SUMMARY: HTSeq 2.0 provides a more extensive application programming interface including a new representation for sparse genomic data, enhancements for htseq-count to suit single-cell omics, a new script for data using cell and molecular barcodes, improved documentation, testing and deployment, bug fixes and Python 3 support. AVAILABILITY AND IMPLEMENTATION: HTSeq 2.0 is released as an open-source software under the GNU General Public License and is available from the Python Package Index at https://pypi.python.org/pypi/HTSeq. The source code is available on Github at https://github.com/htseq/htseq. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: The analysis of the evolutionary dynamics of a population with many polymorphic loci is challenging, as a large number of possible genotypes needs to be tracked. In the absence of analytical solutions, forward computer simulations are an important tool in multi-locus population genetics. The run time of standard algorithms to simulate sexual populations increases as 8(L) with the number of loci L, or with the square of the population size N. RESULTS: We have developed algorithms to simulate large populations with arbitrary genetic maps, including multiple crossovers, with a run time that scales as 3(L). If the number of crossovers is restricted to at most one, the run time is reduced to L2(L). The algorithm is based on an analogue of the Fast Fourier Transform (FFT) and allows for arbitrary fitness functions (i.e. any epistasis). In addition, we include a streamlined individual-based framework. The library is implemented as a collection of C++ classes and a Python interface.