Browsing by Author "Wham, Briana Ezray"

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    FASTA/FASTQ Data Curation Primer
    (Data Curation Network, 2023) Bowman, Laura; Sheridan, Shannon; Wham, Briana Ezray; Wright, Sarah
    Background: FASTA and FASTQ are commonly used text-based file formats for storing and sharing nucleotide (DNA or RNA) sequences and/or amino acid (protein) sequences, and are the main focus of this primer. FASTA and FASTQ are the recognized standard file formats for bioinformatics studies, including next-generation sequencing (NGS), enabling large-scale exchange of data and information associated with massive sequencing projects (Sielemann et al., 2020). NGS refers to high-throughput technologies for large-scale DNA sequencing such as whole genome sequencing, whole-exome sequencing (WES, WXS), RNA-seq, miRNA-seq, ChIP-seq, and DNA Methylation. NGS experiments generate billions of short sequence reads for each sample which when combined with description and annotations can result in files ranging from a few to hundreds of gigabytes (Zhang, 2016). FASTA and FASTQ files can be opened by many sequence alignment applications or text editors. There are various applications that can convert .fasta files.
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    New and Improved: Refining the CURATE(D) model and developing online modules
    (2022) Wham, Briana Ezray; Narlock, Mikala R.
    The CURATE(D) model for data curation is a useful teaching tool for demonstrating data curation best practices: while practical and structured enough to provide a foundation for learners, it also provides enough flexibility to be adaptive for different disciplines and data format needs. In the past year, the Data Curation Network has undertaken efforts to expand this model, incorporate ethical concerns, and make it accessible online via learning modules. In this presentation, attendees will learn more about the CURATE(D) 2.0 model and the collaborative revision process, as well as have early access to a beta version of the online learning modules. Participants will also be invited to provide asynchronous feedback on the modules during and following the session. Presented at the 2022 Midwest Data Librarian Symposium.