Lukas Hübner

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About Lukas Hübner:

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SEEK ID: https://publications.h-its.org/people/169

Location: Germany

ORCID: https://orcid.org/0000-0001-9213-7597

Joined: 17th Jan 2022

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Computational Molecular Evolution

The Computational Molecular Evolution (CME) group focuses on developing algorithms, computer architectures, and high-performance computing solutions for bioinformatics.

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Heidelberg Institute for Theoretical Studies

Country: Germany

City: Heidelberg

Web page: https://www.h-its.org

Showing 5 out of a possible 10 Publications Advanced Publications list for this Person with search and filtering

KaMPIng: Flexible and (Near) Zero-Overhead C++ Bindings for MPI

Computational Molecular Evolution

Abstract (Expand)

The Message-Passing Interface (MPI) and C++ form the backbone of high-performance computing, but MPI only provides C and Fortran bindings. While this offers great language interoperability, high-level …

Authors: Tim Niklas Uhl, Matthias Schimek, Lukas Hübner, Demian Hespe, Florian Kurpicz, Daniel Seemaier, Christoph Stelz, Peter Sanders

Date Published: 17th Nov 2024

Publication Type: Proceedings

DOI: 10.1109/SC41406.2024.00050

Citation: SC24: International Conference for High Performance Computing, Networking, Storage and Analysis,pp.1-21,IEEE

Created: 9th Jan 2025 at 10:12, Last updated: 9th Jan 2025 at 10:13

Re-Engineering Genomic Tree Sequence Inference Algorithms

Computational Molecular Evolution

Abstract (Expand)

In the field of population genetics, the driving forces of evolution within species can be studied with trees. Along a genome, each tree describes the local ancestries of a small genomic region. Together, …

Authors: Johannes Hengstler, Lukas Hübner, Alexandros Stamatakis

Date Published: 1st Aug 2024

Publication Type: Master's Thesis

Citation:

Created: 9th Jan 2025 at 13:02, Last updated: 25th Feb 2025 at 09:56

Brief Announcement: (Near) Zero-Overhead C++ Bindings for MPI

Computational Molecular Evolution

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The Message-Passing Interface (MPI) and C++ form the backbone of high-performance computing and algorithmic research in the field of distributed-memory computing, but MPI only provides C and Fortran …

Authors: Kunal Agrawal, Erez Petrank, Demian Hespe, Lukas Hübner, Florian Kurpicz, Peter Sanders, Matthias Schimek, Daniel Seemaier, Tim Niklas Uhl

Date Published: 17th Jun 2024

Publication Type: Proceedings

DOI: 10.1145/3626183.3660260

Citation: Proceedings of the 36th ACM Symposium on Parallelism in Algorithms and Architectures,pp.289-291,ACM

Created: 9th Jan 2025 at 10:19, Last updated: 25th Feb 2025 at 09:20

Faster Sorting of Aligned DNA-Read Files

Computational Molecular Evolution

Abstract (Expand)

In the analysis of DNA sequencing data for finding disease causing mutations, to understand evolutionary relationships between species, and to find variants, DNA-Reads are compared to a reference genome. … A reference genome is a representative example for a set of genes of a species. Sorting these aligned DNA-Reads by their position within the reference sequence is a crucial step in many of these downstream analyses. SAMtools sort, a widely used tool, performs external memory sorting of aligned DNA-Reads stored in the BAM format (Binary Alignment Map). This format allows for compressed storage of alignment data. SAMtools sort provides the most comprehensive set of features while exhibiting demonstrably faster execution times than its open source alternatives. In this work, we analyze SAMtools sort for sorting BAM files and propose methods to reduce its runtime. We divide the analysis into three parts: management of temporary files, compression, and input/output (IO). For the management of temporary files, we find that the maximum number of temporary files SAMtools sort can open concurrently is lower than the maximum number of open files permitted by the operating system. This results in an unnecessarily high number of merges of temporary files into larger temporary files, introducing overhead as SAMtools sort performs extra write and compression operations. To overcome this, we propose a dynamic limit for the number of temporary files, adapting to the operating system’s soft limit for open files. For compression, we test seven different libraries for compatible compression and a range of compression levels, identifying options that offer faster compression and result in a speedup of up to five times in single-threaded execution of SAMtools sort. For IO, we demonstrate that a minimal level of compression avoids IO overhead, thereby reducing the runtime of SAMtools sort compared to uncompressed output. However, we also show that uncompressed output can be used in the pipelining of SAMtools commands to reduce the runtime of subsequent SAMtools commands. Our proposed modifications to SAMtools sort and user behavior have the potential to achieve speedups of up to 6. This represents an important contribution to the field of bioinformatics, considering the widespread adoption of SAMtools sort evidenced by its over 5,000 citations and over 5.1 million downloads through Bioconda.

Authors: Dominik Siebelt, Lukas Hübner, Alexandros Stamatakis

Date Published: 3rd Jun 2024

Publication Type: Bachelor's Thesis

Citation:

Created: 9th Jan 2025 at 13:05

Memoization on Shared Subtrees Accelerates Computations on Genealogical Forests

Computational Molecular Evolution

Abstract (Expand)

The field of population genetics attempts to advance our understanding of evolutionary processes. It has applications, for example, in medical research, wildlife conservation, and – in conjunction with … recent advances in ancient DNA sequencing technology – studying human migration patterns over the past few thousand years. The basic toolbox of population genetics includes genealogical tress, which describe the shared evolutionary history among individuals of the same species. They are calculated on the basis of genetic variations. However, in recombining organisms, a single tree is insufficient to describe the evolutionary history of the whole genome. Instead, a collection of correlated trees can be used, where each describes the evolutionary history of a consecutive region of the genome. The current corresponding state of-the-art data structure, tree sequences, compresses these genealogical trees via edit operations when moving from one tree to the next along the genome instead of storing the full, often redundant, description for each tree. We propose a new data structure, genealogical forests, which compresses the set of genealogical trees into a DAG. In this DAG identical subtrees that are shared across the input trees are encoded only once, thereby allowing for straight-forward memoization of intermediate results. Additionally, we provide a C++ implementation of our proposed data structure, called gfkit , which is 2.1 to 11.2 (median 4.0) times faster than the state-of-the-art tool on empirical and simulated datasets at computing important population genetics statistics such as the Allele Frequency Spectrum, Patterson’s f , the Fixation Index, Tajima’s D , pairwise Lowest Common Ancestors, and others. On Lowest Common Ancestor queries with more than two samples as input, gfkit scales asymptotically better than the state-of-the-art, and is thus up to 990 times faster. In conclusion, our proposed data structure compresses genealogical trees by storing shared subtrees only once, thereby enabling straight-forward memoization of intermediate results, yielding a substantial runtime reduction and a potentially more intuitive data representation over the state-of-the-art. Our improvements will boost the development of novel analyses and models in the field of population genetics and increases scalability to ever-growing genomic datasets. 2012 ACM Subject Classification Applied computing → Computational genomics; Applied computing → Molecular sequence analysis; Applied computing → Bioinformatics; Applied computing → Population genetics

Authors: Lukas Hübner, Alexandros Stamatakis

Date Published: 27th May 2024

Publication Type: Proceedings

DOI: 10.1101/2024.05.23.595533

Citation: biorxiv;2024.05.23.595533v1,[Preprint]

Created: 9th Jan 2025 at 10:18, Last updated: 9th Jan 2025 at 10:18

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