Kaarme is a memory-efficient hash table implementation for long k-mers. In this software, its functionality is demonstrated with a k-mer counter.
Kaarme k-mer counter is (partially) multithreaded, and counts only canonical k-mers.
Supported input types are fasta and plain text (one read per line) files.
- CMake 3.10
- C++17
This program has been tested only on OSx and Linux-based OS
Run the following commands:
git clone git@github.com:Denopia/kaarme.git
cd kaarme
mkdir build
cd build
cmake -S .. -B .
cmake --build .
Run the following command:
./kaarme [OPTIONS] INPUT KLEN TABLE_SIZE
Parameters are:
Positionals:
INPUT TEXT REQUIRED Input file
KLEN INT REQUIRED k-mer length
Options:
-h,--help Print this help message and exit
-m,--hash-table-type INT Hash table type: 0 for plain and 2 for kaarme (def. 2)
-a,--min-k-abu UINT Minimum abundance threshold for the output k-mers (def. 2)
-t,--threads UINT Number of working threads (def. 3)
-o,--output-file TEXT Output file where the k-mer counts will be stored
-b,--use-bfilter Use bloom filters to discard unique k-mers
-f,--bfilter-fpr FLOAT Bloom filter false positive rate (def. 0.01)
[Exactly 1 of the following options is required]
Excluding params:
-s,--hash-tab-size UINT Hash table size
-u,--unq-kmers UINT Estimated number of unique k-mers
Kaarme hash table has two modes: one that uses Bloom filter to filter out k-mers that occur less than twice (--use-bfilter flag), and other that does not use a Bloom filter. In the case you want to use Bloom filter, you must provide an estimate for the number of unique k-mers (--unq-kmers parameter). If you do not wish to use the Bloom filter, you must provide a size for the hash table as parameter -s. If Bloom filter mode is used, you can provide the false positive rate as parameter -f. Otherwise, default value 0.01 is used.
Use the installation instructions to install the program. Then run the following (assuming you are in the project root directory and Kaarme is installed in build directory):
./build/kaarme example/ecoli1x.fasta 51 -s 8000000 -t 3 -o example/ecoli1x-51mers.txt
Now the example directory should contain a file called ecoli1x-51mers.txt with all 51-mers that appear at least twice in ecoli1x.fasta.
The example above uses the Kaarme without Bloom filtering. To use Bloom filtering, run the following example:
./build/kaarme example/ecoli1x.fasta 51 -t 3 -u 4000000 --use-bfilter -o example/ecoli1x-51mers.txt
This implementation also includes a basic k-mer counter using a plain hash table instead of the Kaarme hash table. This plain hash table k-mer counter can be used by setting the hash table type parameter -m value to 0. To run the above examples using the plain hash table, run the following without Bloom filter:
./build/kaarme example/ecoli1x.fasta 51 -s 8000000 -t 3 -m 0 -o example/ecoli1x-51mers.txt
And the following for plain hash table with Bloom filter:
./build/kaarme example/ecoli1x.fasta 51 -t 3 -m 0 -u 4000000 --use-bfilter -o example/ecoli1x-51mers.txt
TBD