Evidence map›Paper›PMID 27075447›Full record

ReviewHuman genetics2016

Novel bioinformatic developments for exome sequencing.

Stefan H Lelieveld, Joris A Veltman, Christian Gilissen

Abstract readReview
In one paragraph

Review in Human genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. InnovativeFrontiers in genetics · 2022
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Genetic Landscape of Rett Syndrome Spectrum: Improvements and Challenges.International journal of molecular sciences · 2019
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Big Data Analytics for Genomic Medicine.International journal of molecular sciences · 2017
    Review
  18. Article
  19. Article
  20. Review
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

3 authors.

Stefan H LelieveldDepartment of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands.
Joris A VeltmanDepartment of Human Genetics, Donders Centre for Neuroscience, Radboudumc, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands.
Christian GilissenDepartment of Human Genetics, Donders Centre for Neuroscience, Radboudumc, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands. christian.gilissen@radboudumc.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the widespread adoption of next generation sequencing technologies by the genetics community and the rapid decrease in costs per base, exome sequencing has become a standard within the repertoire of genetic experiments for both research and diagnostics. Although bioinformatics now offers standard solutions for the analysis of exome sequencing data, many challenges still remain; especially the increasing scale at which exome data are now being generated has given rise to novel challenges in how to efficiently store, analyze and interpret exome data of this magnitude. In this review we discuss some of the recent developments in bioinformatics for exome sequencing and the directions that this is taking us to. With these developments, exome sequencing is paving the way for the next big challenge, the application of whole genome sequencing.

Indexed as

Computational BiologyGenome, HumanExomeHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNA

Identifiers

PMID27075447
PMCPMC4883269

What OpenQuestion holds

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LicenceCC BY
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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.