Spoa

Spoa (SIMD POA) is a c++ implementation of the partial order alignment (POA) algorithm (as described in 10.1093/bioinformatics/18.3.452) which is used to generate consensus sequences (as described in 10.1093/bioinformatics/btg109). It supports three alignment modes: local (Smith-Waterman), global (Needleman-Wunsch) and semi-global alignment (overlap), and three gap modes: linear, affine and convex (piecewise affine). It also supports Intel SSE4.1+ and AVX2 vectorization (marginally faster due to high latency shifts), SIMDe and dispatching.

Build

Dependencies

gcc 7+ | clang 4+
(spoa_exe)(spoa_test) zlib 1.2.8+

Hidden

[optional] USCiLab/cereal 1.3.0
[optional] simd-everywhere/simde 0.7.6
[optional] google/cpu_features 0.6.0
(spoa_exe)(spoa_test) rvaser/bioparser 3.1.0
(spoa_exe)(spoa_test) rvaser/biosoup 0.11.0
(spoa_test) google/googletest 1.10.0

CMake (3.12+)

git clone https://github.com/rvaser/spoa && cd spoa
cmake -B build -DCMAKE_BUILD_TYPE=Release
make -C build

Options

spoa_install: generate library install target
spoa_build_exe: build executable
spoa_build_tests: build unit tests
spoa_optimize_for_native: build with -march=native
spoa_optimize_for_portability: build with -msse4.1
spoa_use_cereal: use cereal library
spoa_use_simde: build with SIMDe for porting vectorized code
spoa_use_simde_nonvec: use SIMDe library for nonvectorized code
spoa_use_simde_openmp: use SIMDe support for OpenMP SIMD
spoa_generate_dispatch: use SIMDe to generate x86 dispatch

Meson (0.60.0+)

git clone https://github.com/rvaser/spoa && cd spoa
meson setup build
ninja -C build

Options

exe: build executable
tests: build unit tests
avx2: build with -mavx2
sse41: build with -msse4.1
cereal: build serialization funcitons
simde: build with SIMDe
simde_nonvec: use SIMDe for nonvectorized code
simde_openmp: use SIMDe support for OpenMP SIMD
dispatch: use SIMDe to generate x86 dispatch

Usage

usage: spoa [options ...] <sequences>

  # default output is stdout
  <sequences>
    input file in FASTA/FASTQ format (can be compressed with gzip)

  options:
    -m <int>
      default: 5
      score for matching bases
    -n <int>
      default: -4
      score for mismatching bases
    -g <int>
      default: -8
      gap opening penalty (must be non-positive)
    -e <int>
      default: -6
      gap extension penalty (must be non-positive)
    -q <int>
      default: -10
      gap opening penalty of the second affine function
      (must be non-positive)
    -c <int>
      default: -4
      gap extension penalty of the second affine function
      (must be non-positive)
    -l, --algorithm <int>
      default: 0
      alignment mode:
        0 - local (Smith-Waterman)
        1 - global (Needleman-Wunsch)
        2 - semi-global
    -r, --result <int> (option can be used multiple times)
      default: 0
      result mode:
        0 - consensus (FASTA)
        1 - multiple sequence alignment (FASTA)
        2 - 0 & 1 (FASTA)
        3 - partial order graph (GFA)
        4 - 0 & 3 (GFA)
    -d, --dot <file>
      output file for the partial order graph in DOT format
    -s, --strand-ambiguous
      for each sequence pick the strand with the better alignment
    --version
      prints the version number
    -h, --help
      prints the usage

  gap mode:
    linear if g >= e
    affine if g <= q or e >= c
    convex otherwise (default)

Examples

#include <iostream>

#include "spoa/spoa.hpp"

int main(int argc, char** argv) {

  std::vector<std::string> sequences = {
      "CATAAAAGAACGTAGGTCGCCCGTCCGTAACCTGTCGGATCACCGGAAAGGACCCGTAAAGTGATAATGAT",
      "ATAAAGGCAGTCGCTCTGTAAGCTGTCGATTCACCGGAAAGATGGCGTTACCACGTAAAGTGATAATGATTAT",
      "ATCAAAGAACGTGTAGCCTGTCCGTAATCTAGCGCATTTCACACGAGACCCGCGTAATGGG",
      "CGTAAATAGGTAATGATTATCATTACATATCACAACTAGGGCCGTATTAATCATGATATCATCA",
      "GTCGCTAGAGGCATCGTGAGTCGCTTCCGTACCGCAAGGATGACGAGTCACTTAAAGTGATAAT",
      "CCGTAACCTTCATCGGATCACCGGAAAGGACCCGTAAATAGACCTGATTATCATCTACAT"
  };

  auto alignment_engine = spoa::AlignmentEngine::Create(
      spoa::AlignmentType::kNW, 3, -5, -3);  // linear gaps

  spoa::Graph graph{};

  for (const auto& it : sequences) {
    auto alignment = alignment_engine->Align(it, graph);
    graph.AddAlignment(alignment, it);
  }

  auto consensus = graph.GenerateConsensus();

  std::cerr << ">Consensus LN:i:" << consensus.size() << std::endl
            << consensus << std::endl;

  auto msa = graph.GenerateMultipleSequenceAlignment();

  for (const auto& it : msa) {
    std::cerr << it << std::endl;
  }

  return 0;
}

Acknowledgement

This work has been supported in part by Croatian Science Foundation under projects UIP-11-2013-7353 and IP-2018-01-5886.