https://github.com/pnnl/mercat

MerCat: python code for versatile k-mer counting and diversity estimation for database independent property analysis for meta -ome data
https://github.com/pnnl/mercat

dask database-independent-analysis diversity diversity-estimation divideandconquer fastq k-mer-counting k-mer-frequency kmer-frequency-count metagenomic-analysis metatranscriptomic-analysis nucleotides plotly protein python

Last synced: 17 days ago
JSON representation

MerCat: python code for versatile k-mer counting and diversity estimation for database independent property analysis for meta -ome data

• Host: GitHub
• URL: https://github.com/pnnl/mercat
• Owner: pnnl
• License: other
• Created: 2017-02-10T14:45:02.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2022-11-30T15:50:51.000Z (over 2 years ago)
• Last Synced: 2025-03-26T00:41:31.190Z (about 1 month ago)
• Topics: dask, database-independent-analysis, diversity, diversity-estimation, divideandconquer, fastq, k-mer-counting, k-mer-frequency, kmer-frequency-count, metagenomic-analysis, metatranscriptomic-analysis, nucleotides, plotly, protein, python
• Language: Python
• Homepage: https://github.com/pnnl/mercat
• Size: 2.7 MB
• Stars: 18
• Watchers: 5
• Forks: 13
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

Awesome Lists containing this project

README

        
# This version of MerCat is depreciated please use the new updated version

# https://github.com/raw-lab/mercat2

===========================================================================================

###### MerCat: python code for versatile k-mer counter and diversity estimator for database independent property analysis (DIPA)  obtained from metagenomic and/or metatranscriptomic sequencing data

![GitHub Logo](mercat_workflow.jpg)

  

Installing MerCat: 

 - Available via Anaconda: Enable BioConda repo and run `conda install mercat`  

 - We do not have a pip installer available as of now. If you would like to use pip, please install the 

   modules listed in `dependencies.txt` via pip and run `python setup.py install` for setting up mercat.

 

Usage:

-----

 * -i I        path-to-input-file

 * -f F        path-to-folder-containing-input-files

 * -k K        kmer length

 * -n N        no of cores [default = all]

 * -c C        minimum kmer count [default = 10]

 * -pro        run mercat on protein input file specified as .faa 

 * -q          tell mercat that input file provided are raw nucleotide reads as [.fq, .fastq]

 * -p          run prodigal on nucleotide assembled contigs. Must be one of ['.fa', '.fna', '.ffn', '.fasta']

 * -t [T]      Trimmomatic options

 * -s          Data split size for large files (default is 100 Mb file size) 

 * -h, --help  show this help message

By default mercat assumes that inputs provided is one of ['.fa', '.fna', '.ffn', '.fasta']

> Example: To compute all 3-mers, run `mercat -i test.fa -k 3 -n 8 -c 10 -p`          

 

 The above command:

* Runs prodigal on `test.fa`, then runs mercat on the resulting protein file.            

* Results are generally stored in input-file-name_{protein|nucleotide}.csv and input-file-name_{protein|nucleotide}_summary.csv  

   * `test_protein.csv` and `test_protein_summary.csv` in this example  

* `test_protein_summary.csv` contains kmer frequency count, pI, Molecular Weight, and Hydrophobicity metrics for all unique kmers across all sequences in `test.fa`

* `test_protein_diversity_metrics.txt` containing the alpha diversity metrics.

* `test_protein.csv` contains kmer frequency count, pI, Molecular Weight, and Hydrophobicity metrics for individual sequences. 

  > NOTE: We disabled the code that generates this file since computing k-mer counts for individual 

sequences was getting very expensive in terms of time & memory usage for large input files.

Other usage examples:

---------------------

* `mercat -i test.fq -k 3 -n 8 -c 10 -q`  

   Runs mercat on raw nucleotide read (.fq or .fastq) 

   

*  `mercat -i test.fq -k 3 -n 8 -c 10 -q -t`  

   Runs trimmomatic on raw nucleotide reads (.fq or .fastq), then runs mercat on the trimmed nucleotides

    

*  `mercat -i test.fq -k 3 -n 8 -c 10 -q -t 20`  

   Same as above but can provide the quality option to trimmomatic

   

*  `mercat -i test.fq -k 3 -n 8 -c 10 -q -t 20 -p`

   Run trimmomatic on raw nucleotide reads, then run prodigal on the trimmed read to produce a protein file which is then processed by mercat

      

*  `mercat -i test.fna -k 3 -n 8 -c 10`  

   Run mercat on nucleotide input - one of ['.fa', '.fna', '.ffn', '.fasta']

    

*   `mercat -i test.fna -k 3 -n 8 -c 10 -p`  

    Run prodigal on nucleotide input, generate a .faa protein file and run mercat on it

    

*   `mercat -i test.faa -k 3 -n 8 -c 10 -pro`  

    Run mercat on a protein input (.faa)

* All the above examples can also be used with  `-f input-folder` instead of `-i input-file` option

  -  Example:  `mercat  -f /path/to/input-folder -k 3 -n 8 -c 10` --- Runs mercat on all inputs in the folder

  

* To save working memory (RAM) on low RAM computers or >2 GB files use '-s option' to split/chunk the file 

  - Example: `mercat -i test.fna -k 3 -n 8 -c 10 -s 50` --Runs mercat in nucleotide mode splitting file into 50 MB pieces 

  

  

Citing Mercat

-------------

If you are publishing results obtained using MerCat, please cite:

White III RA, Panyala A, Glass K, Colby S, Glaesemann KR, Jansson C, Jansson JK. (2017) MerCat: a versatile k-mer counter and diversity estimator for database-independent property analysis obtained from metagenomic and/or metatranscriptomic sequencing data. PeerJ Preprints 5:e2825v1 https://doi.org/10.7287/peerj.preprints.2825v1

CONTACT

-------

Please send all queries to Richard Allen White III  <[[email protected]]([email protected])> or <[[email protected]]([email protected])>