CITEMO (A flexible single-cell multimodal omics analysis framework to reveal the heterogeneity of immune cells)

• We propose a flexible framework, called CITEMO, to analyze single-cell multimodal omics data.
• This project is a practice of CITEMO, which can inspire other single-cell multi-multi-omics sequencing data analysis. CITEMO_CBMC.ipynb shows an example of using CITEMO to analyze CBMC multimodal omics samples. All data involved in this project are stored in the Data folder.
• It is strongly recommended to install the specified version of the python package as shown in Requirement.
• It is worth noting that running CITEMO_CBMC.ipynb in different environments may get different results. You should combine biological experience and try to constantly adjust the model parameters to obtain the best results.

Requirement

• Python >= 3.8.0
• jupyterlab >= 3.0.9
• numpy == 1.19.5
• ray == 1.1.0
• matplotlib == 3.3.4
• seaborn == 0.11.1
• scipy == 1.6.1
• scikit-learn == 0.24.1
• statsmodels == 0.12.2
• pandas == 1.2.3
• pillow == 8.1.2
• jedi == 0.18.0
• umap-learn == 0.5.1
• phenograph == 1.5.7
• bokeh == 2.3.0

Dataset

• CBMC https://satijalab.org/seurat/archive/v3.2/multimodal_vignette.html
• HBMC https://satijalab.org/seurat/articles/weighted_nearest_neighbor_analysis.html
• PBMC1k https://support.10xgenomics.com/single-cell-gene-expression/datasets/3.0.0/pbmc_1k_protein_v3
• PBMC10k https://support.10xgenomics.com/single-cell-gene-expression/datasets/3.0.0/pbmc_10k_protein_v3
• MALT https://support.10xgenomics.com/single-cell-gene-expression/datasets/3.0.0/malt_10k_protein_v3
• PBMC5k https://support.10xgenomics.com/single-cell-gene-expression/datasets/3.0.2/5k_pbmc_protein_v3