Evidence map›Paper›PMID 30223769›Full record

ArticleBMC genomics2018

Systematic evaluation of signal-to-noise ratio in variant detection from single cell genome multiple displacement amplification and exome sequencing.

Anita T Simonsen, Marcus C Hansen, Eigil Kjeldsen, Peter L Møller, Johnny J Hindkjær, Peter Hokland, Anni Aggerholm

Abstract readEvaluation Study
In one paragraph

Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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  5. Article
  6. Cancer evolution: Darwin and beyond.The EMBO journal · 2021
    Review
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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.

Anita T SimonsenDepartment of Hematology, Aarhus University Hospital, Aarhus, Denmark.
Marcus C HansenDepartment of Hematology, Aarhus University Hospital, Aarhus, Denmark. marcus@clin.au.dk.ORCID http://orcid.org/0000-0003-3083-4850
Eigil KjeldsenDepartment of Hematology, Aarhus University Hospital, Aarhus, Denmark.
Peter L MøllerDepartment of Hematology, Aarhus University Hospital, Aarhus, Denmark.
Johnny J HindkjærAAGAARD Skejby Fertility Clinic, Aarhus, Denmark.
Peter HoklandDepartment of Hematology, Aarhus University Hospital, Aarhus, Denmark.
Anni AggerholmDepartment of Hematology, Aarhus University Hospital, Aarhus, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe current literature on single cell genomic analyses on the DNA level is conflicting regarding requirements for cell quality, amplification success rates, allelic dropouts and resolution, lacking a systematic comparison of multiple cell input down to the single cell. We hypothesized that such a correlation assay would provide an approach to address the latter issues, utilizing the leukemic cell line OCI-AML3 with a known set of genetic aberrations.

resultsBy analyzing single and multiple cell replicates (2 to 50 cells) purified by micromanipulation and serial dilution we stringently assessed the signal-to-noise ratio (SNR) from single as well as a discrete number of cells based on a multiple displacement amplification method, with whole exome sequencing as signal readout. In this setting, known OCI-AML3 mutations as well as large copy number alterations could be identified, adding to the current knowledge of cytogenetic status. The presence of DNMT3A R882C, NPM1 W288 fs and NRAS Q61L was consistent, in spite of uneven allelic read depths. In contrast, at the level of single cells, we observed that one-third to half of all variants were not reproduced in the replicate sample, and this allelic mismatch displayed an exponential function of cell input. Large signature duplications were discernible from 5 cells, whereas deletions were visible down to the single cell. Thus, even under highly optimized conditions, single cell whole genome amplification and interpretation must be taken with considerable caution, given that allelic change is frequent and displays low SNR. Allelic noise is rapidly alleviated with increased cell input, and the SNR is doubled from 2 to 50 cells.

conclusionsIn conclusion, we demonstrate noisy allele distributions, when analyzing genetic aberrations within single cells relative to multiple cells. Based on the presented data we recommend that single cell analyses should include replicate cell dilution assays for a given setup for relative assessment of procedure-specific SNR to ensure that the resolution supports the specific hypotheses.

Indexed as

Genetic VariationGenomicsSignal-To-Noise RatioSingle-Cell AnalysisAllelesAllelic ImbalanceCell CountCell Line, TumorCytogenetic AnalysisDNA Copy Number VariationsExome SequencingGenome, HumanHumansNucleophosminNucleophosminAllele dropoutNGSSignal-to-noise ratioSingle cell sequencingSparse cell sequencingWhole exome sequencing

Identifiers

PMID30223769
PMCPMC6142419

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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.