Evidence map›Paper›PMID 27670852›Full record

ArticleScientific reports2016

Next Generation Sequencing of Pooled Samples: Guideline for Variants' Filtering.

Santosh Anand, Eleonora Mangano, Nadia Barizzone, Roberta Bordoni, Melissa Sorosina, Ferdinando Clarelli, Lucia Corrado, Filippo Martinelli Boneschi, Sandra D'Alfonso, Gianluca De Bellis

Erratum issuedAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 55 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 1 pooled it
–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

55 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Genomic architecture of insertion-deletion (indel) variants in beetal goats of India.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
    Article
  5. Article
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  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
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  13. Article
  14. Sampling strategies for genotyping common bean (Frontiers in plant science · 2024
    Article
  15. Article
  16. Deep Learning in Population Genetics.Genome biology and evolution · 2023
    Article
  17. Article
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Santosh AnandInstitute for Biomedical Technologies, National Research Council, Segrate (MI), Italy.
Eleonora ManganoInstitute for Biomedical Technologies, National Research Council, Segrate (MI), Italy.
Nadia BarizzoneInterdisciplinary Research Center of Autoimmune Diseases IRCAD, University of Eastern Piedmont, Novara, Italy.
Roberta BordoniInstitute for Biomedical Technologies, National Research Council, Segrate (MI), Italy.
Melissa SorosinaLaboratory of Human Genetics of Neurological Disorders, Institute of Experimental Neurology (INSPE), Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy.
Ferdinando ClarelliLaboratory of Human Genetics of Neurological Disorders, Institute of Experimental Neurology (INSPE), Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy.
Lucia CorradoInterdisciplinary Research Center of Autoimmune Diseases IRCAD, University of Eastern Piedmont, Novara, Italy.
Filippo Martinelli BoneschiLaboratory of Human Genetics of Neurological Disorders, Institute of Experimental Neurology (INSPE), Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy.
Sandra D'AlfonsoInterdisciplinary Research Center of Autoimmune Diseases IRCAD, University of Eastern Piedmont, Novara, Italy.
Gianluca De BellisInstitute for Biomedical Technologies, National Research Council, Segrate (MI), Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sequencing large number of individuals, which is often needed for population genetics studies, is still economically challenging despite falling costs of Next Generation Sequencing (NGS). Pool-seq is an alternative cost- and time-effective option in which DNA from several individuals is pooled for sequencing. However, pooling of DNA creates new problems and challenges for accurate variant call and allele frequency (AF) estimation. In particular, sequencing errors confound with the alleles present at low frequency in the pools possibly giving rise to false positive variants. We sequenced 996 individuals in 83 pools (12 individuals/pool) in a targeted re-sequencing experiment. We show that Pool-seq AFs are robust and reliable by comparing them with public variant databases and in-house SNP-genotyping data of individual subjects of pools. Furthermore, we propose a simple filtering guideline for the removal of spurious variants based on the Kolmogorov-Smirnov statistical test. We experimentally validated our filters by comparing Pool-seq to individual sequencing data showing that the filters remove most of the false variants while retaining majority of true variants. The proposed guideline is fairly generic in nature and could be easily applied in other Pool-seq experiments.

Identifiers

PMID27670852
PMCPMC5037392

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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.