Evidence map›Paper›PMID 31913291›Full record

ArticleScientific data2020

Evaluating sequence data quality from the Swift Accel-Amplicon CFTR Panel.

Marco L Leung, Deborah J Watson, Courtney N Vaccaro, Fernanda Mafra, Adam Wenocur, Tiancheng Wang, Hakon Hakonarson, Avni Santani

Abstract readDataset
In one paragraph

Article in Scientific data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Marco L LeungCenter for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA. leungm@email.chop.edu.
Deborah J WatsonCenter for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Courtney N VaccaroCenter for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Fernanda MafraCenter for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Adam WenocurCenter for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Tiancheng WangCenter for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Hakon HakonarsonCenter for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.ORCID http://orcid.org/0000-0003-2814-7461
Avni SantaniCenter for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA. santani@email.chop.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cystic fibrosis (CF) is one of the most common genetic diseases worldwide with high carrier frequencies across different ethnicities. Next generation sequencing of the cystic fibrosis transmembrane conductance regulator (CFTR) gene has proven to be an effective screening tool to determine carrier status with high detection rates. Here, we evaluate the performance of the Swift Biosciences Accel-Amplicon CFTR Capture Panel using CFTR-positive DNA samples. This assay is a one-day protocol that allows for one-tube reaction of 87 amplicons that span all coding regions, 5' and 3'UTR, as well as four intronic regions. In this study, we provide the FASTQ, BAM, and VCF files on seven unique CFTR-positive samples and one normal control sample (14 samples processed including repeated samples). This method generated sequencing data with high coverage and near 100% on-target reads. We found that coverage depth was correlated with the GC content of each exon. This dataset is instrumental for clinical laboratories that are evaluating this technology as part of their carrier screening program.

Indexed as

Genetic Carrier ScreeningBase CompositionCystic FibrosisCystic Fibrosis Transmembrane Conductance RegulatorHumansSequence Analysis, DNACFTR protein, humanCystic Fibrosis Transmembrane Conductance Regulator

Identifiers

PMID31913291
PMCPMC6949293

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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.