Sampling algorithms

This library provides a collection of sampling algorithms, including:

• random minimizers (`'M'``),
• closed sycnmers ('C', a.k.a. "miniception"),
• open syncmers ('O'),
• open-closed minimizers ('OC'),
• double decycling set based ('DD'),
• mod-sampling paired with any of the previous methods, thus:
  • random mod-minimizers ('mod-M'),
  • closed mod-minimizers ('mod-C'),
  • open mod-minimizers ('mod-O'),
  • open-closed mod-minimizers ('mod-OC'),
  • double-decycling mod-minimizers ('mod-DD').

The code has been used for the experiments of the paper "The open-closed mod-minimizer algorithm" (AMB 2025), based on the previous paper "The mod-minimizer: a simple and efficient sampling algorithm for long k-mers" (WABI 2024, code).

To reproduce the experiments in the paper: first compile the code as explained below and then run the scripts here.

Compile the code

Before compiling, pull all dependencies with

git submodule update --init --recursive

Compile the code with

mkdir build
cd build
cmake ..
make

Quick start

After compilation, generate some random sequence (in the following example, of 1 million nucleotides) with

./generate_random_sequence -o test.bin -n 1000000 -s 4

and evaluate density of different methods with the tool density. Some examples below.

./density -i test.bin -k 63 -w 8 -a M --stream

  is_forward = YES
  num_sampled_kmers = 222230
  num_kmers = 999938
  num_windows = 999931
  density = 0.222244
  1.77795X away from lower bound 1/w = 0.125

./density -i test.bin -k 63 -w 8 -a OC --stream

  is_forward = YES
  num_sampled_kmers = 181061
  num_kmers = 999938
  num_windows = 999931
  density = 0.181072
  1.44858X away from lower bound 1/w = 0.125

./density -i test.bin -k 63 -w 8 -a mod-OC --stream

  is_forward = YES
  num_sampled_kmers = 138011
  num_kmers = 999938
  num_windows = 999931
  density = 0.13802
  1.10416X away from lower bound 1/w = 0.125