comparison antismash.xml @ 11:d2c2eb518142 draft

Uploaded

10:d2c785cdf23e

    <requirements>
        <requirement type="package" version="3.0">hmmer</requirement>
        <requirement type="package" version="2.3.2">hmmer</requirement>
        <requirement type="package" version="2.2.28">blast+</requirement>
        <requirement type="package" version="3.8.31">muscle</requirement>
        <requirement type="package" version="1.62">biopython</requirement>
        <requirement type="package" version="2.0.2">antismash_python_deps</requirement>
        <requirement type="package" version="2.0.2">antismash</requirement>
    </requirements>
    <command>
        run_antismash.py 

    </command>
    <inputs>
        <param name="infile" type="data" format="gb,embl" label="Nucleotide sequence file in GenBank or EMBL format"/>

        <param name="smcogs" type="boolean" label="Look for sec.met. clusters of orthologous groups" falsevalue="" truevalue="--smcogs" checked="false" />
        <param name="clusterblast" type="boolean" label="BLAST identified clusters against known clusters" truevalue="--clusterblast" falsevalue="" checked="false" />
        <param name="subclusterblast" type="boolean" label="BLAST identified clusters against known subclusters" truevalue="--subclusterblast" falsevalue="" checked="false" />

        <param name="inclusive" type="boolean" label="Use inclusive algorithm for cluster detection" truevalue="--inclusive" falsevalue="" checked="false" />
        <param name="full_hmmer" type="boolean" label="Run a whole-genome HMMer analysis" truevalue="--full-hmmer" falsevalue="" checked="false" />
        <param name="full_blast" type="boolean" label="Run a whole-genome BLAST analysis" truevalue="--full-blast" falsevalue="" checked="false" />

        <param name="pfam_database" type="select" label="Pfam database" help="Pfam Covariance models">
            <options from_file="antismash.loc">
              <column name="value" index="0"/>
              <column name="name" index="1"/>

    </outputs>
  <help>
    
.. class:: infomark

That version of antiSMASH can only handle one sequence. So multi-sequence FASTA files are not supported.
For multiple sequences please use multi-antiSMASH. The advantage of that tool is that it will provide you with a 
archive of all results created from antiSMASH (It can be large!) and a HTML output, for better inspection.


**What it does**

antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genomes. 
It integrates and cross-links with a large number of in silico secondary metabolite analysis tools that have been published earlier.


**Input**

If you don't have an annotated GenBank or embl file you also can provide a glimmer prediction output. You can created it with glimmer or glimmerHMM.


**References**

Marnix H. Medema, Kai Blin, Peter Cimermancic, Victor de Jager, Piotr Zakrzewski, Michael A. Fischbach, Tilmann Weber, 

11:d2c2eb518142

    <requirements>
        <requirement type="package" version="3.0">hmmer</requirement>
        <requirement type="package" version="2.3.2">hmmer</requirement>
        <requirement type="package" version="2.2.28">blast+</requirement>
        <requirement type="package" version="3.8.31">muscle</requirement>
        <requirement type="package" version="2.0.2">antismash_python_deps</requirement>
        <requirement type="package" version="2.0.2">antismash</requirement>
    </requirements>
    <command>
        run_antismash.py 

    </command>
    <inputs>
        <param name="infile" type="data" format="gb,embl" label="Nucleotide sequence file in GenBank or EMBL format"/>

        <param name="clusterblast" type="boolean" label="BLAST identified clusters against known clusters" truevalue="--clusterblast" falsevalue="" checked="True" />
        <param name="smcogs" type="boolean" label="analysis of secondary metabolism gene families (smCOGs)" 
            falsevalue="" truevalue="--smcogs" checked="True" />

        <param name="full_blast" type="boolean" label="Run a whole-genome BLAST analysis" truevalue="--full-blast" falsevalue="" checked="False" />
        <param name="subclusterblast" type="boolean" label="Subcluster Blast analysis" truevalue="--subclusterblast" falsevalue="" checked="false" />
        <param name="full_hmmer" type="boolean" label="Run a whole-genome Pfam analysis" truevalue="--full-hmmer" falsevalue="" checked="false" />

        <param name="inclusive" type="boolean" label="Use inclusive algorithm for cluster detection" truevalue="--inclusive" falsevalue="" checked="false" />

        <param name="pfam_database" type="select" label="Pfam database" help="Pfam Covariance models">
            <options from_file="antismash.loc">
              <column name="value" index="0"/>
              <column name="name" index="1"/>

    </outputs>
  <help>
    
.. class:: infomark

**What it does**

antiSMASH allows the rapid genome-wide identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genomes. 
It integrates and cross-links with a large number of in silico secondary metabolite analysis tools that have been published earlier.


**Input**

The ideal input for antiSMASH is an annotated nucleotide file in Genbank format or EMBL format. If no annotation is available, 
we recommend running your sequence through an annotation pipeline like RAST are one included in Galaxy.


There are several optional analyses that may or may not be run on your sequence.
Highly recommended is the Gene Cluster Blast Comparative Analysis, which runs BlastP using each amino acid sequence from a detected gene cluster as a 
query on a large database of predicted protein sequences from secondary metabolite biosynthetic gene clusters, and pools the results to identify 
the gene clusters that are most homologous to the gene cluster that was detected in your query nucleotide sequence.


Also available is the analysis of secondary metabolism gene families (smCOGs). 
This analysis attempts to allocate each gene in the detected gene clusters to a secondary metabolism-specific gene 
family using profile hidden Markov models specific for the conserved sequence region characteristic of this family. 
Additionally, a phylogenetic tree is constructed of each gene together with the (max. 100) sequences of the smCOG seed alignment.


For the most thorough genome analysis, we provide genome-wide PFAM HMM analysis of all genes in the genome through modules of the CLUSEAN pipeline. 
Of course, some regions important to secondary metabolism may have been missed in the gene cluster identification stage 
(e.g. because they represent the biosynthetic pathway of a yet unknown secondary metabolite). 
Therefore, when genome-wide PFAM HMM analysis is selected, the PFAM frequencies are also used to find all genome regions in which PFAM domains typical for secondary metabolism are overrepresented.


**References**

Marnix H. Medema, Kai Blin, Peter Cimermancic, Victor de Jager, Piotr Zakrzewski, Michael A. Fischbach, Tilmann Weber,