This Docker image runs based on rocker/verse and provides the necessary packages, data files, and R Markdown file for a WGCNA-based gene co-expression network analysis on publicly available brain expression data.
Docker image hosted at https://hub.docker.com/r/kkhaichau/weighted_networks
docker run -p 8787:8787 -v /your/working/directory:/home/rstudio/work kkhaichau/weighted_networksThen, launch a web browser, navigate to localhost:8787, and run the tutorial.
LOGIN:
Username = rstudio
Password = rstudio
Recommended Docker settings include:
- CPUs: 2
- Memory: 4096 MB
References
- Allen Institute for Brain Science (2018). BrainSpan Atlas of the Developing Human Brain. RNA-seq Gencode v10 summarized to genes. Available from https://brainspan.org
- Chen, E. Y., Tan, C. M., Kou, Y., Duan, Q., Wang, Z., Meirelles, G. V., … Ma’ayan, A. (2013). Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics, 14, 128. http://doi.org/10.1186/1471-2105-14-128
- Langfelder, P., & Horvath, S. (2008). WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics, 9, 559. http://doi.org/10.1186/1471-2105-9-559
- Kuleshov, M. V., Jones, M. R., Rouillard, A. D., Fernandez, N. F., Duan, Q., Wang, Z., … Ma’ayan, A. (2016). Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Research, 44(Web Server issue), W90–W97. http://doi.org/10.1093/nar/gkw377