Preprocessing, clustering and QC code for all analysis is in: 0_Preprocessing.ipynb
Figure 5: General clustering and macrophage and cDC subclustering. For iterative clustering code see preprocessing notebook.
A-D: Figure5_all_cell_clustering.ipynb
E-H: Figure5_macrophage_cell_clustering.ipynb
J-M: Figure5_cDC_clustering.ipynb
N-I: Functional_enrichment.ipynb
Figure 6: Figure6_tnk_clustering.ipynb
Figure 7:
A. Differential expression within Cytotoxic NK/T cells between anti-CD8a depleted samples and control: pseudobulk_differential_expression.ipynb
B. Violin plots of lineage genes between groups Figure6_tnk_clustering.ipynb
C. Gene ontology analysis: Tcell_functional_enrichment.ipynb
Figure 8:
Interaction analysis details:
-
Generate pseudobulk counts for clusters of interest
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Generate csv containing percent of cells expressing each gene for each cluster
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Run DESeq2 to get differential expressed genes between conditions then run NicheNet on those lists - Nichenet_pseudobulk_interaction_analysis.ipynb
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Calculate interaction potentials and annotate NicheNET list based on these significant potentials - Figure8_Receptor_Ligand_Interactions.ipynb
A,B: Figure8_Receptor_Ligand_interactions.ipynb
C. Figure8_S10.ipynb
S4: See preprocessing notebook for details
A. 0_Preprocessing.ipynb
B. Figure5_all_cell_and_myeloid_clustering.ipynb
C. 0_Preprocessing.ipynb
D. 0_Preprocessing.ipynb
E. 0_Preprocessing.ipynb
F. Figure6_tnk_clusteing.ipynb
S5: See figure 8 description for interaction analysis details (A-E).
F-G: Figure8_S10.ipynb
Pseudobulk differential expression: pseudobulk_differential_expression.ipynb
Differential abundance: DA_with_edgeR.ipynb