This is the code for the paper Succinct k-mer Set Representations Using Subset Rank Queries on the Spectral Burrows-Wheeler Transform (SBWT). The repository includes implementations of the various SBWT variants described in the paper. The data structures answer k-mer membership queries on the input data. Note that contrary to many other k-mer membership data structures, our code is not aware of DNA reverse complements. That is, it considers a k-mer and its reverse complement as separate k-mers.
This construction algorithm is based on the lightning-fast k-mer counter KMC. We call the KMC binaries directly from our code. The construction is very disk-heavy, so it is recommended to run construction code off a fast SSD drive.
The following commands have been tested to successfully build SBWT on a clean Ubuntu 18.04 Docker image.
apt-get update
apt-get install -y g++ gcc cmake git python3-dev g++-8 libz-dev
git clone https://github.com/algbio/SBWT
cd SBWT/build
cmake .. -DCMAKE_CXX_COMPILER=g++-8 -DMAX_KMER_LENGTH=32
make -j8
Change the parameter -DMAX_KMER_LENGTH=32 to increase the maximum allowed k-mer length, up to 255. Larger values lead to slower construction and higher disk usage during construction.
Troubleshooting: If you run into problems involving the <filesystem> header, you probably need to update your compiler. The compiler g++-8 should be sufficient. Install a new compiler and direct CMake to use it with the -DCMAKE_CXX_COMPILER option. For example, to set the compiler to g++-8, run CMake with the option -DCMAKE_CXX_COMPILER=g++-8.
Note: the Elias-Fano variants make use of the _pext_u64 instruction in the BMI2 instruction set. Older CPUs might not support this instruction. In that case, we fall back to a simple software implementation, which will ruin the performance of the Elias-Fano variants (those whose variant name starts with "mef").
Below is the command to build the SBWT for input data example_data/coli3.fna provided in this repository, with k = 30. The index is written to the file index.sbwt.
./build/bin/sbwt build -i example_data/coli3.fna -o index.sbwt -k 30
This builds the default variant, which is the plain matrix SBWT. Other variant can be specified with the --variant option.
The list of all command line options and parameters is below:
Construct an SBWT variant.
Usage:
build [OPTION...]
-i, --in-file arg The input sequences as a FASTA or FASTQ
file, possibly gzipped. If the file
extension is .txt, the file is interpreted
as a list of input files, one file on each
line. All input files must be in the same
format.
-o, --out-file arg Output file for the constructed index.
-k, --kmer-length arg The k-mer length.
--variant arg The SBWT variant to build. Available
variants: plain-matrix rrr-matrix
mef-matrix plain-split rrr-split mef-split
plain-concat mef-concat plain-subsetwt
rrr-subsetwt (default: plain-matrix)
--add-reverse-complements
Also add the reverse complement of every
k-mer to the index. Warning: this creates a
temporary reverse-complemented duplicate of
each input file before construction. Make
sure that the directory at --temp-dir can
handle this amount of data. If the input is
gzipped, the duplicate will also be
compressed, which might take a while.
--no-streaming-support Save space by not building the streaming
query support bit vector. This leads to
slower queries.
-t, --n-threads arg Number of parallel threads. (default: 1)
-a, --min-abundance arg Discard all k-mers occurring fewer than
this many times. By default we keep all
k-mers. Note that we consider a k-mer
distinct from its reverse complement.
(default: 1)
-b, --max-abundance arg Discard all k-mers occurring more than this
many times. (default: 1000000000)
-m, --ram-gigas arg RAM budget in gigabytes (not strictly
enforced). Must be at least 2. (default: 2)
-d, --temp-dir arg Location for temporary files. (default: .)
-h, --help Print usage
To query for existence of all k-mers in an index for all sequences in a fastq-file, run the following command:
./build/bin/sbwt search -i index.sbwt -q example_data/queries.fastq -o out.txt
This prints for each query of length n in the input a line containing n-k+1 space-separated integers, which are the ranks of the columns representing the k-mer in the index. If the k-mer is not found, -1 is printed. If the index was built streaming support (which is the default), the faster streaming query algorithm is automatically used. The full options are:
Query all k-mers of all input reads.
Usage:
search [OPTION...]
-o, --out-file arg Output filename.
-i, --index-file arg Index input file.
-q, --query-file arg The query in FASTA or FASTQ format, possibly
gzipped. Multi-line FASTQ is not supported. If the
file extension is .txt, this is interpreted as a
list of query files, one per line. In this case,
--out-file is also interpreted as a list of output
files in the same manner, one line for each input
file.
-z, --gzip-output Writes output in gzipped form. This can shrink the
output files by an order of magnitude.
-h, --help Print usage
The API for the SBWT is still in the works. Do not expect a stable API at this point.
The SBWT can be constructed and queried using the SBWT class. The class is templatized by the underlying subset rank support structure. See here for types of subset rank query data structures are suitable for the template parameter. See https://github.com/algbio/SBWT/tree/master/api_examples for a self-contained piece of code demonstrating the API using the bit matrix SBWT representation.
git submodule init
git submodule update
# Build googletest
cd googletest
mkdir build
cd build
cmake ..
make
# Build SBWT
cd ../../build
cmake .. -DCMAKE_BUILD_TYPE=Debug -DBUILD_TESTS=1 -DMAX_KMER_LENGTH=32
make
This will build the executable ./build/bin/sbwt_tests. Make sure to run the test executable from the root of the repository, or otherwise it will not find the example data in ./example_data.
The command-line parsing and the gzip support are implemented using cxxopts and zstr respectively.