DeepDeconUQ estimates malignant cell fraction prediction intervals in bulk RNA-seq tissue

Accurate estimation of malignant cell fractions in tissues plays a critical role in cancer diagnosis, prognosis, and subsequent treatment decisions. However, most currently available methods provide only point estimates, neglecting the quantification of uncertainties, which is essential for both cli...

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Vydáno v:	PLoS computational biology Ročník 21; číslo 6; s. e1013133
Hlavní autoři:	Huang, Jiawei, Du, Yuxuan, Kelly, Kevin R., Lv, Jinchi, Fan, Yingying, Zhong, Jiang F., Sun, Fengzhu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Public Library of Science 04.06.2025 Public Library of Science (PLoS)
Témata:	Accuracy Artificial neural networks Biology and Life Sciences Calibration Cancer Computational Biology - methods Computer and Information Sciences Conformity Datasets Deep Learning Estimates Gene expression Gene sequencing Genetic aspects Humans Intervals Lower bounds Medical research Medicine and Health Sciences Methods Neoplasms - genetics Neoplasms - pathology Neural networks Neural Networks, Computer Performance evaluation Predictions Quantiles Research and analysis methods Ribonucleic acid RNA RNA sequencing RNA-Seq - methods Sequence Analysis, RNA - methods Single-Cell Analysis - methods Statistical analysis Uncertainty Validity United States
ISSN:	1553-7358, 1553-734X, 1553-7358
On-line přístup:	Získat plný text
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