PDAC single cell datasets integration and annotation for deconvolution

Poster for Bigre Days - Grenoble Feb 2025 Accuracy of bulk deconvolution algorithms to infer tumor composition is currently limited. A promissing approach consist of using single-cell referenced profiles for deconvolution. Here we present our work strategy to contribute to the creation of new robust single-cell reference profiles.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-14
DOI
https://doi.org/10.5281/zenodo.14872215
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
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article

PDAC single cell datasets integration and annotation for deconvolution

Zenodo (CERN European Organization for Nuclear Research)
Single-cell and spatial transcriptomics
article

PDAC single cell datasets integration and annotation for deconvolution

article en

Abstract

Poster for Bigre Days - Grenoble Feb 2025 Accuracy of bulk deconvolution algorithms to infer tumor composition is currently limited. A promissing approach consist of using single-cell referenced profiles for deconvolution. Here we present our work strategy to contribute to the creation of new robust single-cell reference profiles.

Zenodo (CERN European Organization for Nuclear Research)
Centre National de la Recherche Scientifique (FR), University of Abou Bekr Belkaïd (DZ), Institut de génétique et de développement de Rennes (FR)
Openalex Percentile: Top 53%
Single-cell and spatial transcriptomics
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