read-mapping

CMU-SAFARI/RawHash

RawHash is the first mechanism that can accurately and efficiently map raw nanopore signals to large reference genomes (e.g., a human reference genome) in real-time without using powerful computational resources (e.g., GPUs). Described by Firtina et al. (published at https://academic.oup.com/bioinformatics/article/39/Supplement_1/i297/7210440)

CMU-SAFARI/BLEND

BLEND is a mechanism that can efficiently find fuzzy seed matches between sequences to significantly improve the performance and accuracy while reducing the memory space usage of two important applications: 1) finding overlapping reads and 2) read mapping. Described by Firtina et al. (published in NARGAB https://doi.org/10.1093/nargab/lqad004)

CMU-SAFARI/GenASM

Source code for the software implementations of the GenASM algorithms proposed in our MICRO 2020 paper: Senol Cali et. al., "GenASM: A High-Performance, Low-Power Approximate String Matching Acceleration Framework for Genome Sequence Analysis" at https://people.inf.ethz.ch/omutlu/pub/GenASM-approximate-string-matching-framework-for-genome-analysis_micro20.pdf

orangeSi/GSSplayground

Lightweight single-html-file-based Genome Segments playground for Visualize genome features cluster(gene arrow map or other features), add synteny among genome fragments or add crosslink among features, add short(PE/MP)/long reads(pacbio or nanopore) mapping or snpindel in vcf(not support complex sv yet), support all CIGAR of sam alignment, directly modify almost all features in Chrome by click the feature

bpucker/MGSE

Mapping-based Genome Size Estimation (MGSE) performs an estimation of a genome size based on a read mapping to an existing genome sequence assembly.

CMU-SAFARI/GenStore

GenStore is the first in-storage processing system designed for genome sequence analysis that greatly reduces both data movement and computational overheads of genome sequence analysis by exploiting low-cost and accurate in-storage filters. Described in the ASPLOS 2022 paper by Mansouri Ghiasi et al. at https://people.inf.ethz.ch/omutlu/pub/GenStore_asplos22-arxiv.pdf

CMU-SAFARI/Genome-on-Diet

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).

yjx1217/Varathon

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

CMU-SAFARI/Molecules2Variations

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://arxiv.org/abs/2205.07957

CMU-SAFARI/GateSeeder

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.

gaojunxuan/chrom_mini_graph

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

Mangul-Lab-USC/review-technology-dictates-algorithms

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.org/abs/2003.00110.

achacond/gem-cutter

Highly optimized genomic resources for GPUs

karel-brinda/dymas

Dynamic Mapping Simulator.

laurentnoe/iedera

subset and spaced seed design tool

berkalpyakici/mscrm

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

CMU-SAFARI/SequenceLab

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

kalyaniasthana/FindingMutationsInDNAAndProteins_BioinformaticsVI

coding problems from course 6 of the Bioinformatics specialization

laurentnoe/storm

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

acgtun/gpu-perm

The GPU-version and MPI-version of PerM

acgtun/perm2

DNA read mapping (seed-extension-aligner)

acgtun/s3

S3: Sequence Similarity Search (Protein Sequence)

Schre/Read-Mapping

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

BCCDC-PHL/alignment-variants

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

Fatemehrshd/Read-mapping-and-genome-assembly

Fatemehrshd/RNA-Seq-Analysis