Evidence map›Paper›PMID 33726811›Full record

ArticleGenome biology2021

Kssd: sequence dimensionality reduction by k-mer substring space sampling enables real-time large-scale datasets analysis.

Huiguang Yi, Yanling Lin, Chengqi Lin, Wenfei Jin

Abstract read
In one paragraph

Article in Genome biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Genome research · 2025
    Article
  4. Article
  5. Review
  6. Fractional hitting sets for efficient multiset sketching.Algorithms for molecular biology : AMB · 2025
    Article
  7. Article
  8. Article
  9. CAIM: Coverage-based Analysis for Identification of Microbiome.bioRxiv : the preprint server for biology · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
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

4 authors.

Huiguang YiShenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, 518055, Guangdong, China.
Yanling LinShenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, 518055, Guangdong, China.
Chengqi LinInstitute of Life Sciences, Southeast University, Nanjing, 210096, Jiangsu, China.
Wenfei JinShenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, 518055, Guangdong, China. jinwf@sustech.edu.cn.ORCID 0000-0002-0028-3739

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Here, we develop k -mer substring space decomposition (Kssd), a sketching technique which is significantly faster and more accurate than current sketching methods. We show that it is the only method that can be used for large-scale dataset comparisons at population resolution on simulated and real data. Using Kssd, we prioritize references for all 1,019,179 bacteria whole genome sequencing (WGS) runs from NCBI Sequence Read Archive and find misidentification or contamination in 6164 of these. Additionally, we analyze WGS and exome runs of samples from the 1000 Genomes Project.

Indexed as

SoftwareAlgorithmsBacteriaComputational BiologyDatabases, GeneticGenome, BacterialHigh-Throughput Nucleotide SequencingMetagenomicsSequence Analysis, DNADistance estimationK-merMislabeling detectionSequence comparisonSketching method

Identifiers

PMID33726811
PMCPMC7962209

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.