read-mapping
There are 1 repository under read-mapping topic.
muellan / metacache
memory efficient, fast & precise taxnomomic classification system for metagenomic read mapping
Language:C++ 64- RawHash
CMU-SAFARI / RawHash
RawHash can accurately and efficiently map raw nanopore signals to reference genomes of varying sizes (e.g., from viral to a human genomes) in real-time without basecalling. Described by Firtina et al. (published at https://academic.oup.com/bioinformatics/article/39/Supplement_1/i297/7210440).
Language:C 58 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)
Language:C 43bpucker / 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.
Language:Python 35orangeSi / 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
Language:HTML 33Source 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
Language:C 31Genome-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).
Language:Roff 16GenStore 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
Language:C 14- Varathon
yjx1217 / Varathon
A scalable variant calling and benchmarking framework supporting both short and long reads.
Language:Perl 14 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
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.
Language:Jupyter Notebook 8GateSeeder 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.
Language:C 7gaojunxuan / chrom_mini_graph
Space-efficient minimizer-based pangenome reference graph and haplotype mapping tool
Language:Rust 7achacond / gem-cutter
Highly optimized genomic resources for GPUs
Language:C 4SequenceLab 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
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laurentnoe / iedera
subset and spaced seed design tool
Language:C++ 3berkalpyakici / mscrm
Reference-based read-mapper which performs ungapped alignment of sample reads on reference sequence.
Language:Java 1jlmaier12 / ProActive
Detect elevations and gaps in read coverage on metagenome contigs or assembled genomes
Language:HTML 1kalyaniasthana / FindingMutationsInDNAAndProteins_BioinformaticsVI
coding problems from course 6 of the Bioinformatics specialization
Language:Python 1Illumina (and SOLiD) sensitive read mapping tool (cloned from svn://scm.gforge.inria.fr/svnroot/storm/, original code from @marta- , with some work done by @yoann-dufresne)
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Schre / Read-Mapping
Mapping reads to a corresponding genome using a suffix tree (linear time construction) and Smith-Waterman local alignment algorithm
Language:C++ 0BCCDC-PHL / alignment-variants
Pipeline to perform alignment & variant calling on whole-genome sequence data
Language:PythonNIGMS / Intro-to-Pangenomics
This repository provides a comprehensive module on graphical pangenomics, guiding users through building, indexing, mapping, and visualizing pangenome graphs. The module runs on Google Cloud Platform using Jupyter notebooks and includes tools like PGGB, vg, BLAST, and Bandage.
Language:HTMLpesho-ivanov / shmap
Long read sketch-based read mapper based on an admissible seed heuristic
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