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1.
Nat Commun ; 15(1): 7362, 2024 Aug 27.
Artigo em Inglês | MEDLINE | ID: mdl-39191725

RESUMO

We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.


Assuntos
Linfócitos T CD4-Positivos , Linfócitos T CD8-Positivos , Neoplasias , Humanos , Linfócitos T CD8-Positivos/metabolismo , Linfócitos T CD4-Positivos/metabolismo , Neoplasias/genética , Neoplasias/imunologia , Neoplasias/patologia , Perfilação da Expressão Gênica/métodos , Transcriptoma , Aprendizado Profundo , Biologia Computacional/métodos , Linfócitos do Interstício Tumoral/imunologia , Regulação Neoplásica da Expressão Gênica
2.
Database (Oxford) ; 20222022 06 23.
Artigo em Inglês | MEDLINE | ID: mdl-35735230

RESUMO

Experimental tools and resources, such as animal models, cell lines, antibodies, genetic reagents and biobanks, are key ingredients in biomedical research. Investigators face multiple challenges when trying to understand the availability, applicability and accessibility of these tools. A major challenge is keeping up with current information about the numerous tools available for a particular research problem. A variety of disease-agnostic projects such as the Mouse Genome Informatics database and the Resource Identification Initiative curate a number of types of research tools. Here, we describe our efforts to build upon these resources to develop a disease-specific research tool resource for the neurofibromatosis (NF) research community. This resource, the NF Research Tools Database, is an open-access database that enables the exploration and discovery of information about NF type 1-relevant animal models, cell lines, antibodies, genetic reagents and biobanks. Users can search and explore tools, obtain detailed information about each tool as well as read and contribute their observations about the performance, reliability and characteristics of tools in the database. NF researchers will be able to use the NF Research Tools Database to promote, discover, share, reuse and characterize research tools, with the goal of advancing NF research. Database URL: https://tools.nf.synapse.org/.


Assuntos
Pesquisa Biomédica , Neurofibromatoses , Animais , Bases de Dados Factuais , Camundongos , Reprodutibilidade dos Testes
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