The GPU-version and MPI-version of PerM

S3: Sequence Similarity Search (Protein Sequence)

DNA read mapping (seed-extension-aligner)

Pipeline to perform alignment & variant calling on whole-genome sequence data

Mapping reads to a corresponding genome using a suffix tree (linear time construction) and Smith-Waterman local alignment algorithm

coding problems from course 6 of the Bioinformatics specialization

SequenceLab is a benchmark suite for evaluating computational methods for comparing genomic sequences, such as pre-alignment filters and pairwise sequence alignment algorithms. SequenceLab is described by Rumpf et al. at https://arxiv.org/abs/2310.16908

Illumina (and SOLiD) sensitive read mapping tool (cloned from svn://scm.gforge.inria.fr/svnroot/storm/)

Reference-based read-mapper which performs ungapped alignment of sample reads on reference sequence.

subset and spaced seed design tool

Dynamic Mapping Simulator.

Highly optimized genomic resources for GPUs

A systematic survey of algorithmic foundations and methodologies across 107 alignment methods (1988-2021), for both short and long reads. We provide a rigorous experimental evaluation of 11 read aligners to demonstrate the effect of these underlying algorithms on speed and efficiency of read alignment. Described by Alser et al. at https://arxiv.…

GateSeeder is the first near-memory CPU-FPGA co-design for alleviating both the compute-bound and memory-bound bottlenecks in short and long-read mapping. GateSeeder outperforms Minimap2 by up to 40.3×, 4.8×, and 2.3× when mapping real ONT, HiFi, and Illumina reads, respectively.

Space-efficient minimizer-based pangenome reference graph and haplotype mapping tool

The first work to provide a comprehensive survey of a prominent set of algorithmic improvement and hardware acceleration efforts for the entire genome analysis pipeline used for the three most prominent sequencing data, short reads (Illumina), ultra-long reads (ONT), and accurate long reads (HiFi). Described in arXiv (2022) by Alser et al. https…

Genome-on-Diet is a fast and memory-frugal framework for exemplifying sparsified genomics for read mapping, containment search, and metagenomic profiling. It is much faster & more memory-efficient than minimap2 for Illumina, HiFi, and ONT reads. Described by Alser et al. (preliminary version: https://arxiv.org/abs/2211.08157).

A scalable variant calling and benchmarking framework supporting both short and long reads.