Shixiang Wang

PDF

Shixiang Wang

Education

  • 2016.09 ~ Present, Ph.D Student, Cancer Biology (focusing on cancer informatics),
    ShanghaiTech. University, Shanghai, China

  • 2012.09 ~ 2016.07, B.E. Biomedical Engineering,
    University of Electronic Science and Technology of China, Chengdu, China

Professional skills

  • Programming levels:
    • R \(\star\star\star\star\star\)
    • Shell \(\star\star\star\)
    • Python \(\star\star\star\)
    • Golang \(\star\star\)
  • Data analysis. I have advanced experience in using R and Shell for data preprocessing, data cleaning and data interpretation.
  • Statistics. I have moderate experience in using R for statistical modeling and data visualization.
  • Package/pipeline development. I master developing pure R packages and have a little experience in Python package and R Shiny development. I can combine multiple languages to create analysis pipeline.
  • Genomic analysis. I can process raw genomic data and analyze them. I have moderate experience in somatic variant calling (including SNV, INDEL and CNV), differential expression analysis and enrichment analysis.
  • Clinical analysis. I know how to construct survival models and interpret results.
  • Machine learning. I know how to do machine learning (including deep learning) and have applied some technologies to my projects.
  • Writing. I like to write with R Markdown (including Markdown) and share my knowledge to others in many ways (e.g. GitHub Issue, Jianshu, Wechat, and etc.).

Developments

More activities about my development and contribution can be viewed at github.com/ShixiangWang.

Publications

Total citations: 106. (Data source: Google Scholar. Update time: 2020-08-02)

  • Wang, S., He, Z., Wang, X., Li, H., & Liu, X. S. (2019). Antigen presentation and tumor immunogenicity in cancer immunotherapy response prediction. eLife, 8, e49020. https://doi.org/10.7554/eLife.49020 (PDF)
  • Wang, S., He, Z., Wang, X., Li, H., Wu, T., Sun, X., … & Liu, X. S. (2019). Can tumor mutational burden determine the most effective treatment for lung cancer patients?. Lung Cancer Management. https://doi.org/10.2217/lmt-2019-0013 (PDF)
  • Wang, S., Cowley, L. A., & Liu, X. S. (2019). Sex differences in Cancer immunotherapy efficacy, biomarkers, and therapeutic strategy. Molecules, 24(18), 3214. (PDF)
  • Wang, S. & Liu, X. S. (2019). The UCSCXenaTools R package: a toolkit for accessing genomics data from UCSC Xena platform, from cancer multi-omics to single-cell RNA-seq. Journal of Open Source Software, 4(40), 1627, https://doi.org/10.21105/joss.01627 (PDF)
  • He, Z., Wang, S., Shao, Y., Zhang, J., Wu, X., Chen, Y., … & Liu, X. S. (2019). Ras downstream effector GGCT alleviates oncogenic stress. iScience. (PDF)
  • Wang, S., Zhang, J., He, Z., Wu, K., & Liu, X. S. (2019). The predictive power of tumor mutational burden in lung cancer immunotherapy response is influenced by patients’ sex. International journal of cancer, 145(10), 2840-2849. (PDF)
  • Wang, S., Jia, M., He, Z., & Liu, X. S. (2018). APOBEC3B and APOBEC mutational signature as potential predictive markers for immunotherapy response in non-small cell lung cancer. Oncogene, 37(29), 3924-3936. (PDF)