scCrab: A Reference-Guided Cancer Cell Identification Method based on Bayesian Neural Networks.

Journal: Interdisciplinary sciences, computational life sciences
PMID:

Abstract

Cancer is a significant global public health concern, where early detection can greatly enhance curative outcomes. Therefore, the identification of cancer cells holds significant importance as the primary method for cancer diagnosis. The advancement of single-cell RNA sequencing (scRNA-seq) technology has made it possible to address the problem of cancer cell identification at the single-cell level more efficiently with computational methods, as opposed to the time-consuming and less reproducible manual identification methods. However, existing computational methods have shown suboptimal identification performance and a lack of capability to incorporate external reference data as prior information. Here, we propose scCrab, a reference-guided automatic cancer cell identification method, which performs ensemble learning based on a Bayesian neural network (BNN) with multi-head self-attention mechanisms and a linear regression model. Through a series of experiments on various datasets, we systematically validated the superior performance of scCrab in both intra- and inter-dataset predictions. Besides, we demonstrated the robustness of scCrab to dropout rate and sample size, and conducted ablation experiments to investigate the contributions of each component in scCrab. Furthermore, as a dedicated model for cancer cell identification, scCrab effectively captures cancer-related biological significance during the identification process.

Authors

  • Heyang Hua
    School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, China.
  • Wenxin Long
    School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, China.
  • Yan Pan
    Department of Gastroenterology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, China.
  • Siyu Li
    School of Life Sciences, Jilin University, Changchun 130012, China.
  • Jianyu Zhou
    Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, Sichuan, 611130, China.
  • Haixin Wang
    Sichuan Provincial Key Laboratory for Human Disease Gene Study, Center for Medical Genetics, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
  • Shengquan Chen
    MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST, Beijing, 100084, China.