memory efficient, fast & precise taxnomomic classification system for metagenomic read mapping
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Updated
Mar 11, 2024 - C++
memory efficient, fast & precise taxnomomic classification system for metagenomic read mapping
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, dire…
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-analys…
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.
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)
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.…
Mapping-based Genome Size Estimation (MGSE) performs an estimation of a genome size based on a read mapping to an existing genome sequence assembly.
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)
Highly optimized genomic resources for GPUs
subset and spaced seed design tool
Reference-based read-mapper which performs ungapped alignment of sample reads on reference sequence.
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/GenS…
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.
The GPU-version and MPI-version of PerM
S3: Sequence Similarity Search (Protein Sequence)
DNA read mapping (seed-extension-aligner)
coding problems from course 6 of the Bioinformatics specialization
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