kseq++

kseq++ is a C++11 re-implementation of kseq .h by Heng Li. The goal for re-implementation of kseq is providing better API and resource management while preserving its flexibility and performance. Like original kseq, this parser is based on generic stream buffer and works with different file types. However, instead of using C macros, it uses C++ templates.

It inherits all features from kseq (quoting from kseq homepage):

Parse both FASTA and FASTQ format, and even a mixture of FASTA and FASTQ records in one file.

Seamlessly adapt to gzipped compressed file when used with zlib.

Support multi-line FASTQ.

Work on a stream with an internal stream buffer.

while additionally provides:

simpler and more readable API
RAII-style memory management

The library also comes with a FASTA/Q writer. Like reading, it can write mixed multi-line FASTA and FASTQ records with gzip compression. The writer is multi-threaded and the actual write function call happens in another thread in order to hide the IO latency.

The RAII-style class KStream is the core class which handles input and output streams. Each FASTA or FASTQ record will be stored in a KSeq object.

This library provides another layer of abstraction which hides most details and provides very simple API on top of KStream: SeqStreamIn and SeqStreamOut classes for reading and writing a sequence file respectively with exactly the same interface. It is highly recommended to use these classes unless you intent to use low-level interface like changing buffer size or use custom stream type.

Looking for a quick start guide?

Jump to Examples or Installation.

KStream (`kseq++.hpp`)

KStream is a generic, template class with the following template parameters which are usually inferred by the compiler when constructed (so, there is no need to provide them manually):

TFile: type of the underlying stream/file (e.g. gzFile)
TFunc: type of the read/write function corresponding to TFile (e.g. int (*)(gzFile_s*, const void*, unsigned int) for an output stream with gzFile as underlying file type)
TSpec: stream opening mode (with values: mode::in or mode::out)

The template parameters are inferred by compiler in C++17 when instantiated by calling their constructors. make_kstream function family also construct KStreams which might be useful for inferring template parameters when using older standards; e.g. C++11 or C++14.

To construct an instance, it requires at least three arguments: 1) the file object/pointer/descriptor (can be of any type), 2) its corresponding read/write function, and 3) stream opening mode (see Examples).

Higher-level API (`seqio.hpp`)

This header file defines SeqStream class set: i.e. SeqStreamIn and SeqStreamOut. SeqStream classes are inherited from KStream with simpler constructors using sensible defaults. They do not define any new method or override inherited ones. So, they can be treated the same way as KStream.

In order to prevent imposing any unwanted external libraries (e.g. zlib) , the SeqStream class set are defined in a separated header file (seqio.hpp) from the core library.

Examples

Reading a sequence file

These examples read FASTQ/A records one by one from either compressed or uncompressed file.

Using SeqStreamIn:

#include <iostream>
#include <kseq++/seqio.hpp>

using namespace klibpp;

int main(int argc, char* argv[])
{
  KSeq record;
  SeqStreamIn iss("file.fq.gz");
  while (iss >> record) {
    std::cout << record.name << std::endl;
    if (!record.comment.empty()) std::cout << record.comment << std::endl;
    std::cout << record.seq << std::endl;
    if (!record.qual.empty()) std::cout << record.qual << std::endl;
  }
}

Low-level API

Using KStream

#include <iostream>
#include <zlib>
#include <kseq++/kseq++.hpp>

using namespace klibpp;

int main(int argc, char* argv[])
{
  KSeq record;
  gzFile fp = gzopen(filename, "r");
  auto ks = make_kstream(fp, gzread, mode::in);
  // auto ks = KStream(fp, gzread, mode::in);  // C++17
  // auto ks = KStreamIn(fp, gzread);  // C++17
  while (ks >> record) {
    std::cout << record.name << std::endl;
    if (!record.comment.empty()) std::cout << record.comment << std::endl;
    std::cout << record.seq << std::endl;
    if (!record.qual.empty()) std::cout << record.qual << std::endl;
  }
  gzclose(fp);
}

Or records can be fetched and stored in a std::vector< KSeq > in chunks.

Using SeqStreamIn:

#include <iostream>
#include <kseq++/seqio.hpp>

using namespace klibpp;

int main(int argc, char* argv[])
{
  SeqStreamIn iss("file.fq");
  auto records = iss.read();
  // auto records = iss.read(100);  // read a chunk of 100 records
}

Low-level API

Using KStream

#include <iostream>
#include <zlib>
#include <kseq++/kseq++.hpp>

using namespace klibpp;

int main(int argc, char* argv[])
{
  gzFile fp = gzopen(filename, "r");
  auto ks = make_ikstream(fp, gzread);
  auto records = ks.read();  // fetch all the records
  // auto records = ks.read(100);  // read a chunk of 100 records
  gzclose(fp);
}

Writing a sequence file

These examples write FASTA/Q records to an uncompressed file.

Using SeqStreamIn:

#include <iostream>
#include <kseq++/seqio.hpp>

using namespace klibpp;

int main(int argc, char* argv[])
{
  SeqStreamOut oss("file.dat");
  for (KSeq const& r : records) oss << r;
}

Low-level API

Using KStream

#include <iostream>
#include <zlib>
#include <kseq++/kseq++.hpp>

using namespace klibpp;

int main(int argc, char* argv[])
{
  int fd = open(filename, O_WRONLY);
  auto ks = make_kstream(fd, write, mode::out);
  // auto ks = KStreamOut(fd, write);  // C++ 17
  // ...
  for (KSeq const& r : records) ks << r;
  ks << kend;
  close(fd);
}

Another example for writing a series of FASTQ records to a gzipped file in FASTA format:

#include <iostream>
#include <kseq++/seqio.hpp>

using namespace klibpp;

int main(int argc, char* argv[])
{
  /* let `record` be a list of FASTQ records */
  SeqStreamOut oss("file.fa.gz", /* compression */ true, format::fasta);
  for (KSeq const& r : records) oss << r;
}

NOTE

The buffer will be flushed to the file when the KStream object goes out of the scope. Otherwise, ks << kend is required to be called before closing the file to make sure that there is no data loss.

There is no need to write kend to the stream if using SeqStreamOut.

Wrapping seq/qual lines

While writing a record to a file, sequence and quality scores can be wrapped at a certain length. The default wrapping length for FASTA format is 60 bps and can be customised by KStream::set_wraplen method. For FASTQ format -- i.e. when the format is explicitly set to format::fastq -- output sequence and quality string are not wrapped by default.

Wrapping can be disabled or enable by KStream::set_nowrapping and KStream::set_wrapping methods respectively. The latter reset the wrapping length to the default value (60 bps).

Formatting

The default behaviour is to write a record in FASTQ format if it has quality information. Otherwise, i.e. when the quality string is empty, the record will be written in FASTA format. So, the output might be a mixture of FASTQ and FASTA records. However, the output format can be forced by using format::fasta and format::fastq modifiers. For example:

out << format::fasta << fastq_record;
out << another_record;  // all other calls after this will also be in FASTA format.

will write a FASTQ record in FASTA format. These modifiers affect all writes after them until another modifier is used. The format::mix modifier reverts the behaviour to default.

NOTE

Writing a FASTA record in FASTQ format throws an exception unless the record is empty (a record with empty sequence and quality string).

Installation

kseq++ is a header-only library and can be simply included in a project. Use the package provided in the Releases section and copy include/kseq++ to your project tree.

The kseq++.hpp is the core header file and seqio.hpp is optional and only needs to be included when using higher-level API (see above). The latter requires zlib as dependency which should be linked.

There are also other ways to install the library:

From source

Installing from source requires CMake>= 3.10:

git clone https://github.com/cartoonist/kseqpp
cd kseqpp
mkdir build && cd build
cmake .. # -DCMAKE_INSTALL_PREFIX=/path/to/custom/install/prefix (optional)
make install

From conda

It is also distributed on bioconda:

conda install -c bioconda kseqpp

Development

CMake integration

After installing the library, you can import the library to your project using find_package. It imports kseq++::kseq++ target which can be passed to target_include_directories and target_link_libraries calls. This is a sample CMake file for building myprogram which uses the library:

cmake_minimum_required(VERSION 3.10)
project(myprogram VERSION 0.0.1 LANGUAGES CXX)

find_package(kseq++ REQUIRED)

set(SOURCES "src/main.cpp")
add_executable(myprogram ${SOURCES})
target_include_directories(myprogram
  PRIVATE kseq++::kseq++)
target_link_libraries(myprogram
  PRIVATE kseq++::kseq++)

CMake options:

for building tests: -DBUILD_TESTING=on
for building benchmark: -DBUILD_BENCHMARKING=on

Benchmark

NOTE: The results below are based on older versions of kseq++ and kseq.h.

TODO Update benchmark

NOTE: It is fair to say that kseq++ comes with a very negligible overhead and is almost as fast as kseq.h (in 'read' mode) with an idiomatic C++ API and more convinient resource management. The original kseq.h does not support writing FASTA/Q files.

Datasets

For this benchmark, I re-used sequence files from SeqKit benchmark: seqkit-benchmark-data.tar.gz

file	format	type	num_seqs	sum_len	min_len	avg_len	max_len
dataset_A.fa	FASTA	DNA	67,748	2,807,643,808	56	41,442.5	5,976,145
dataset_B.fa	FASTA	DNA	194	3,099,750,718	970	15,978,096.5	248,956,422
dataset_C.fq	FASTQ	DNA	9,186,045	918,604,500	100	100	100

Platform

CPU: Intel® Xeon® CPU E3-1241 v3 @ 3.50GHz, 4 cores, 8 threads
RAM: DDR3 1600 MHz, 16352 MB
HDD: Seagate Desktop HDD 500GB, 16MB Cache, SATA-3
OS: Debian GNU/Linux 9.4 (stretch), Linux 4.9.91-1-amd64-smp
Compiler: GCC 6.3.0, compiled with optimisation level 3 (-O3)

Result (for kseq++ v0.1.4)

Reading all records

file	kseq++	kseq	SeqAn	kseq++/read*	SeqAn/readRecords**
dataset_A.fa	2.35 s	2.5 s	2.92 s	3.52 s	4.94 s
dataset_B.fa	2.66 s	2.8 s	3.34 s	3.74 s	9.82 s
dataset_C.fq	2.56 s	2.46 s	2.66 s	4.56 s	11.8 s

* storing all records in std::vector.

** storing all records in seqan2::StringSet< seqan2::CharString >.

Writing all records

file	kseq++/plain	kseq++/gzipped	SeqAn/plain
dataset_A.fa	2.3 s	866 s	2.29 s
dataset_B.fa	2.19 s	849 s	2.33 s
dataset_C.fq	1.94 s	365 s	2.24 s

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README.md

README.md

kseq++

Looking for a quick start guide?

KStream (`kseq++.hpp`)

Higher-level API (`seqio.hpp`)

Examples

Reading a sequence file

Writing a sequence file

Wrapping seq/qual lines

Formatting

Installation

From source

From conda

Development

CMake integration

Benchmark

Datasets

Platform

Result (for kseq++ v0.1.4)

Reading all records

Writing all records

Files

README.md

Latest commit

History

README.md

File metadata and controls

kseq++

Looking for a quick start guide?

KStream (kseq++.hpp)

Higher-level API (seqio.hpp)

Examples

Reading a sequence file

Writing a sequence file

Wrapping seq/qual lines

Formatting

Installation

From source

From conda

Development

CMake integration

Benchmark

Datasets

Platform

Result (for kseq++ v0.1.4)

Reading all records

Writing all records

KStream (`kseq++.hpp`)

Higher-level API (`seqio.hpp`)