Mercurial > repos > galaxyp > megahit
comparison megahit_contig2fastg.xml @ 0:b379f4728136 draft default tip
planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/megahit_contig2fastg commit 55d148dd4fae2d0156cc0ab680fd4f00efc6f242
author | galaxyp |
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date | Thu, 08 Nov 2018 16:08:02 -0500 |
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1 <?xml version='1.0' encoding='utf-8'?> | |
2 <tool id="megahit_contig2fastg" name="MEGAHIT Contig2fastg" version="@VERSION@"> | |
3 <description>for converting MEGAHIT's contigs to fastg</description> | |
4 <macros> | |
5 <token name="@VERSION@">1.1.2</token> | |
6 </macros> | |
7 <requirements> | |
8 <requirement type="package" version="@VERSION@">megahit</requirement> | |
9 </requirements> | |
10 <version_command>megahit --version</version_command> | |
11 <command detect_errors="exit_code"><![CDATA[ | |
12 megahit_toolkit contig2fastg | |
13 '${kmer}' | |
14 '${contigs}' > '${fastg}' | |
15 ]]></command> | |
16 <inputs> | |
17 <param name="contigs" type="data" format="fastq,fastqsanger,fasta,fastq.gz,fastqsanger.gz" multiple="true" label="Single-end file(s)" help="FASTQ/FASTA/FASTQ.GZ files accepted" /> | |
18 <param name="kmer" type="integer" value="99" label="K-mer length" /> | |
19 </inputs> | |
20 <outputs> | |
21 <data format="txt" name="fastg" label="Conversion to FASTG with ${tool.name} on ${on_string}" /> | |
22 </outputs> | |
23 <tests> | |
24 <test> | |
25 <param name="contigs" value="k21.contigs.fa" ftype="fasta" /> | |
26 <param name="kmer" value="21"/> | |
27 <output name="fastg"> | |
28 <assert_contents> | |
29 <has_text text=">NODE_1_length_576" /> | |
30 </assert_contents> | |
31 </output> | |
32 </test> | |
33 </tests> | |
34 <help><![CDATA[ | |
35 | |
36 **MEGAHIT_toolkit contig2fastg** | |
37 | |
38 Contig2fastg is a subprogram within the MEGAHIT toolkit. It converts MEGAHIT's k*.contigs.fa to fastg format that can be viewed by Bandage. | |
39 | |
40 **MEGAHIT** | |
41 | |
42 MEGAHIT is a single node assembler for large and complex metagenomics NGS reads, such as soil. It makes use of succinct de Bruijn graph (SdBG) to achieve low memory assembly. MEGAHIT can optionally utilize a CUDA-enabled GPU to accelerate its SdBG contstruction. The GPU-accelerated version of MEGAHIT has been tested on NVIDIA GTX680 (4G memory) and Tesla K40c (12G memory) with CUDA 5.5, 6.0 and 6.5. | |
43 | |
44 -------- | |
45 | |
46 **Project links:** | |
47 | |
48 https://github.com/voutcn/megahit | |
49 https://github.com/voutcn/megahit/blob/master/tools/toolkit.cpp | |
50 | |
51 | |
52 ]]></help> | |
53 <citations> | |
54 <citation type="doi">10.1093/bioinformatics/btv033</citation> | |
55 </citations> | |
56 </tool> |