Evidence map›Paper›PMID 24507442›Full record

ArticleBMC genomics2014

SASI-Seq: sample assurance Spike-Ins, and highly differentiating 384 barcoding for Illumina sequencing.

Michael A Quail, Miriam Smith, David Jackson, Steven Leonard, Thomas Skelly, Harold P Swerdlow, Yong Gu, Peter Ellis

Abstract read
In one paragraph

Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

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  8. Genomic diversity ofWellcome open research · 2020
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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

8 authors.

Michael A QuailWellcome Trust Sanger Institute, Hinxton CB10 1SA, Cambs, UK. mq1@sanger.ac.uk.
Miriam Smith
David Jackson
Steven Leonard
Thomas Skelly
Harold P Swerdlow
Yong Gu
Peter Ellis

Funding

Wellcome TrustWellcome Trust 098051
6 · The paper itself

Abstract

backgroundA minor but significant fraction of samples subjected to next-generation sequencing methods are either mixed-up or cross-contaminated. These events can lead to false or inconclusive results. We have therefore developed SASI-Seq; a process whereby a set of uniquely barcoded DNA fragments are added to samples destined for sequencing. From the final sequencing data, one can verify that all the reads derive from the original sample(s) and not from contaminants or other samples.

resultsBy adding a mixture of three uniquely barcoded amplicons, of different sizes spanning the range of insert sizes one would normally use for Illumina sequencing, at a spike-in level of approximately 0.1%, we demonstrate that these fragments remain intimately associated with the sample. They can be detected following even the tightest size selection regimes or exome enrichment and can report the occurrence of sample mix-ups and cross-contamination.As a consequence of this work, we have designed a set of 384 eleven-base Illumina barcode sequences that are at least 5 changes apart from each other, allowing for single-error correction and very low levels of barcode misallocation due to sequencing error.

conclusionSASI-Seq is a simple, inexpensive and flexible tool that enables sample assurance, allows deconvolution of sample mix-ups and reports levels of cross-contamination between samples throughout NGS workflows.

Indexed as

DNADNA ContaminationGene LibraryHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNADNA

Identifiers

PMID24507442
PMCPMC4008303

What OpenQuestion holds

Textmetadata
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.