High-performance sequence processing
7
Rolling hashes on sequences
PhD Thesis
Abstract
Introduction
1
Comparing genomic sequences
2
Comparing using k-mers
3
Sketching sequences
4
Sampling with minimizers
High-performance sequence processing
5
An intro to vectorization
6
Vectorized sequence parsing
7
Rolling hashes on sequences
8
Vectorized computation of minimizers
9
Application to sequence filtering
Locality-preserving representations of k-mer sets
10
Background on k-mer sets
11
Necklaces and minimizers
12
Set representation and operations
13
Super-k-mers maps
14
Sketching super-k-mers
Sampling k-mers to lower memory & complexity
15
Background on minimizers
16
Multiminimizers
17
Locally-consistent phrases
18
Lexicographic-informed sampling
Discussion & conclusion
References
High-performance sequence processing
7
Rolling hashes on sequences
7
Rolling hashes on sequences
See
(
Groot Koerkamp & Martayan, 2025
)
Bias of default NtHash, see
this repo
Groot Koerkamp
, R. &
Martayan
, I. (2025)
SimdMinimizers: Computing Random Minimizers, fast
.
23rd international symposium on experimental algorithms (SEA 2025)
, vol. 338. Schloss Dagstuhl – Leibniz-Zentrum f
ü
r Informatik.
6
Vectorized sequence parsing
8
Vectorized computation of minimizers