Francesca Finotello
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Articles (10)
Year:
2025
Summary Transcriptome deconvolution has emerged as a reliable technique to estimate cell-type abundances from bulk RNA sequencing data. Unlike their human equivalents, methods to quantify the cellular composition of complex tissues from murine transcriptomics are sparse and sometimes not easy to use. We extended the immunedeconv R package to facilitate the deconvolution of mouse transcriptomics, enabling the quantification of murine immune-cell types using 13 different methods. Through immunedeconv, we further offer the possibility of tweaking cell signatures used by deconvolution methods, providing custom annotations tailored for specific cell types and tissues. These developments strongly facilitate the study of the immune-cell composition of mouse models and further open new avenues in the investigation of the cellular composition of other tissues and organisms. Availability and implementation The R package and the documentation are available at https://github.com/omnideconv/immunedeconv.
Year:
2024
Year:
2024
Year:
2022
Year:
2022
Year:
2021
Year:
2020
Year:
2020
Year:
2020
Year:
2020
Collaborators (6)
Katharina Günther
University of Innsbruck
Francisco Ayala de la Peña
Profesor Titular (Oncología Médica)
Universidad de Murcia
Alexander Kirchmair
Medical University of Innsbruck
Zlatko Trajanoski
Professor
Medical University of Innsbruck
Markus List
Technical University of Munich
Frank Edenhofer
Prof., Head Dpt. Genomics, Stem Cell Biology & Regenerative Medicine
University of Innsbruck
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