Contributed analyses
May 11, 2021 ยท View on GitHub
Contributions
| Hackathon | Participant(s) | Title | Language | Vignette | Additional info |
|---|---|---|---|---|---|
| scNMTseq | Al J Abadi | Multi-block PLS | ![]() | ![]() | |
| scNMTseq | Wancen Mu and Michael Love | CV-MOFA | ![]() | ![]() | |
| scNMTseq | Josh Welch | LIGER analysis of scNMT-seq | ![]() | ![]() | |
| scNMTseq | Arshi Arora | MOSAIC analysis of scNMT-seq | ![]() | ![]() | |
| scProteomics | Lauren Hsu | Exploratory analyses | ![]() | ![]() | |
| scProteomics | Chen Meng | Predicting partially overlapping data | ![]() | ||
| scProteomics | Pratheepa Jeganathan | Latent Dirichlet Allocation | ![]() | ||
| scProteomics | Yingxin Lin | Integrative analysis of breast cancer survival based on spatial features | ![]() | ![]() | |
| scSpatial | Alexis Coullomb | Neighbours Aggregtion | ![]() | ||
| scSpatial | Joshua Sodicoff | Utilizing LIGER for the integration of spatial transcriptomic data | ![]() | ![]() | |
| scSpatial | Dario Righelli | SpatialExperiment Analysis | ![]() | ![]() | |
| scSpatial | Amrit Singh | seqFISH+scRNASeq integration using semi-supervised glmnet | ![]() | ||
| scSpatial | Hang Xu | Cortex seq-FISH + scRNA data - gene selection | ![]() | ||
| scSpatial | Yuzhou Feng | sPLS-DA and MINT models for cell type prediction and gene selection | ![]() | ![]() |
How to deploy your own html and containerized report using GitHub Actions
:zero: Choose a name for your package. Recommended convention: {hackathon_event}.{theme}.{method/topic}. e.g. BIRSBIO2020.scNMTseq.Benchmarking, BIRSBIO2020.scProteomics.LatentDirichlet. Ensure that you also have a Docker account for automatic containerization as well.
:one: Use https://github.com/seandavi/BuildABiocWorkshop2020 as template for your analysis package. You can simply click here to accomplish this. Make it public and include all branches (to keep master & gh-pages, you can delete the rest).
:exclamation: For python notebooks also see https://github.com/fastai/fastpages
:two: Follow the steps outlined here to set up your own workflow and create a package from your analyses. The notebooks should go in ./vignettes folder and source files in ./R (or simply include them in notebooks). Include all dependencies in DESCRIPTION and ensure it can be installed, Ensure devtools::build_vignettes() can successfully create the vignettes locally before testing using GitHub Actions.
:bulb: If you use R and have python dependencies, this setup should help as an example.
:bulb: The docker image name should only include lowercase letters, integers, _ and -.
:bulb: Follow this article to add Docker credentials to GitHub Secrets.
:three: Push and ensure the workflow deploys successfully using GitHub Actions (https://github.com/YOUR_GITHUB_USER/REPO/actions)
:four: Add the relevant links and details to the table above through a pull request
:five: Please update these steps through a PR if required
Multi-block PLS

