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PancrESS - a meta-analysis resource for understanding cell-type specific expression in the human pancreas.
Sturgill, David; Wang, Li; Arda, H Efsun.
Afiliação
  • Sturgill D; Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, 20892, USA.
  • Wang L; Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, 20892, USA.
  • Arda HE; Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, 20892, USA. efsun.arda@nih.gov.
BMC Genomics ; 25(1): 76, 2024 Jan 18.
Article em En | MEDLINE | ID: mdl-38238687
ABSTRACT

BACKGROUND:

The human pancreas is composed of specialized cell types producing hormones and enzymes critical to human health. These specialized functions are the result of cell type-specific transcriptional programs which manifest in cell-specific gene expression. Understanding these programs is essential to developing therapies for pancreatic disorders. Transcription in the human pancreas has been widely studied by single-cell RNA technologies, however the diversity of protocols and analysis methods hinders their interpretability in the aggregate.

RESULTS:

In this work, we perform a meta-analysis of pancreatic single-cell RNA sequencing data. We present a database for reference transcriptome abundances and cell-type specificity metrics. This database facilitates the identification and definition of marker genes within the pancreas. Additionally, we introduce a versatile tool which is freely available as an R package, and should permit integration into existing workflows. Our tool accepts count data files generated by widely-used single-cell gene expression platforms in their original format, eliminating an additional pre-formatting step. Although we designed it to calculate expression specificity of pancreas cell types, our tool is agnostic to the biological source of count data, extending its applicability to other biological systems.

CONCLUSIONS:

Our findings enhance the current understanding of expression specificity within the pancreas, surpassing previous work in terms of scope and detail. Furthermore, our database and tool enable researchers to perform similar calculations in diverse biological systems, expanding the applicability of marker gene identification and facilitating comparative analyses.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pancreatopatias / Software Tipo de estudo: Guideline / Prognostic_studies / Systematic_reviews Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pancreatopatias / Software Tipo de estudo: Guideline / Prognostic_studies / Systematic_reviews Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article