A search-based geographic metadata curation pipeline to refine sequencing institution information and support public health.

ABSTRACT:

Background

The National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) has amassed a vast reservoir of genetic data since its inception in 2007. These public data hold immense potential for supporting pathogen surveillance and control. However, the lack of standardized metadata and inconsistent submission practices in SRA may impede the data's utility in public health.

Methods

To address this issue, we introduce the Search-based Geographic Metadata Curation (SGMC) pipeline. SGMC utilized Python and web scraping to extract geographic data of sequencing institutions from NCBI SRA in the Cloud and its website. It then harnessed ChatGPT to refine the sequencing institution and location assignments. To illustrate the pipeline's utility, we examined the ge

SUBMITTER: Zhao K 

PROVIDER: S-EPMC10683794 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature