comparison lastz_d.xml @ 5:ec4affe27298 draft

"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/lastz commit 25c49a61a5358cc7ab016fb5847328af7e67a24c"

4:0acd9701676b

        '--infscores=${output}'
        ]]>
    </command>
    <inputs>
        <expand macro="target_input"/>
        <param name="query" format="fasta,fastq" type="data" label="Select QUERY sequence(s)" help="These are the sequences that you are aligning against TARGET"/>
        <param name="score_file" type="data" format="txt" optional="true" label="Control file for inference" argument="--inferonly[=control_file]" help="Optional controf file. If nothing is selected, LASTZ_D uses default described in the manual"/>
     </inputs>
    <outputs>
        <data format="txt" name="output" label="${tool.name} on ${on_string}: substituion matrix"/>
    </outputs>

    <help><![CDATA[

**What is does**

LASTZ_D is a non-integer (**D** stands for Double) version of LASTZ that can be used to estimate substitution matrix that will be used to score alignments. It was developed by `Bob Harris <http://www.bx.psu.edu/~rsharris/>`_ in the lab of Webb Miller at Penn State as a part of LASTZ. Matrix computed by this tool is to be used by LASTZ (see below).

.. class:: warningmark

**Read documentation** before proceeding. LASTZ is a complex tool with many parameter options. Fortunately, there is a `great manual <https://lastz.github.io/lastz/>`_ maintained by its author. The two sections that are particularly relevant to the inference of substitution matrix are `Inferring Score Sets <http://www.bx.psu.edu/~rsharris/lastz/README.lastz-1.04.00.html#adv_inference>`_ and `Inference Control File <http://www.bx.psu.edu/~rsharris/lastz/README.lastz-1.04.00.html#fmt_inference>`_.

**Notes on the inference**

Inference is achieved by computing the probability of each of the 18 different alignment events (gap open, gap extend, and 16 substitutions). These probabilities are estimated from alignments of the sequences. Of course, at first we don't have alignments, so the process begins by using a generic scoring set to create alignments, infer scores from those, then realign, and so on, until the scores stabilize or "converge". Ungapped alignments are performed until the substitution scores converge, then gapped alignments are performed (holding the substitution scores constant) until the gap penalties converge. In the end you get a matrix like this::

    # (a LASTZ scoring set, created by "LASTZ --infer")

    bad_score          = X:-1781 # used for sub[X][*] and sub[*][X]
    fill_score         = -178    # used when sub[*][*] not otherwise defined

5:ec4affe27298

        '--infscores=${output}'
        ]]>
    </command>
    <inputs>
        <expand macro="target_input"/>
        <param name="query" format="fasta,fastq,fasta.gz,fastq.gz,fastq.bz2" type="data" label="Select QUERY sequence(s)" help="These are the sequences that you are aligning against TARGET"/>
        <param name="score_file" type="data" format="txt" optional="true" label="Control file for inference" argument="--inferonly[=control_file]" help="Optional controf file. If nothing is selected, LASTZ_D uses default described in the manual"/>
     </inputs>
    <outputs>
        <data format="txt" name="output" label="${tool.name} on ${on_string}: substituion matrix"/>
    </outputs>

    <help><![CDATA[

**What is does**

LASTZ_D is a non-integer (**D** stands for Double) version of LASTZ that can be used to estimate substitution matrix that
will be used to score alignments. It was developed by `Bob Harris <http://www.bx.psu.edu/~rsharris/>`_ in the lab of
Webb Miller at Penn State as a part of LASTZ. Matrix computed by this tool is to be used by LASTZ (see below).

.. class:: warningmark

**Read documentation** before proceeding. LASTZ is a complex tool with many parameter options. Fortunately, there is
a `great manual <https://lastz.github.io/lastz/>`_ maintained by its author. The two sections that are particularly
relevant to the inference of substitution matrix are
`Inferring Score Sets <https://www.bx.psu.edu/~rsharris/lastz/README.lastz-1.04.03.html#adv_inference>`_ and
`Inference Control File <https://www.bx.psu.edu/~rsharris/lastz/README.lastz-1.04.03.html#fmt_inference>`_.

**Notes on the inference**

Inference is achieved by computing the probability of each of the 18 different alignment events (gap open, gap extend, and 16 substitutions).
These probabilities are estimated from alignments of the sequences. Of course, at first we don't have alignments, so the process
begins by using a generic scoring set to create alignments, infer scores from those, then realign, and so on, until the scores stabilize
or "converge". Ungapped alignments are performed until the substitution scores converge, then gapped alignments are performed
(holding the substitution scores constant) until the gap penalties converge. In the end you get a matrix like this::

    # (a LASTZ scoring set, created by "LASTZ --infer")

    bad_score          = X:-1781 # used for sub[X][*] and sub[*][X]
    fill_score         = -178    # used when sub[*][*] not otherwise defined