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...

Full description

Saved in:

Bibliographic Details
Published in:	PLoS computational biology Vol. 21; no. 6; p. e1013133
Main Authors:	Huang, Jiawei, Du, Yuxuan, Kelly, Kevin R., Lv, Jinchi, Fan, Yingying, Zhong, Jiang F., Sun, Fengzhu
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 04.06.2025 Public Library of Science (PLoS)
Subjects:	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
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!