Evidence map›Paper›PMID 38579261›Full record

ArticleBioinformatics (Oxford, England)2024

Designing efficient randstrobes for sequence similarity analyses.

Moein Karami, Aryan Soltani Mohammadi, Marcel Martin, Barış Ekim, Wei Shen, Lidong Guo, Mengyang Xu, Giulio Ermanno Pibiri, Rob Patro, Kristoffer Sahlin

Open access · goldAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 7 institutions in 4 countries.

Moein KaramiDepartment of Mathematics, Science for Life Laboratory, Stockholm University, Stockholm 106 91, Sweden.
Aryan Soltani MohammadiDepartment of Mathematics, Science for Life Laboratory, Stockholm University, Stockholm 106 91, Sweden.
Marcel MartinDepartment of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Stockholm University, Solna SE-17121, Sweden.ORCID 0000-0002-0680-200X
Barış EkimComputer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, United States.
Wei ShenDepartment of Infectious Diseases, Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China.ORCID 0000-0002-8099-8258
Lidong GuoBGI Research, Qingdao 266555, China.
Mengyang XuBGI Research, Shenzhen 518083, China.ORCID 0000-0002-4487-7088
Giulio Ermanno PibiriDepartment of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Venice 30172, Italy.
Rob PatroDepartment of Computer Science and Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, United States.ORCID 0000-0001-8463-1675
Kristoffer SahlinDepartment of Mathematics, Science for Life Laboratory, Stockholm University, Stockholm 106 91, Sweden.ORCID 0000-0001-7378-2320
Stockholm University · SEBGI Group (China) · CNBGI Research · CNBroad Institute · USDalian Medical University · CNIstituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" · ITUniversity of Maryland, College Park · US

Funding

Swedish Research Council 2021-04000
6 · The paper itself

Abstract

motivationSubstrings of length k, commonly referred to as k-mers, play a vital role in sequence analysis. However, k-mers are limited to exact matches between sequences leading to alternative constructs. We recently introduced a class of new constructs, strobemers, that can match across substitutions and smaller insertions and deletions. Randstrobes, the most sensitive strobemer proposed in Sahlin (Effective sequence similarity detection with strobemers. Genome Res 2021a;31:2080-94. https://doi.org/10.1101/gr.275648.121), has been used in several bioinformatics applications such as read classification, short-read mapping, and read overlap detection. Recently, we showed that the more pseudo-random the behavior of the construction (measured in entropy), the more efficient the seeds for sequence similarity analysis. The level of pseudo-randomness depends on the construction operators, but no study has investigated the efficacy.

resultsIn this study, we introduce novel construction methods, including a Binary Search Tree-based approach that improves time complexity over previous methods. To our knowledge, we are also the first to address biases in construction and design three metrics for measuring bias. Our evaluation shows that our methods have favorable speed and sampling uniformity compared to existing approaches. Lastly, guided by our results, we change the seed construction in strobealign, a short-read mapper, and find that the results change substantially. We suggest combining the two results to improve strobealign's accuracy for the shortest reads in our evaluated datasets. Our evaluation highlights sampling biases that can occur and provides guidance on which operators to use when implementing randstrobes. AVAILABILITY AND IMPLEMENTATION: All methods and evaluation benchmarks are available in a public Github repository at https://github.com/Moein-Karami/RandStrobes. The scripts for running the strobealign analysis are found at https://github.com/NBISweden/strobealign-evaluation.

Indexed as

AlgorithmsComputational BiologySequence AlignmentSequence Analysis, DNASoftware

Identifiers

PMID38579261
PMCPMC11034988
OpenAlexW4394768492

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.