Evidence map›Paper›PMID 28049435›Full record

ArticleBMC genomics2017

Detecting very low allele fraction variants using targeted DNA sequencing and a novel molecular barcode-aware variant caller.

Chang Xu, Mohammad R Nezami Ranjbar, Zhong Wu, John DiCarlo, Yexun Wang

Abstract read
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Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.

0numbers the graph read from it
0cells of the map it votes in
66citing 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

66 citing papers in PubMed.

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  19. Effect of Antigen Retrieval on Genomic DNA From Immunodissected Samples.The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society · 2022
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6 more citing papers are in PubMed but not listed here.

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

5 authors.

Chang XuLife Science Research and Foundation, Qiagen Sciences, Inc., 6951 Executive Way, Frederick, Maryland, 21703, USA. chang.xu@qiagen.com.
Mohammad R Nezami RanjbarLife Science Research and Foundation, Qiagen Sciences, Inc., 6951 Executive Way, Frederick, Maryland, 21703, USA.
Zhong WuLife Science Research and Foundation, Qiagen Sciences, Inc., 6951 Executive Way, Frederick, Maryland, 21703, USA.
John DiCarloLife Science Research and Foundation, Qiagen Sciences, Inc., 6951 Executive Way, Frederick, Maryland, 21703, USA.
Yexun WangLife Science Research and Foundation, Qiagen Sciences, Inc., 6951 Executive Way, Frederick, Maryland, 21703, USA. yexun.wang@qiagen.com.ORCID 0000-0003-0362-1892

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDetection of DNA mutations at very low allele fractions with high accuracy will significantly improve the effectiveness of precision medicine for cancer patients. To achieve this goal through next generation sequencing, researchers need a detection method that 1) captures rare mutation-containing DNA fragments efficiently in the mix of abundant wild-type DNA; 2) sequences the DNA library extensively to deep coverage; and 3) distinguishes low level true variants from amplification and sequencing errors with high accuracy. Targeted enrichment using PCR primers provides researchers with a convenient way to achieve deep sequencing for a small, yet most relevant region using benchtop sequencers. Molecular barcoding (or indexing) provides a unique solution for reducing sequencing artifacts analytically. Although different molecular barcoding schemes have been reported in recent literature, most variant calling has been done on limited targets, using simple custom scripts. The analytical performance of barcode-aware variant calling can be significantly improved by incorporating advanced statistical models.

resultsWe present here a highly efficient, simple and scalable enrichment protocol that integrates molecular barcodes in multiplex PCR amplification. In addition, we developed smCounter, an open source, generic, barcode-aware variant caller based on a Bayesian probabilistic model. smCounter was optimized and benchmarked on two independent read sets with SNVs and indels at 5 and 1% allele fractions. Variants were called with very good sensitivity and specificity within coding regions.

conclusionsWe demonstrated that we can accurately detect somatic mutations with allele fractions as low as 1% in coding regions using our enrichment protocol and variant caller.

Indexed as

AllelesBase SequenceDNA Barcoding, TaxonomicGene FrequencyGenetic VariationComputational BiologyModels, StatisticalMultiplex Polymerase Chain ReactionReproducibility of ResultsSensitivity and SpecificityMolecular barcodePCR enrichmentStatistical modelVariant caller

Identifiers

PMID28049435
PMCPMC5209917

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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.