recipe mosca

MOSCA - Meta-Omics Software for Community Analysis

Homepage

https://github.com/iquasere/MOSCA

Documentation

https://github.com/iquasere/MOSCA/blob/master/README.md

License

GPL / GNU General Public License v3 (GPL-3.0)

Recipe

/mosca/meta.yaml

MOSCA (portuguese for fly) is a pipeline designed for performing metagenomics (MG), metatranscriptomics (MT) and metaproteomics (MP) integrated data analysis, in a mostly local and fully automated workflow. Metagenomics is used to build a reference database for MT and MP, beginning with preprocessing of data for removal of Illumina adapters and lower quality regions, folowed by assembly of reads into contigs, gene calling on the contigs and homology-based and domain-based annotation of identified proteins, using the UniProt and COG databases, respectively. If available, MT reads are then aligned to the ORFs for gene expression quantification, and MP spectra are submitted for Peptide-to-Spectrum matching, with the annotated ORFs as reference database. Final steps include differential expression analysis for both MT and MP, and metabolic pathways analysis through KEGG Pathways.

package mosca

Versions

1.2.1-0,  1.2.0-0,  1.1.1-0,  1.1.0-0

Depends

• bioconductor-deseq2 >=1.10.1

• bioconductor-edger >=3.14.0

• biopython >=1.78

• blast >=2.5.0

• bowtie2 2.3.*

• checkm-genome >=1.1.0

• diamond >=2.0.2

• fastqc >=0.11.9

• fraggenescan >=1.31

• htseq >=0.12.4

• keggcharter >=0.1.1

• krona >=2.7.1

• lxml >=4.6.1

• maxbin2 >=2.2.7

• maxquant >=1.6.10

• megahit >=1.2.9

• openpyxl >=3.0.3

• pandas >=1.1.4

• perl

• progressbar33 >=2.4

• python

• quast >=5.0.2

• r-optparse

• r-pheatmap

• r-rcolorbrewer >=1.1.2

• recognizer >=1.3.2

• reportlab >=3.5.45

• samtools >=1.11

• scikit-learn >=0.23.1

• seqkit >=0.13.2

• seqtk

• snakemake >=5.27.4

• sortmerna 2.1b.*

• spades >=3.14.1

• svn >=1.9.7

• tqdm >=4.33.0

• trimmomatic >=0.39

• upimapi >=1.0.4

• xlrd >=0.9.0

• xlsxwriter >=1.3.7

Required By

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install mosca

and update with:

conda update mosca

or use the docker container:

docker pull quay.io/biocontainers/mosca:<tag>

(see mosca/tags for valid values for <tag>)

Link to this page

Render an badge with the following MarkDown:

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