source.plotopts.lcols:
            '${color.lcol}'
          #end for
        #end if
        #if $str($opt.source.plotopts.span):
          --loess-span $str($opt.source.plotopts.span)
        #end if
      #end if
    ]]></command>
  
    <inputs>
        <conditional name="opt">
            <param name="mode" type="select" label="type of mapping analysis to perform" 
            help="Select Simple Variant Density (SVD) Mapping to map mutations based on linked inheritance in near isogenic populations, Variant Allele Frequency (VAF) Mapping for bulk segregant analysis. Select Reprocess for rapidly replotting the result of a previous VAF analysis.">
                <option value="SVD">Simple Variant Density Mapping</option>
                <option value="VAF">Variant Allele Frequency Mapping</option>
                <option value="VAC">Variant Allele Contrast Mapping</option>
            </param>
            <when value="SVD">
                <conditional name="source">
                    <param name="inputtype" type="select" label="data source to use">
                        <option value="vcf">VCF file of variants (for de-novo mapping)</option>
                        <option value="rep">per-variant report file (for remapping a previous analysis)</option>
                    </param>
                    <when value="vcf">
                        <param name="ifile" type="data" format="vcf" 
                        label="input file with variants to analyze" />
                        <expand macro="svd_unconditional" />
                        <param name="tabfile" type="select" 
                        label="additional per-variant output file" 
                        help="You can either choose to produce a tabular per-variant report, which is useful for fast replotting with different plot settings, or a VCF-like CloudMap-compatibility output that can be used as input for the older CloudMap EMS Variant Density Mapping tool as an alternative plotting tool.">
                            <option value="">Do not generate per-variant output</option>
                            <option value="-t">Tabular per-variant report</option>
                            <option value="--cloudmap -t">CloudMap compatibility output</option>
                        </param>
                    </when>
                    <when value="rep">
                        <param name="ifile" type="data" format="tabular,csv" 
                        label="input file with variants to analyze" />
                        <param name="tabfile" type="hidden" value="" />
                        <expand macro="svd_unconditional" />
                    </when>
                </conditional>
            </when>
            <when value="VAF">
                <conditional name="source">
                    <param name="inputtype" type="select" label="data source to use">
                        <option value="vcf">VCF file of variants (for de-novo mapping)</option>
                        <option value="rep">per-variant report file (for remapping a previous analysis)</option>
                    </param>
                    <when value="vcf">
                        <param name="ifile" type="data" format="vcf" 
                        label="input file with variants to analyze" />
                        <expand macro="seqdict_param" />
                        <param name="sample" type="text" 
                        label="mapping sample name" help="the sample to perform mutation mapping for">
                            <validator type="empty_field" />
                        </param>
                        <param name="related_parent_sample" type="text" 
                        label="name of the related parent sample" 
                        help="the sample that provides variants present in your original mutant strain or in an ancestor (like the pre-mutagenesis strain); leave blank if not available" />
                        <param name="unrelated_parent_sample" type="text" 
                        label="name of the unrelated parent sample" 
                        help="the sample that provides variants present in the unrelated mapping strain (or in an ancestor of it) used in the mapping cross; leave blank if not available" />
                        <param name="infer_missing" type="boolean" truevalue="--infer-missing" falsevalue="" checked="false" 
                        label="Infer alleles for missing parent" 
                        help="if variant data for either the related or the unrelated parent strain is not available, the tool can try to infer the alleles present in that parent from the allele spectrum found in the mapping sample. Use with caution on carefully filtered variant lists only!" />
                        <param name="contrast_sample" type="hidden" value="" />
                        <expand macro="vaf_unconditional" />
                        <param name="tabfile" type="select" 
                        label="additional per-variant output file" 
                        help="You can either choose to produce a tabular per-variant report, which is useful for fast replotting with different plot settings, or a VCF-like CloudMap-compatibility output that can be used as input for the older CloudMap Hawaiian Variant Mapping tool as an alternative plotting tool.">
                            <option value="">Do not generate per-variant output</option>
                            <option value="-t">Tabular per-variant report</option>
                            <option value="--cloudmap -t">CloudMap compatibility output</option>
                        </param>
                    </when>
                    <when value="rep">
                        <param name="ifile" type="data" format="tabular,csv" 
                        label="input file with variants to analyze" />
                        <expand macro="seqdict_param" />
                        <param name="tabfile" type="hidden" value="" />
                        <expand macro="hidden_algo_params" />
                        <expand macro="vaf_unconditional" />
                    </when>
                </conditional>
            </when>
            <when value="VAC">
                <conditional name="source">
                    <param name="inputtype" type="select"
                    label="data source to use">
                        <option value="vcf">VCF file of variants (for de-novo mapping)</option>
                        <option value="rep">per-variant report file (for remapping a previous analysis)</option>
                    </param>
                    <when value="vcf">
                        <param name="ifile" type="data" format="vcf"
                        label="input file with variants to analyze" />
                        <expand macro="seqdict_param" />
                        <expand macro="hidden_vaf_algo_params" />
                        <param name="sample" type="text"
                        label="mapping sample name"
                        help="the sample to perform mutation mapping for">
                            <validator type="empty_field" />
                        </param>
                        <param name="contrast_sample" type="text"
                        label="name of the contrast sample"
                        help="the sample that provides contrasting allele composition around the causal variant">
                            <validator type="empty_field" />
                        </param>
                        <expand macro="vac_unconditional" />
                        <param name="tabfile" type="select"
                        label="additional per-variant output file"
                        help="You can choose to produce a tabular per-variant report, which is useful for fast replotting with different plot settings.">
                            <option value="">Do not generate per-variant output</option>
                            <option value="-t">Tabular per-variant report</option>
                        </param>
                    </when>
                    <when value="rep">
                        <param name="ifile" type="data" format="tabular,csv"
                        label="input file with variants to analyze" />
                        <expand macro="seqdict_param" />
                        <param name="tabfile" type="hidden" value="" />
                        <expand macro="hidden_algo_params" />
                        <expand macro="vac_unconditional" />
                    </when>
                </conditional>
            </when>
        </conditional>
    </inputs>
    <outputs>
        <data name="ofile" format="tabular" 
        label="MiModD ${opt.mode} Mapping - binned variant counts for ${on_string}" />
        <data name="tfile" format="tabular" 
        label="MiModD ${opt.mode} Mapping - per-variant report for ${on_string}">
            <filter>(opt['source']['tabfile'])</filter>
        </data>
        <data name="pfile" format="pdf" 
        label="MiModD ${opt.mode} Mapping - linkage plots for ${on_string}">
            <filter>(opt['source']['plotopts']['plots'])</filter>
        </data>
    </outputs>

    <tests>
        <test expect_num_outputs="1">
            <conditional name="opt">
                <param name="mode" value="SVD" />
                <conditional name="source">
                    <param name="inputtype" value="vcf" />
                    <conditional name="plotopts">
                        <param name="plots" value="" />
                    </conditional>
                    <param name="ifile" value="a.vcf" />
                </conditional>
            </conditional>
            <expand macro="test_tabular_out" />
        </test>
        <test expect_num_outputs="2">
            <conditional name="opt">
                <param name="mode" value="VAF" />
                <conditional name="source">
                    <param name="inputtype" value="vcf" />
                    <conditional name="plotopts">
                        <param name="plots" value="-p" />
                    </conditional>
                    <param name="sample" value="ot266" />
                    <param name="related_parent_sample" value="N2" />
                    <param name="ifile" value="a.vcf" />
                </conditional>
            </conditional>
            <expand macro="test_tabular_out" />
            <output name="pfile" file="vaf_linkage.pdf" ftype="pdf"
            compare="sim_size" delta="100000" />
        </test>
    </tests>
    
    <help><![CDATA[
.. class:: infomark

   **What it does**

This is the most downstream tool in
`mapping-by-sequencing analysis workflows in MiModD`_.

It can be used to analyze and visualize the inheritance pattern of variants
detected and selected with other MiModD tools or as an alternative (and more
versatile) plotting engine for data generated with `CloudMap`_.

-------------

**Usage Modes:**

This tool can be run in one of three different modes depending on the type of
mapping analysis that should be performed:

1) *Simple Variant Density (SVD) Mapping* mode analyzes the density of variants
   along the reference genome by dividing each chromosome into regions of
   user-defined size (bins) and counting the variants found in each bin. 
    
   All variants listed in the input file are analyzed in this mode, which means
   that as input you will typically want to use filtered lists of variants (as
   produced by the VCF Filter tool). 
    
   The aim of SVD analysis is to identify clusters of variants in an outcrossed
   strain carrying a selectable unknown mutation, which is interpreted as
   linkage between the corresponding genomic region and the unknown mutation.
    
   This mode corresponds roughly to EMS Variant Density Mapping in CloudMap.

2) *Variant Allele Frequency (VAF) Mapping* mode analyzes the inheritance
   pattern in cross-progeny at sites, at which the parents are homozygous for
   different alleles. 
    
   The aim of VAF analysis is to identify clusters of variants with (near)
   homozygous inheritance in a F2 (or later generation) population obtained
   from a cross between a strain carrying a selectable unknown mutation and an
   unrelated mapping strain. Such a cluster is interpreted as linkage between
   the corresponding genomic region and the unknown mutation selected for in
   the F2 generation. 
    
   This mode corresponds roughly to Hawaiian Variant Mapping in CloudMap, but
   can simultaneously take into account non-reference alleles found in either
   parent strain (CloudMap users may think of this as a combined Hawaiian
   Variant and Variant Discovery Mapping analysis).

3) *Variant Allele Contrast (VAC) Mapping* mode analyzes and visualizes the
   divergence between two samples at all sites in the input dataset. It works
   independent of any parent strain information and can be used if you have two
   samples selected for contrary phenotypes, but also with a selected and a
   non-selected sample.

-------------

**Input:**

Valid input for this tool are VCF datasets (any such dataset in SVD mode, a
MiModD-generated multi-sample VCF dataset in VAF and VAC modes) or a tabular
report as generated by the CloudMap Hawaiian Variant Mapping tool.
Alternatively, the tool can generate (in both modes) its own tabular reports,
which can be used as input instead of the original VCF dataset, when rerunning
the tool with different plotting parameters, to reduce analysis time. 

-------------

**Output:**

The tool produces up to three output files:

1) a default tabular report of binned variant counts that can be used to plot
   the data with external software such as Excel,

2) an optional pdf containing linkage plots, and
  
3) an optional tabular per-variant report, which can be configured to be either
   valid input for the corresponding original CloudMap tool (for users who
   really, really want to continue using CloudMap for plotting) or to be
   reusable in fast reruns of the tool (which can be useful to experiment with
   different plotting parameters).

-------------

**Settings:**

1) Analysis settings

   *bin size to analyze variants in* - determines the width of the regions
   along each chromosome, in which variants are counted and analyzed together. 
     
   Several bin sizes can be specified and for each size you will get a
   corresponding results section in the binned variant counts report and a
   linkage histogram plot.
      
   *sample names (in VAF and VAC modes only)* - to analyze inheritance
   patterns, the VAF and VAC modes need information about the relationship
   between the samples defined in the input. While VAC mode simply requires
   you to name the two contrasting samples for the analysis, the sample roles
   in VAF mode are a bit more complicated to understand. Specifically:

   The *mapping sample name* should be set to the name of the sample for which
   the inheritance pattern is to be analyzed (the pooled progeny population). 

   The *name of the related sample* should indicate the parent sample that
   carried and brought in the unknown mutation to be mapped (or, alternatively,
   a closely related ancestor). 

   The *name of the unrelated sample* should be that of the other parent strain
   used in the cross. 
     
   At least one of the parent samples MUST be specified, but if the input
   contains variant information for both parents, they can be analyzed together
   for higher mapping accuracy. If you are reanalyzing a tabular report from a
   previous tool run or from CloudMap, the association between variants and
   samples is already stored in the input dataset and cannot be specified
   again.

2) Graphical output settings

   .. class:: warningmark
  
      To be able to generate plots, the system running MiModD needs to have the
      statistical programming environment R and its Python interface rpy2
      installed. Disable graphical output if this is not the case.

   *y-axes scaling* - if you want to override the defaults

   *x-axis scaling* - choose *preserve relative contig sizes* if you want the
   largest chromosome to fit the page width and smaller chromosomes to appear
   according to their relative size or choose *scale each contig to fit the
   plot width* if all chromosomes should exploit the available space

   *span value to be used in calculating the Loess regression line* - this
   value determines the degree of smoothing of the regression line through the
   scatterplot data. Information on loess regression and the loess span
   parameter can be found at http://en.wikipedia.org/wiki/Local_regression.
   
   *colors used for plotting* - can be selected freely from the offered
   palette. For histogram colors, the list of selected colors will be used to
   provide the colors for the different histograms plotted. If less colors than
   histograms (determined by the number of bin sizes selected) are specified,
   colors from the list will be recycled.

.. _CloudMap: https://usegalaxy.org/u/gm2123/p/cloudmap
.. _mapping-by-sequencing analysis workflows in MiModD: http://mimodd.readthedocs.io/en/latest/nacreousmap.html
.. _CloudMap-style sequence dictionary: http://mimodd.readthedocs.io/en/latest/fileformats.html#cloudmap-style-sequence-dictionary

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