SRTpipeline is a powerful and easy-to-use R package for processing and analyzing spaitally resolved transcriptomics (SRT) data by providing step-by-step tutorials. SRTpipeline integrates a series of our developed methods and commonly used analyses tools. SRTpipeline is able to handle single data batch and multiple data batches by considering the non-cellular effects such as batch effects.
For single data batch, it has the following functions:
- (Spatial) dimension reduction
- Spatial clustering
- Joint dimension reduction and spatial clustering
- SRT embeddings for visualization
- DEG analysis
- Trajectory inference
- Conditional spaital variation analysis
- SRT deconvolution analysis
For multiple data batches, it has the following functions:
- (Spatial) dimension reduction by removing batch effects
- Spatial clustering by removing batch effects
- SRT embeddings for visualization
- Recover comparable gene expression matrices among datasets
- Combined DEG analysis
- Combined trajectory inference
You can install the development version of SRTpipeline from GitHub with:
# install.packages("devtools")
devtools::install_github("feiyoung/SRTpipeline")
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To cite {SRTpipeline} please use:
Yi Yang, Xingjie Shi, Wei Liu, Qiuzhong Zhou, Mai Chan Lau, Jeffrey Chun Tatt Lim, Lei Sun, Cedric Chuan Young Ng, Joe Yeong, Jin Liu, SC-MEB: spatial clustering with hidden Markov random field using empirical Bayes, Briefings in Bioinformatics, Volume 23, Issue 1, January 2022, bbab466, https://doi.org/10.1093/bib/bbab466
Wei Liu, Xu Liao, Yi Yang, Huazhen Lin, Joe Yeong, Xiang Zhou, Xingjie Shi, Jin Liu, Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data, Nucleic Acids Research, Volume 50, Issue 12, 8 July 2022, Page e72, https://doi.org/10.1093/nar/gkac219
Wei Liu, Xu Liao, Ziye Luo, Yi Yang, Mai Chan Lau, Yuling Jiao, Xingjie Shi, Weiwei Zhai, Hongkai Ji, Joe Yeong, Jin Liu. Probabilistic embedding and clustering with alignment for spatial transcriptomics data integration with PRECAST. Nat Commun 14, 296 (2023). https://doi.org/10.1038/s41467-023-35947-w
Xiao Zhang, Wei Liu, Fangda Song, Jin Liu, iSC.MEB: an R package for multi-sample spatial clustering analysis of spatial transcriptomics data, Bioinformatics Advances, 2023;, vbad019, https://doi.org/10.1093/bioadv/vbad019
Xingjie Shi, Yi Yang, Xiaohui Ma, Zhenxing Guo, Jin Liu, Probabilistic cell/domain-type assignment of spatial transcriptomics data with SpatialAnno, bioRxiv 2023.02.08.527590; doi: https://doi.org/10.1101/2023.02.08.527590
For more information, documentation and examples of use, see also the
{SRTpipeline} website at
SRTpipeline.