Published June 14, 2024 | Version v2
Dataset Open

Systematic lineage tracing unveils polyclonal origin and evolution in colorectal precancer

  • 1. Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
  • 2. SIAT-HKUST Joint Laboratory of Cell Evolution and Digital Health, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
  • 3. Cancer Centre, Faculty of Health Sciences, University of Macau, Taipa, Macau, China
  • 4. MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-Sen University, Guangzhou, China
  • 5. School of Mathematical Sciences, Xiamen University, Xiamen, China
  • 6. National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China
  • 7. Ministry of Education Frontiers Science Center for Precision Oncology, University of Macau, Macau, China
  • 8. Department of Pathology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
  • 9. Department of General Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
  • 10. Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
  • 11. Department of Chemical and Biological Engineering, Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong SAR, China
  • 12. Hong Kong Center for Neurodegenerative Diseases, InnoHK, Hong Kong SAR, China
  • 13. Key Laboratory of Human Microbiome and Chronic Diseases (Sun Yat-sen University), Ministry of Education, Guangzhou, China

Description

Data and code for Systematic lineage tracing unveils polyclonal origin and evolution in colorectal precancer

This dataset contains reproducibility, pipeline and data for 4 parts of the paper, including PacBio data analysis, scRNA-seq data analysis, HumanCRC data analysis and WGS data analysis. 

See readme.txt in each folder for more details. 

Files

data_scripts.zip

Files (1.2 GB)

Name Size Download all
md5:48f301f31095a5aa76dea6341f473d7b
1.2 GB Preview Download