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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.

• -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.

• 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

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

Please send all queries to Richard Allen White III <rwhit101@uncc.edu> or <raw937@gmail.com>