Statistical and machine learning methods for spatially resolved transcriptomics data analysis

Zexian Zeng, Yawei Li, Yiming Li, Yuan Luo
2022 Genome Biology  
AbstractThe recent advancement in spatial transcriptomics technology has enabled multiplexed profiling of cellular transcriptomes and spatial locations. As the capacity and efficiency of the experimental technologies continue to improve, there is an emerging need for the development of analytical approaches. Furthermore, with the continuous evolution of sequencing protocols, the underlying assumptions of current analytical methods need to be re-evaluated and adjusted to harness the increasing
more » ... ta complexity. To motivate and aid future model development, we herein review the recent development of statistical and machine learning methods in spatial transcriptomics, summarize useful resources, and highlight the challenges and opportunities ahead.
doi:10.1186/s13059-022-02653-7 pmid:35337374 pmcid:PMC8951701 fatcat:d7qddix4tjfppi265o7wilph5i