Protocol to estimate cell type proportions from bulk RNA-seq using DAISM-DNN.

Journal: STAR protocols
Published Date: Jul 31, 2022

Abstract

Computational protocols for cell type deconvolution from bulk RNA-seq data have been used to understand cellular heterogeneity in disease-related samples, but their performance can be impacted by batch effect among datasets. Here, we present a DAISM-DNN protocol to achieve robust cell type proportion estimation on the target dataset. We describe the preparation of calibrated samples from human blood samples. We then detail steps to train a dataset-specific deep neural network (DNN) model and cell type proportion estimation using the trained model. For complete details on the use and execution of this protocol, please refer to Lin et al. (2022).

Authors

  • Yating Lin
    School of Informatics, Xiamen University, Xiamen 361005, China.
  • Shangze Wu
    School of Informatics, Xiamen University, Xiamen 361005, China.
  • Xu Xiao
    Key Laboratory of Underwater Acoustics Environment, Chinese Academy of Sciences, Beijing 100190, China.
  • Jingbo Zhao
    Amoy Diagnostics, Xiamen 361000, China.
  • Minshu Wang
    National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361005, China; School of Medicine, Xiamen University, Xiamen 361102, China.
  • Haojun Li
    School of Informatics, Xiamen University, Xiamen 361005, China.
  • Kejia Wang
    Graduate School of Biomedical Engineering, University of New South Wales, Sydney 2033, Australia.
  • Minwei Zhang
    Department of Critical Care Medicine, The First Affiliated Hospital of Xiamen University, Xiamen 361003, China.
  • Frank Zheng
    Amoy Diagnostics, Xiamen 361000, China.
  • Wenxian Yang
    Aginome Scientific Pte. Ltd., Xiamen, China.
  • Lei Zhang
    Division of Gastroenterology, Union Hospital, Tongji Medical College Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Jiahuai Han
    State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen 361102, China; National Institute for Data Science in Health and Medicine, School of Medicine, Xiamen University, Xiamen 361102, China. Electronic address: jhan@xmu.edu.cn.
  • Rongshan Yu
    School of Informatics, Xiamen University, Xiamen, China. rsyu@xmu.edu.cn.

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