Evidence map›Paper›PMID 22923522›Full record

ArticleNucleic acids research2012

Repeat or not repeat?--Statistical validation of tandem repeat prediction in genomic sequences.

Elke Schaper, Andrey V Kajava, Alain Hauser, Maria Anisimova

Abstract read
In one paragraph

Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Whole Genome Sequencing Analysis of Effects of CRISPR/Cas9 inJournal of fungi (Basel, Switzerland) · 2022
    Article
  10. Article
  11. Identification of RareInternational journal of molecular sciences · 2021
    Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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.

Elke SchaperComputer Science Department, ETH Zürich, Universitätsstrasse 6, CH-8092 Zürich, Switzerland. elke@inf.ethz.ch
Andrey V Kajava
Alain Hauser
Maria Anisimova

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tandem repeats (TRs) represent one of the most prevalent features of genomic sequences. Due to their abundance and functional significance, a plethora of detection tools has been devised over the last two decades. Despite the longstanding interest, TR detection is still not resolved. Our large-scale tests reveal that current detectors produce different, often nonoverlapping inferences, reflecting characteristics of the underlying algorithms rather than the true distribution of TRs in genomic data. Our simulations show that the power of detecting TRs depends on the degree of their divergence, and repeat characteristics such as the length of the minimal repeat unit and their number in tandem. To reconcile the diverse predictions of current algorithms, we propose and evaluate several statistical criteria for measuring the quality of predicted repeat units. In particular, we propose a model-based phylogenetic classifier, entailing a maximum-likelihood estimation of the repeat divergence. Applied in conjunction with the state of the art detectors, our statistical classification scheme for inferred repeats allows to filter out false-positive predictions. Since different algorithms appear to specialize at predicting TRs with certain properties, we advise applying multiple detectors with subsequent filtering to obtain the most complete set of genuine repeats.

Indexed as

Models, StatisticalRepetitive Sequences, Amino AcidSequence Analysis, DNATandem Repeat SequencesAlgorithmsGenomicsHumansLikelihood FunctionsPhylogenySequence Analysis, Protein

Identifiers

PMID22923522
PMCPMC3488214

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.