InstaPrism is R package to deconvolute cellular proportion and gene expression in bulk RNA-Seq data. Based on the same conceptual framework and corresponding generative mode from BayesPrism, InstaPrism re-implements BayesPrism in a derandomized framework by replacing the time-consuming Gibbs sampling steps in BayesPrism with a fixed-point algorithm, which greatly accelerated the calculation speed while maintaining highly comparable performance.
library("devtools");
install_github("humengying0907/InstaPrism")
Using either scRNA-based reference (update = F) or updated reference (update = T), InstaPrism achieves identical deconvolution results as BayesPrism.
![](https://private-user-images.githubusercontent.com/54827603/295460026-36c6cfa1-308c-4a0b-adc2-bf4b6399139b.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MTQ4NzM5ODYsIm5iZiI6MTcxNDg3MzY4NiwicGF0aCI6Ii81NDgyNzYwMy8yOTU0NjAwMjYtMzZjNmNmYTEtMzA4Yy00YTBiLWFkYzItYmY0YjYzOTkxMzliLnBuZz9YLUFtei1BbGdvcml0aG09QVdTNC1ITUFDLVNIQTI1NiZYLUFtei1DcmVkZW50aWFsPUFLSUFWQ09EWUxTQTUzUFFLNFpBJTJGMjAyNDA1MDUlMkZ1cy1lYXN0LTElMkZzMyUyRmF3czRfcmVxdWVzdCZYLUFtei1EYXRlPTIwMjQwNTA1VDAxNDgwNlomWC1BbXotRXhwaXJlcz0zMDAmWC1BbXotU2lnbmF0dXJlPWJmNzYyMTZjNDkxNDllYWVkMTIwZmMwOGU2YjczZjM2NWM2ODVjOWMzMjkxYWZiOWQyYWM3OWFmNmMwMDkyNTImWC1BbXotU2lnbmVkSGVhZGVycz1ob3N0JmFjdG9yX2lkPTAma2V5X2lkPTAmcmVwb19pZD0wIn0.SR6iBcEUApwGmidewv5LByf9KmzZ5lvso9rd4E4p938)
Below is a running time comparsion when running deconvolution on the tutorial data provided in BayesPrism.
![](https://private-user-images.githubusercontent.com/54827603/262544571-8e158249-9cc9-4f06-8e89-63867540bfc6.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.3r4Jh1WZq8EzHKDSEtj0mlbWj0wWSWIC201ue23t72Y)
InstaPrism significantly reduced the memory required to store the deconvolution project, when running deconvolution on the tutorial data provided in BayesPrism.
![](https://private-user-images.githubusercontent.com/54827603/269779981-3d9c8b8b-8aac-4c4b-b793-e64c33cac752.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.83aRFFqgZpQt38l63BWUdxbLWi1OH52y2Heui-uh5ZE)
We have provided precompiled reference tailored for a wide range of cancer types. Download the reference from the link below and use the following code to run deconvolution.
# take BRCA_refPhi for example
BRCA_refPhi = readRDS("BRCA_refPhi.RDS")
InstaPrism.res = InstaPrism(input_type = 'refPhi_cs', bulk_Expr = bulk_expr,refPhi_cs = BRCA_refPhi, n.core = 16)
reference name | tumor type | #cells used for reference construction | #cell types/cell states | umap | citation | download |
---|---|---|---|---|---|---|
BRCA_refPhi | breast cancer | 100,064 | 9/76 | UMAP | Wu et al. 2021 | ↓ |
CRC_refPhi | colorectal cancer | 371,223 | 15/149 | UMAP | Pelka et al. 2021 | ↓ |
GBM_refPhi | glioblastoma | 338,564 | 8/55 | cellxgeneLink, UMAP | Ruiz et al. 2022 | ↓ |
LUAD_refPhi | lung adenocarcinomas | 118,293 | 13/74 | UMAP | Xing et al. 2021 | ↓ |
OV_refPhi | ovarian cancer | 929,690 | 9/40 | cellxgeneLink, UMAP | Vazquez et al. 2022 | ↓ |
RCC_refPhi | clear cell renal cell carcinoma | 270,855 | 12/86 | cellxgeneLink, UMAP | Li et al. 2022 | ↓ |
SKCM_refPhi | skin cutaneous melanoma | 4,645 | 8/23 | UMAP | Tirosh et al. 2016 | ↓ |
Check InstaPrism_tumorial for detailed implementation of InstaPrism and compare its performance with BayesPrism.
M. Hu and M. Chikina, “InstaPrism: an R package for fast implementation of BayesPrism.” bioRxiv, p. 2023.03.07.531579, Mar. 12, 2023. doi: https://doi.org/10.1101/2023.03.07.531579