comparison bed_to_gff.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_bed2gff" name="BED-to-GFF" version="2.0.0">
2 <description>converter</description>
3 <command interpreter="python">bed_to_gff.py $inf_bed &gt; $gff_format
4 </command>
5 <inputs>
6 <param format="bed" name="inf_bed" type="data" label="Convert this query" help="Provide genome annotation in 12 column BED format."/>
7 </inputs>
8 <outputs>
9 <data format="gff3" name="gff_format" label="${tool.name} on ${on_string}: Converted" />
10 </outputs>
11 <tests>
12 <test>
13 <param name="inf_bed" value="ccds_genes.bed" />
14 <output name="gff_format" file="ccds_genes.gff3" />
15 </test>
16 <test>
17 <param name="inf_bed" value="hs_2009.bed" />
18 <output name="gff_format" file="hs_2009.gff3" />
19 </test>
20 </tests>
21 <help>
22
23 **What it does**
24
25 This tool converts data from a 12 column UCSC wiggle BED format to GFF3 (scroll down for format description).
26
27 --------
28
29 **Example**
30
31 - The following data in UCSC Wiggle BED format::
32
33 chr1 11873 14409 uc001aaa.3 0 + 11873 11873 0 3 354,109,1189, 0,739,1347,
34
35 - Will be converted to GFF3::
36
37 ##gff-version 3
38 chr1 bed2gff gene 11874 14409 0 + . ID=Gene:uc001aaa.3;Name=Gene:uc001aaa.3
39 chr1 bed2gff transcript 11874 14409 0 + . ID=uc001aaa.3;Name=uc001aaa.3;Parent=Gene:uc001aaa.3
40 chr1 bed2gff exon 11874 12227 0 + . Parent=uc001aaa.3
41 chr1 bed2gff exon 12613 12721 0 + . Parent=uc001aaa.3
42 chr1 bed2gff exon 13221 14409 0 + . Parent=uc001aaa.3
43
44 --------
45
46 **About formats**
47
48 **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:
49
50 The first three BED fields (required) are::
51
52 1. chrom - The name of the chromosome (e.g. chr1, chrY_random).
53 2. chromStart - The starting position in the chromosome. (The first base in a chromosome is numbered 0.)
54 3. chromEnd - The ending position in the chromosome, plus 1 (i.e., a half-open interval).
55
56 The additional BED fields (optional) are::
57
58 4. name - The name of the BED line.
59 5. score - A score between 0 and 1000.
60 6. strand - Defines the strand - either '+' or '-'.
61 7. thickStart - The starting position where the feature is drawn thickly at the Genome Browser.
62 8. thickEnd - The ending position where the feature is drawn thickly at the Genome Browser.
63 9. reserved - This should always be set to zero.
64 10. blockCount - The number of blocks (exons) in the BED line.
65 11. blockSizes - A comma-separated list of the block sizes. The number of items in this list should correspond to blockCount.
66 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.
67
68 **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::
69
70 1. seqid - Must be a chromosome or scaffold or contig.
71 2. source - The program that generated this feature.
72 3. type - The name of this type of feature. Some examples of standard feature types are "gene", "CDS", "protein", "mRNA", and "exon".
73 4. start - The starting position of the feature in the sequence. The first base is numbered 1.
74 5. stop - The ending position of the feature (inclusive).
75 6. score - A score between 0 and 1000. If there is no score value, enter ".".
76 7. strand - Valid entries include '+', '-', or '.' (for don't know/care).
77 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 '.'.
78 9. attributes - All lines with the same group are linked together into a single item.
79
80 --------
81
82 **Copyright**
83
84 2009-2014 Max Planck Society, University of Tübingen &amp; Memorial Sloan Kettering Cancer Center
85
86 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)
87
88 </help>
89 </tool>