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bloomfilter

The BTL C/C++ Common Bloom filters for bioinformatics projects, as well as any APIs created for other programming languages.

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usage example (C++)

Fast Bloom filter loading using the rolling hash function.

#include "BloomFilter.hpp"
#include <vector>
#include <string>
#include "vendor/ntHashIterator.hpp"

using namespace std;

int main(int argc, char** argv)
{
    /* test sequence */
    const string seq = "TAGAATCACCCAAAGA";
    /* k-mer size */
    const unsigned k = 5;
    /* number of Bloom filter hash functions */
    const unsigned numHashes = 4;
    /* size of Bloom filter (in bits) */
    const unsigned size = 1000;
	//Building the filter
	{
		/* init Bloom filter */
		BloomFilter bloom(size, numHashes, k);

		/* init rolling hash state and compute hash values for first k-mer */
		ntHashIterator itr(seq, numHashes, k);
		while (itr != itr.end()) {
			bloom.insert(*itr);
			++itr;
		}
		/* store the bloom filter */
		bloom.storeFilter("filterPathname.bf");
	}

	//After building
	{
		/* load the bloom filter */
		BloomFilter bloom("filterPathname.bf");

		/* query the bloom filter */

		/* init rolling hash state and compute hash values for first k-mer */
		ntHashIterator itr(seq, numHashes, k);
		while (itr != itr.end()) {
			bloom.contains(*itr);
			++itr;
		}
	}
	return 0;
}

Fast Counting Bloom filter loading using the rolling hash function.

#include "CountingBloomFilter.hpp"
#include <vector>
#include <string>
#include "vendor/ntHashIterator.hpp"

using namespace std;

int main(int argc, char** argv)
{
    /* test sequence */
    const string seq = "TAGAATCACCCAAAGA";
    /* k-mer size */
    const unsigned k = 5;
    /* number of Bloom filter hash functions */
    const unsigned numHashes = 4;
    /* size of Bloom filter (in bytes) */
    size_t size = 1000;
    /* counts to threshold bloom filter on*/
    const unsigned threshold = 1;
	//Building the filter
	{
		/* init Bloom filter */
		CountingBloomFilter<uint8_t> bloom(size, numHashes, k, threshold);

		/* init rolling hash state and compute hash values for first k-mer */
		ntHashIterator itr(seq, numHashes, k);
		while (itr != itr.end()) {
			bloom.insert(*itr);
			++itr;
		}
		/* store the bloom filter */
		bloom.storeFilter("filterPathname.bf");
	}

	//After building
	{
		/* load the bloom filter */
		CountingBloomFilter<uint8_t> bloom("filterPathname.bf", threshold);

		/* query the bloom filter */

		/* init rolling hash state and compute hash values for first k-mer */
		ntHashIterator itr(seq, numHashes, k);
		while (itr != itr.end()) {
			bloom.contains(*itr);
			++itr;
		}
	}
	return 0;
}

files

• BloomFilter.hpp: main Bloom filter class
• CountingBloomFilter.hpp: Counting Bloom filter class
• RollingHashIterator.h: Enable rolling hashing on a string
• RollingHash.h: rolling hash interface (required by RollingHashIterator.h)
• rolling.h: rolling hash function (required by BloomFilter.hpp and RollingHash.h)
• Tests/Unit: unit tests
• Tests/AdHoc: ad-hoc tests

unit tests

The unit tests may be compiled and run with:

$ ./autogen.sh
$ ./configure
$ make check

To see more detailed output for the individual tests, run the binaries in Tests/Unit from the command line. (The ad-hoc tests in Tests/AdHoc may also be run in this way.)

acknowledgements

This projects uses:

• CATCH unit test framework for C/C++
• nthash rolling hash implementation by Hamid Mohamadi
• cpptoml TOML parser and serializer implemented by Chase Geigle

Bloom filter file format

The specification of the Bloom filter file format is as follows:

1. magic header string

• Description: bf magic string
• Type: string
• Value: BTLBloomFilter_v1 or BTLCountingBloomFilter_v1

2. header

• Description: Plain header text
• Type: string
• Value:
  • size
    • Description: The size of Bloom filter
    • Type: size_t
    • Value:
  • sizeInBytes
    • Description: The size of Bloom filter in bytes
    • Type: size_t
    • Value:
  • hashNum
    • Description: number of hashes
    • Type: unsigned
    • Value:
  • kmerSize
    • Description: k-mer size
    • Type: unsigned
    • Value:
  • dFPR [optional]
    • Description: desired false positve rate
    • Type: double
    • Value:
  • nEntry [optional]
    • Description: number of entries
    • Type: uint64_t
    • Value:
  • tEntry [optional]
    • Description: total number of entries
    • Type: uint64_t
    • Value:
  • seed [optional] (Not yet implimented)
    • Description: initial seeds for different hashes
    • Type: uint64_t[nhash]
    • Value: [0,1, ..., nhash-1]
  • bitsPerCounter [optional]
    • Description: bits per each counter in the counting bloom filter
    • Type: unsigned
    • Value: 8

3. filter

• Description: Bloom filter content
• Type: uchar[sizeInBytes]
• Value: