Evidence map›Paper›PMID 24409309›Full record

ArticlePloS one2014

Assessment of whole genome amplification for sequence capture and massively parallel sequencing.

Johanna Hasmats, Henrik Gréen, Cedric Orear, Pierre Validire, Mikael Huss, Max Käller, Joakim Lundeberg

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Precision Oncology Decision Support: Current Approaches and Strategies for the Future.Clinical cancer research : an official journal of the American Association for Cancer Research · 2018
    Review
  2. Review
  3. Article
  4. Resurrection of Dormant Daphnia magna: Protocol and Applications.Journal of visualized experiments : JoVE · 2018
    Article
  5. Article
  6. 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

7 authors.

Johanna HasmatsScience for Life Laboratory, School of Biotechnology, Division of Gene Technology, Royal Institute of Technology, Stockholm, Sweden.
Henrik GréenScience for Life Laboratory, School of Biotechnology, Division of Gene Technology, Royal Institute of Technology, Stockholm, Sweden ; Department of Forensic Genetics and Forensic Toxicology, National Board of Forensic Medicine, Linköping, Sweden ; Clinical Pharmacology, Department of Health and Medical Sciences, Linköping University, Linköping, Sweden.
Cedric OrearGenomics Unit, Institut Gustave Roussy, Villejuif, France.
Pierre ValidireDepartment of Pathology, Institut Mutualiste Montsouris, Paris, France.
Mikael HussScience for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden.
Max KällerScience for Life Laboratory, School of Biotechnology, Division of Gene Technology, Royal Institute of Technology, Stockholm, Sweden.
Joakim LundebergScience for Life Laboratory, School of Biotechnology, Division of Gene Technology, Royal Institute of Technology, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exome sequence capture and massively parallel sequencing can be combined to achieve inexpensive and rapid global analyses of the functional sections of the genome. The difficulties of working with relatively small quantities of genetic material, as may be necessary when sharing tumor biopsies between collaborators for instance, can be overcome using whole genome amplification. However, the potential drawbacks of using a whole genome amplification technology based on random primers in combination with sequence capture followed by massively parallel sequencing have not yet been examined in detail, especially in the context of mutation discovery in tumor material. In this work, we compare mutations detected in sequence data for unamplified DNA, whole genome amplified DNA, and RNA originating from the same tumor tissue samples from 16 patients diagnosed with non-small cell lung cancer. The results obtained provide a comprehensive overview of the merits of these techniques for mutation analysis. We evaluated the identified genetic variants, and found that most (74%) of them were observed in both the amplified and the unamplified sequence data. Eighty-nine percent of the variations found by WGA were shared with unamplified DNA. We demonstrate a strategy for avoiding allelic bias by including RNA-sequencing information.

Indexed as

Genome, HumanHigh-Throughput Nucleotide SequencingCarcinoma, Non-Small-Cell LungFemaleGenetic VariationGenomicsHumansLung NeoplasmsMaleMutationReproducibility of ResultsSequence Analysis, DNASequence Analysis, RNA

Identifiers

PMID24409309
PMCPMC3883664

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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.