Dataset Information

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

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.

SUBMITTER: Leung ML

PROVIDER: S-EPMC6949293 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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

Leung Marco L ML Watson Deborah J DJ Vaccaro Courtney N CN Mafra Fernanda F Wenocur Adam A Wang Tiancheng T Hakonarson Hakon H Santani Avni A

Scientific data 20200108 1

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 allo ...[more]

PMID: 31913291

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Project description:Citizen science (CS) contributes to the knowledge about species distributions, which is a critical foundation in the studies of invasive species, biological conservation, and response to climatic change. In this study, we assessed the value of CS for termites worldwide. First, we compared the abundance and species diversity of geo-tagged termite records in iNaturalist to that of the University of Florida termite collection (UFTC) and the Global Biodiversity Information Facility (GBIF). Second, we quantified how the combination of these data sources affected the number of genera that satisfy data requirements for ecological niche modeling. Third, we assessed the taxonomic correctness of iNaturalist termite records in the Americas at the genus and family level through expert review based on photo identification. Results showed that iNaturalist records were less abundant than those in the UFTC and in GBIF, although they complemented the latter two in selected world regions. A combination of GBIF and the UFTC led to a significant increase in the number of termite genera satisfying the abundance criterion for niche modeling compared to either of those two sources alone, whereas adding iNaturalist observations as a third source only had a moderate effect on the number of termite genera satisfying that criterion. Although research grade observations in iNaturalist require a community-supported and agreed upon identification (ID) below the family taxonomic rank, our results indicated that iNaturalist data do not exhibit a higher taxonomic classification accuracy when they are designated research grade. This means that non-research grade observations can be used to more completely map the presence of termite locations in certain geographic locations without significantly jeopardizing data quality. We concluded that CS termite observation records can, to some extent, complement expert termite collections in terms of geographic coverage and species diversity. Based on recent data contribution patterns in CS data, the role of CS termite contributions is expected to grow significantly in the near future.

Dataset Information

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

Publications

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

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