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Subcommand: chunkify
Chunkify a set of fasta files and create abundance maps.
Usage: gappa prepare chunkify [options]
Input | |
---|---|
--fasta-path |
Required. TEXT ... List of fasta files or directories to process. For directories, only files with the extension .(fasta|fas|fsa|fna|ffn|faa|frn) are processed. |
Settings | |
--chunk-size |
UINT=50000 Number of sequences per chunk file. |
--min-abundance |
UINT=1 Minimum abundance of a single sequence. Sequences below are filtered out. |
--hash-function |
TEXT in {MD5,SHA1,SHA256}=SHA1 Hash function for re-naming and identifying sequences. |
Output | |
--chunks-out-dir |
TEXT=. Directory to write chunks files to |
--chunk-file-prefix |
TEXT=chunk_ File prefix for chunk files |
--abundances-out-dir |
TEXT=. Directory to write abundances files to |
--abundance-file-prefix |
TEXT=abundances_ File prefix for abundance files |
The command takes one or more fasta files as input, e.g., each representing an environmental sample. It then writes out numbered chunks files of equal size, containing the unique sequences of the input. For each input file, it also writes an abundance map file, which stores the per-sequence abundances in the input. In order to identify unique sequences, it uses a hash value of the sequence data, which is also assigned as a new name to the sequences in the chunks.
The produced chunk files are intended to be used with phylogenetic placement next (after potentially aligning them first to the reference). Using chunks of equal size ensures relatively stable run times for each chunk, so that large datasets can be processed efficiently on a computer cluster. Furthermore, as the chunks only contain unique sequences, compute time is further reduced.
After finishing phylogentic placement, the unchunkify command then takes the per-chunk placement files as well as the abundance map files produced here, and creates placement files for each of the original input files, with all abundances and original sequences names restored. Thus, the combination of these two commands achieves the same effect as placing each input file separately, but lowers computational cost and maximizes load balancing.
Module analyze
- correlation
- dispersion
- edgepca
- imbalance-kmeans
- krd
- phylogenetic-kmeans
- placement-factorization
- squash
Module edit
Module examine
Module prepare
Module simulate
Module tools