comparison gff_to_bed.xml @ 5:6e589f267c14

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author devteam
date Tue, 04 Nov 2014 12:15:19 -0500
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4:619e0fcd9126 5:6e589f267c14
1 <tool id="fml_gff2bed" name="GFF-to-BED" version="2.0.0">
2 <description>converter</description>
3 <command interpreter="python">gff_to_bed.py $inf_gff &gt; $bed_format
4 </command>
5 <inputs>
6 <param format="gtf,gff,gff3" name="inf_gff" type="data" label="Convert this query" help="Provide genome annotation file in GFF, GTF, GFF3."/>
7 </inputs>
8 <outputs>
9 <data format="bed" name="bed_format" label="${tool.name} on ${on_string}: Converted" />
10 </outputs>
11 <tests>
12 <test>
13 <param name="inf_gff" value="Aly_JGI.gff3" />
14 <output name="bed_format" file="Aly_JGI.bed" />
15 </test>
16 <test>
17 <param name="inf_gff" value="MB7_3R.gff3" />
18 <output name="bed_format" file="MB7_3R.bed" />
19 </test>
20 </tests>
21 <help>
22
23 **What it does**
24
25 This tool converts gene transcript annotation from GTF or GFF or GFF3 to UCSC wiggle 12 column BED format.
26
27 --------
28
29 **Example**
30
31 - The following data in GFF3::
32
33 ##gff-version 3
34 chr1 protein_coding gene 11874 14409 0 + . ID=Gene:uc001aaa.3;Name=Gene:uc001aaa.3
35 chr1 protein_coding transcript 11874 14409 0 + . ID=uc001aaa.3;Name=uc001aaa.3;Parent=Gene:uc001aaa.3
36 chr1 protein_coding exon 11874 12227 0 + . Parent=uc001aaa.3
37 chr1 protein_coding exon 12613 12721 0 + . Parent=uc001aaa.3
38 chr1 protein_coding exon 13221 14409 0 + . Parent=uc001aaa.3
39
40 - Will be converted to UCSC Wiggle BED format::
41
42 chr1 11874 14409 uc001aaa.3 0 + 11874 14409 0 3 354,109,1189, 0,739,1347,
43
44 --------
45
46 **About formats**
47
48 **GFF3 format** General 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::
49
50
51 1. seqid - Must be a chromosome or scaffold or contig.
52 2. source - The program that generated this feature.
53 3. type - The name of this type of feature. Some examples of standard feature types are "gene", "CDS", "protein", "mRNA", and "exon".
54 4. start - The starting position of the feature in the sequence. The first base is numbered 1.
55 5. stop - The ending position of the feature (inclusive).
56 6. score - A score between 0 and 1000. If there is no score value, enter ".".
57 7. strand - Valid entries include '+', '-', or '.' (for don't know/care).
58 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 '.'.
59 9. attributes - All lines with the same group are linked together into a single item.
60
61 **BED format** Browser Extensible Data format was designed at UCSC for displaying data tracks in the Genome Browser. It has three required fields and several additional optional ones:
62
63 The first three BED fields (required) are::
64
65 1. chrom - The name of the chromosome (e.g. chr1, chrY_random).
66 2. chromStart - The starting position in the chromosome. (The first base in a chromosome is numbered 0.)
67 3. chromEnd - The ending position in the chromosome, plus 1 (i.e., a half-open interval).
68
69 The additional BED fields (optional) are::
70
71 4. name - The name of the BED line.
72 5. score - A score between 0 and 1000.
73 6. strand - Defines the strand - either '+' or '-'.
74 7. thickStart - The starting position where the feature is drawn thickly at the Genome Browser.
75 8. thickEnd - The ending position where the feature is drawn thickly at the Genome Browser.
76 9. reserved - This should always be set to zero.
77 10. blockCount - The number of blocks (exons) in the BED line.
78 11. blockSizes - A comma-separated list of the block sizes. The number of items in this list should correspond to blockCount.
79 12. blockStarts - A comma-separated list of block starts. All of the blockStart positions should be calculated relative to chromStart. The number of items in this list should correspond to blockCount.
80
81 --------
82
83 **Copyright**
84
85 2009-2014 Max Planck Society, University of Tübingen &amp; Memorial Sloan Kettering Cancer Center
86
87 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)
88
89 </help>
90 </tool>