<tool id="kallisto_index_builder_data_manager" name="Kallisto" tool_type="manage_data" version="0.43.2" profile="23.0">
    <description>index builder</description>
    <requirements>
        <requirement type="package" version="0.43.1">kallisto</requirement>
        <requirement type="package" version="3.8.3">python</requirement>
    </requirements>
    <command detect_errors="exit_code"><![CDATA[
        python '$__tool_directory__/kallisto_index_builder.py' --output '${out_file}'
            --fasta_filename '${all_fasta_source.fields.path}'
            --fasta_dbkey '${all_fasta_source.fields.dbkey}'
            --fasta_description '${all_fasta_source.fields.name}'
            --data_table_name kallisto_indexes
        ]]>
    </command>
    <inputs>
        <param label="Source FASTA Sequence" name="all_fasta_source" type="select">
            <options from_data_table="all_fasta" />
        </param>
        <param name="sequence_name" type="text" value="" label="Name of sequence" />
        <param name="sequence_id" type="text" value="" label="ID for sequence" />
    </inputs>
    <outputs>
        <data name="out_file" format="data_manager_json" />
    </outputs>
    <help>
<![CDATA[
.. class:: infomark

**Notice:** If you leave name, description, or id blank, it will be generated automatically.

What is Kallisto?
---------------

`kallisto <https://pachterlab.github.io/kallisto/about>`__ is a program for
quantifying abundances of transcripts from RNA-Seq data, or more generally of
target sequences using high-throughput sequencing reads. It is based on the
novel idea of pseudoalignment for rapidly determining the compatibility of
reads with targets, without the need for alignment. On benchmarks with standard
RNA-Seq data, kallisto can quantify 30 million human reads in less than 3
minutes on a Mac desktop computer using only the read sequences and a
transcriptome index that itself takes less than 10 minutes to build.
Pseudoalignment of reads preserves the key information needed for
quantification, and kallisto is therefore not only fast, but also as accurate
as existing quantification tools. In fact, because the pseudoalignment
procedure is robust to errors in the reads, in many benchmarks kallisto
significantly outperforms existing tools.
]]>
    </help>
    <citations>
        <citation type="doi">10.1038/nmeth.3317</citation>
    </citations>
</tool>