Last updated: 2023-08-18
Checks: 2 0
Knit directory: gbcd-workflow/analysis/
This reproducible R Markdown analysis was created with workflowr (version 1.7.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | a78ffef | YushaLiu | 2023-08-18 | Add installation instructions |
| html | f0df13d | YushaLiu | 2023-08-18 | Build site. |
| Rmd | a788fb9 | YushaLiu | 2023-08-18 | Update index.Rmd |
| html | 3e5891c | Peter Carbonetto | 2023-08-09 | Small fix to the overview page. |
| Rmd | 8d6197d | Peter Carbonetto | 2023-08-09 | workflowr::wflow_publish("index.Rmd") |
| html | 0e2b9b8 | Peter Carbonetto | 2023-08-09 | Built the overview page. |
| Rmd | 167e536 | Peter Carbonetto | 2023-08-09 | Updated the workflowr config. |
| Rmd | db41a57 | Peter Carbonetto | 2023-08-09 | Ran wflow_start(). |
This repository contains code and data resources to accompany our research paper:
Yusha Liu, Peter Carbonetto, Jason Willwerscheid, Scott A. Oakes, Kay F. Macleod, and Matthew Stephens (2023). Dissecting tumor transcriptional heterogeneity from single-cell RNA-seq data by generalized binary covariance decomposition. bioRxiv doi:10.1101/2023.08.15.553436.
We provide the following resources:
A vignette that shows how to use GBCD to dissect tumor transcriptional heterogeneity through analysis of multi-tumor single-cell RNA-seq (scRNA-seq) data. We illustrate this using a head and neck squamous cell carcinoma (HNSCC) dataset analyzed in our research paper.
The scripts that reproduce the results and figures presented in the research paper.
Implementing GBCD requires installing the R packages ashr (version 2.2-54), ebnm (version 1.0-42) and flashier (version 0.2.50), which were previously developed by our lab. All the analyses in this research paper were performed in R (version 4.1.0).
If you find any material in this repository useful for your work, please cite our research paper.
All source code and software in this repository are made available under the terms of the MIT license.
See here for the source repository. This is what you will find in the repository:
├── analysis
├── code
├── docs
├── hnscc
├── pdac
└── simulations
The analysis contains R Markdown source files for the workflowr website, including a vignette illustrating how to apply GBCD to analyze your own scRNA-seq data from malignant cells collected from multiple patients and/or studies.
The code directory contains the R source code to implement GBCD, using the functions defined in the ebnm and flashier packages previously developed by our lab.
The docs directory contains webpages generated from the R Markdown files in the analysis directory.
The hnscc directory stores the preprocessed HNSCC dataset analyzed in our research paper, and the results and analysis scripts of the HNSCC data to reproduce the relevant figures in the research paper.
The pdac directory stores the results and analysis scripts of the pancreatic cancer adenocarcinoma data to reproduce the relevant figures in the research paper.
The simulations directory stores the results and analysis scripts related to the simulation study to reproduce the relevant figures in the research paper.
Please note that running these scripts may give you results that are slightly different from those presented in the paper (which were generated much earlier), particularly the GBCD results, due to version updates of the model fitting algorithm. However, the conclusions reported in the paper remain unaffected.