CancerSCEM: a database of single-cell expression map across various human cancers

Author:

Zeng Jingyao123ORCID,Zhang Yadong123,Shang Yunfei1234,Mai Jialin1234,Shi Shuo1234,Lu Mingming1234,Bu Congfan123,Zhang Zhewen123,Zhang Zaichao5,Li Yang6,Du Zhenglin123ORCID,Xiao Jingfa1234ORCID

Affiliation:

1. National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China

2. China National Center for Bioinformation, Beijing 100101, China

3. CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China

4. University of Chinese Academy of Sciences, Beijing 100049, China

5. Department of Biology, The University of Western Ontario, London, Ontario N6A 5B7, Canada

6. Beijing Tongren Eye Center, Beijing key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China

Abstract

Abstract With the proliferating studies of human cancers by single-cell RNA sequencing technique (scRNA-seq), cellular heterogeneity, immune landscape and pathogenesis within diverse cancers have been uncovered successively. The exponential explosion of massive cancer scRNA-seq datasets in the past decade are calling for a burning demand to be integrated and processed for essential investigations in tumor microenvironment of various cancer types. To fill this gap, we developed a database of Cancer Single-cell Expression Map (CancerSCEM, https://ngdc.cncb.ac.cn/cancerscem), particularly focusing on a variety of human cancers. To date, CancerSCE version 1.0 consists of 208 cancer samples across 28 studies and 20 human cancer types. A series of uniformly and multiscale analyses for each sample were performed, including accurate cell type annotation, functional gene expressions, cell interaction network, survival analysis and etc. Plus, we visualized CancerSCEM as a user-friendly web interface for users to browse, search, online analyze and download all the metadata as well as analytical results. More importantly and unprecedentedly, the newly-constructed comprehensive online analyzing platform in CancerSCEM integrates seven analyze functions, where investigators can interactively perform cancer scRNA-seq analyses. In all, CancerSCEM paves an informative and practical way to facilitate human cancer studies, and also provides insights into clinical therapy assessments.

Funder

Chinese Academy of Sciences

National Natural Science Foundation of China

National Key Research Program of China

Chinese Academy of Sciences Key Technology Talent Program

China Postdoctoral Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Genetics

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