view gbk_to_gff.xml @ 7:ee541c1852da

Uploaded version 2.1.0
author vipints
date Thu, 23 Apr 2015 17:43:11 -0400
parents 6e589f267c14
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<tool id="fml_gbk2gff" name="GBK-to-GFF" version="2.0.0">
  <description>converter</description>
  	<command interpreter="python">gbk_to_gff.py $inf_gbk &gt; $gff_format
  	</command>
  	<inputs>
		<param format="gb,gbk,genbank,txt" name="inf_gbk" type="data" label="Convert this query" help="GenBank flat file format consists of an annotation section and a sequence section."/>
  	</inputs>
	<outputs>
		<data format="gff3" name="gff_format" label="${tool.name} on ${on_string}: Converted"/>
  	</outputs>
	<tests>
        <test>
                <param name="inf_gbk" value="s_cerevisiae_SCU49845.gbk" />
                <output name="gff_format" file="s_cerevisiae_SCU49845.gff3" />
        </test>
	</tests>
  	<help>
    
**What it does**

This tool converts data from a GenBank_ flat file format to GFF (scroll down for format description).

.. _GenBank: http://www.ncbi.nlm.nih.gov/genbank/ 

------

**Example**

- The following data in GenBank format::
	
    LOCUS       NM_001202705            2406 bp    mRNA    linear   PLN 28-MAY-2011
    DEFINITION  Arabidopsis thaliana thiamine biosynthesis protein ThiC (THIC)
                mRNA, complete cds.
    ACCESSION   NM_001202705
    VERSION     NM_001202705.1  GI:334184566.........
    FEATURES             Location/Qualifiers
         source          1..2406
                         /organism="Arabidopsis thaliana"
                         /mol_type="mRNA"
                         /db_xref="taxon:3702"........
         gene            1..2406
                         /gene="THIC"
                         /locus_tag="AT2G29630"
                         /gene_synonym="PY; PYRIMIDINE REQUIRING; T27A16.27;........
    ORIGIN
        1 aagcctttcg ctttaggctg cattgggccg tgacaatatt cagacgattc aggaggttcg
        61 ttcctttttt aaaggaccct aatcactctg agtaccactg actcactcag tgtgcgcgat
        121 tcatttcaaa aacgagccag cctcttcttc cttcgtctac tagatcagat ccaaagcttc
        181 ctcttccagc tatggctgct tcagtacact gtaccttgat gtccgtcgta tgcaacaaca
    //


- Will be converted to GFF3::

    ##gff-version 3
    NM_001202705    gbk_to_gff chromosome      1       2406    .       +       1       ID=NM_001202705;Alias=2;Dbxref=taxon:3702;Name=NM_001202705
    NM_001202705    gbk_to_gff gene    1       2406    .       +       1       ID=AT2G29630;Dbxref=GeneID:817513,TAIR:AT2G29630;Name=THIC
    NM_001202705    gbk_to_gff mRNA    192     2126    .       +       1       ID=AT2G29630.t01;Parent=AT2G29630
    NM_001202705    gbk_to_gff CDS     192     2126    .       +       1       ID=AT2G29630.p01;Parent=AT2G29630.t01
    NM_001202705    gbk_to_gff exon    192     2126    .       +       1       Parent=AT2G29630.t01

------

**About formats** 

**GenBank format** An example of a GenBank record may be viewed here_

.. _here: http://www.ncbi.nlm.nih.gov/Sitemap/samplerecord.html 

**GFF3** Generic Feature Format is a format for describing genes and other features associated with DNA, RNA and Protein sequences. GFF3 lines have nine tab-separated fields::

    1. seqid - Must be a chromosome or scaffold or contig.
    2. source - The program that generated this feature.
    3. type - The name of this type of feature. Some examples of standard feature types are "gene", "CDS", "protein", "mRNA", and "exon".
    4. start - The starting position of the feature in the sequence. The first base is numbered 1.
    5. stop - The ending position of the feature (inclusive).
    6. score - A score between 0 and 1000. If there is no score value, enter ".".
    7. strand - Valid entries include '+', '-', or '.' (for don't know/care).
    8. phase - If the feature is a coding exon, frame should be a number between 0-2 that represents the reading frame of the first base. If the feature is not a coding exon, the value should be '.'.
    9. attributes - All lines with the same group are linked together into a single item.

--------

**Copyright**

2009-2014 Max Planck Society, University of Tübingen &amp; Memorial Sloan Kettering Cancer Center

Sreedharan VT, Schultheiss SJ, Jean G, Kahles A, Bohnert R, Drewe P, Mudrakarta P, Görnitz N, Zeller G, Rätsch G. Oqtans: the RNA-seq workbench in the cloud for complete and reproducible quantitative transcriptome analysis. Bioinformatics 10.1093/bioinformatics/btt731 (2014)

	</help>
</tool>