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. 2025 Jan 7;37(1):7-11.
doi: 10.1016/j.cmet.2024.09.001. Epub 2024 Oct 1.

HumanIslets.com: Improving accessibility, integration, and usability of human research islet data

Affiliations

HumanIslets.com: Improving accessibility, integration, and usability of human research islet data

Jessica D Ewald et al. Cell Metab. .

Abstract

HumanIslets.com supports diabetes research by offering easy access to islet phenotyping data, analysis tools, and data download. It includes molecular omics, islet and cellular function assays, tissue processing metadata, and phenotypes from 547 donors. As it expands, the resource aims to improve human islet data quality, usability, and accessibility.

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Conflict of interest statement

Declaration of interests A.L.G.’s spouse is an employee of Genentech and holds stock options in Roche. A.R.P. serves on the Scientific Advisory Committee for Encellin Inc. J.X. is founder of XiaLab Analytics, which provides omics data science training and support.

Figures

Figure 1.
Figure 1.. Corrections for culture time and non-endocrine cell proportions
(A–C) Impact of culture time on expression of FGF2 measured by RNA-seq (A), NanoString (B), or proteomics (C). (D) Impact of adjusting for culture time on gene-level p values for the association of bulk RNA-seq data and diabetes status (T2D vs. none). Transcripts were significant (FDR < 0.05) both with and without adjusting for culture time (dark gray), only when adjusting for culture time (red), only when not adjusting for culture time (blue), or not significant in either scenario (light gray). (E) Cell-type distributions computed from proteomic data across donors, ranked by ‘‘non-endocrine’’ cell proportions. (F) Impact of adjusting for the proportion of non-endocrine cells on protein-level p values for the association of bulk proteomics data and diabetes status (T2D vs. none). Proteins were significant (FDR < 0.05) both with and without adjusting for non-endocrine cells (dark gray), only when adjusting for non-endocrine cells (red), only when not adjusting for non-endocrine cells (blue), or not significant in either scenario (light gray). (G) Adjusting for the proportion of non-endocrine cells increases the proportion of α and β cell-linked RNA-seq and proteomics features (adjusted p < 0.05) when comparing T2D versus no diabetes (non-adjusted RNA-seq, n = 117; adjusted RNA-seq, n = 90; non-adjusted proteomics, n = 134; adjusted proteomics, n = 134).

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