Evidence map›Paper›PMID 30839919›Full record

ArticleAlgorithms for molecular biology : AMB2019

SNPs detection by eBWT positional clustering.

Nicola Prezza, Nadia Pisanti, Marinella Sciortino, Giovanna Rosone

Abstract read
In one paragraph

Article in Algorithms for molecular biology : AMB, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. phyBWT2: phylogeny reconstruction via eBWT positional clustering.Algorithms for molecular biology : AMB · 2023
    Article
  4. MONI: A Pangenomic Index for Finding Maximal Exact Matches.Journal of computational biology : a journal of computational molecular cell biology · 2022
    Article
  5. Computing the original eBWT faster, simpler, and with less memory.International Symposium on String Processing and Information Retrieval : SPIRE ... : proceedings. SPIRE (Symposium) · 2021
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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.

Nicola Prezza1Dipartimento di Informatica, University of Pisa, Pisa, Italy.
Nadia Pisanti1Dipartimento di Informatica, University of Pisa, Pisa, Italy.
Marinella Sciortino2Dipartimento di Matematica e Informatica, University of Palermo, Palermo, Italy.
Giovanna Rosone1Dipartimento di Informatica, University of Pisa, Pisa, Italy.ORCID 0000-0001-5075-1214

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSequencing technologies keep on turning cheaper and faster, thus putting a growing pressure for data structures designed to efficiently store raw data, and possibly perform analysis therein. In this view, there is a growing interest in alignment-free and reference-free variants calling methods that only make use of (suitably indexed) raw reads data.

resultsWe develop the

conclusionsBased on the results of the experiments on synthetic and real data, we conclude that the positional clustering framework can be effectively used for the problem of identifying SNPs, and it appears to be a promising approach for calling other type of variants directly on raw sequencing data. AVAILABILITY: The software ebwt2snp is freely available for academic use at: https://github.com/nicolaprezza/ebwt2snp.

Indexed as

Assembly-freeBWTLCP arrayReference-freeSNPs

Identifiers

PMID30839919
PMCPMC6364478

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.