ALTRA-manuscript

This repository contains Jupyter notebooks and scripts for the ALTRA manuscript data analysis and figures

DATA APP

This is an in-house develpoed application for exploration of ALTRA data with interactive visualizations https://apps.allenimmunology.org/aifi/insights/ra-progression/analysis/

Notebooks Overview

Analysis Folder

• Flow_Cytometry
• Data cleaning, pre-processing ,Object creation and downstream analysis for Flow Cytometry data
• Intercellular_Bcell_Analysis
• Initial B cell data processing Metaclustering, isotype labeling and cleaning of processed B cell cytometry data
• OLINK_analysis
• Data cleaning, pre-processing and clustering analysis for Proteomics/OLINK data
• TEA-Seq_analysis
• Data cleaning, pre-processing ,Object creation and downstream analysis including MOFA and ATAC seq for TEA-Seq data
• scRNA
• Data cleaning, pre-processing ,Object creation and downstream analysis including Differential Abundance/Frequency , NMF analysis, Spectra analysis,Tfh17 validation analysis for scRNA data
• NMF Analysis set up : https://github.com/yyoshiaki/NMFprojection/

Figures Folder

Figure1

• Figure1/Fig_S3E.ipynb
• Frequency changes in CM CD4 T cells and Core CD14 Monocytes between CON1/HC1 and ARI
• Figure1/Figure_1B.ipynb
• Autoantibody levels across disease status
• Figure1/Figure_1E.ipynb
• Plasma concentration across protein cluster (C1 and C6)
• Figure1/Figure_1F.ipynb
• Differentially Expressed Genes between CON1/HC1 and ARI
• Figure1/Figure_S1B.ipynb
• Timepoints of longitunidal RA Converters to clinically significant RA
• Figure1/Figure_S1C.ipynb
• RF levels across the groups
• Figure1/Figure_S2E.ipynb
• Distribution of disease status across the OLINK clusters
• Figure1/Figure_S3_A_B_C.ipynb
• Celltype labelled single cell level UMPAs
• Figure1/Figure_S3D.ipynb
• Frequency changes overtime between CON1/HC1 and ARI
• Figure1/Figure_S1D.ipynb
• OLINK: Differentially Aboundant Proteins (DAPs) in CON1/HC1 and ARI at baseline
• Figure1/Figure_1CD_S2DEF.ipynb
• OLINK: Clustering for disease status
• Figure1/Figure_S1E.ipynb
• OLINK: Pathway Enrichment results for ARI and CON1/HC1 at baseline
• Figure1/Figure_S1F.ipynb
• OLINK: Ethinicity comparion for ARI and CON1/HC1 at baseline
• Figure1/Figure_S2ABC.ipynb
• OLINK: Baseline cross-sectional comparison for ARI,CON1/HC1/ERA/RA Converters at baseline

Figure2

• Figure2/Figure_2B.ipynb
• Intra donor variablity between CON2/HC2 and ARI
• Figure2/Figure_2C.ipynb
• Frequency changes overtime and corresponding DEG counts in ARI
• Figure2/Figure_2D.ipynb
• DEGs for Longitudinal RA Converters
• Figure2/Figure_2F_S5G.ipynb
• paired Pseudobulk DEG analysis results
• Figure2/Figure_2G.ipynb
• Mean gene expression of key marker genes in Monocytes
• Figure2/Figure_2H.ipynb
• RNA score across Monocytes
• Figure2/Figure_2I.ipynb
• IL1B+ monocyte frequency pre and post conversion in RA converters
• Figure2/Figure_S4ABE.ipynb
• Gene Analysis reuslts using spectra model
• Figure2/Figure_S4CD.ipynb
• DEG analysis between RA converters , ARI and Healthy controls at Baseline
• Figure2/Figure_S5B.ipynb
• Clinical lab data analysis results of ALTRA cohort
• Figure2/Figure_S5_A_C.ipynb
• (i) Autoanibodies levels in RA Converters
• (ii) Longitudinal time points for CON2/HC2 subjects
• Figure2/Figure_S5_D_E.ipynb
• Flow cytometery :T cell clustering
• Figure2/Figure_S5_F.ipynb
• Flow cytometery : Frequency changes in CM/EM CD4 Tcells and Naive CD4 T cells
• Figure2/Figure_S5_H.ipynb
• DEGs in Monocytes

Figure3

• Figure3/Figure_3AB_S6C.ipynb
• DEGs in Effector B cells
• Key Isotype expression in Effector B cells
• Figure3/Figure_3C.ipynb
• Proportion of Isotypes in Effector B cells
• Figure3/Figure_3DG_S6FL.ipynb
• B cells gene expression and pathway analysis plots
• Figure3/Figure_3E.ipynb
• GLT for Core Naive B cells
• Figure3/Figure_3F_S6J.ipynb
• Flow Cytometry: Frequency changes in longitunal RA converters in Naive B cells
• Figure3/Figure_S6A_E.ipynb
• Frequency changes in longitunal RA converters in Naive B cells
• Figure3/Figure_S6F.ipynb
• IGHM RNA expression HC1 vs ARI
• Figure3/Figure_S6_G.ipynb
• Expession of Isotypes across B cells
• Figure3/Figure_S6_H.ipynb
• Key marker gene expression across B cells
• Figure3/Figure_S6_I.ipynb
• IGHG GLT Expression
• Figure3/Figure_S6K.ipynb
• Flow cytometry: B cell Clustering
• Figure3/Figure_S6L.ipynb
• PAX5 RNA expression HC1 vs ARI

Figure3_IC

• Figure_3_IC/IC_flow_bcell_data_analysis.R(Figure_3I)
• Intracellular flow cytometry: Percentage cytokine-positive cells among naive B cells of ARI and HC2/CON2

Figure4

• Figure4/Figure_4A.ipynb
• DEGs for CM CD4 T cells
• Figure4/Figure_4B.ipynb
• Gene module score plot for CM CD4 T cells
• Figure4/Figure_4C_S7E.ipynb
• Frequnecy for Non-naive CD4 T cells
• Figure4/Figure_4E.ipynb
• Tfh/Tph gene score across clusters
• Figure4/Figure_4H.ipynb
• DEGs for Non-naive CD4 T cells at single cell level
• Figure4/Figure_4_DFG_S7CD_S8AB.ipynb
• Non-Naive CD4 T cells Plots- NMF projection
• Figure4/Figure_S7A.ipynb
• Key gene expression in RA longitudinal converters
• Figure4/Figure_S7F1.ipynb
• Frequency changes in RA lognitudinal Converters in Memory CD4 T cells
• Figure4/Figure_S7F2.ipynb
• Frequency changes in RA lognitudinal Converters in Total CD4 T cells
• Figure4/Figure_S8CDEFG.ipynb
• Tfh17 signature in TEA-Seq data
• Figure4/Figure_S8H.ipynb
• Mean gene expression of DEGs in Non-naive CD4 T cells
• Figure4/Figure_S9BCD.ipynb
• Flow Cytometry : tfh17 clustering
• Figure4/Figure_S10AC.ipynb
• Ligand-receptor interactions from CD4mem to Beff cells
• Figure4/Figure_S10B.ipynb
• CD4mem Ligand Gene expression
• Figure4/Figure_S10D.ipynb
• Beff cells Ligand Gene expression

Figure5

• Figure5/Figure_5BCDE.ipynb
• TEA-Seq: MOFA model results for CD4 Naive T cells
• Figure5/Figure_5F.ipynb
• DEGs in CD4 Naive T cells
• Figure5/Figure_5G.ipynb
• Gene module score plot for CD4 Naive T cells
• Figure5/Figure_5H_S11H.ipynb
• GSEA plots for CD4 and CD8 T cells
• Figure5/Figure_S11_FG.ipynb
• Frequency for Core naive CD4 Tcells based on key DEGs
• Figure5/Figure_S11D.ipynb
• DEGs CD8 Naive T cells
• Figure5/Figure_S11E.ipynb
• Gene module score plot for CD8 Naive T cells

Figure6_S12

• Figure6_S12/Figure_6ADE_S12C.ipynb
• TEA-Seq : ATAC analysis figures for CD4 T cells
• Figure6_S12/Figure_6B_S12A.ipynb
• TEA-Seq : Frequency of CD4 T cells Clusters
• Figure6_S12/Figure_6C_S12B.ipynb
• Multiomic analysis figures for CD4 T cells in Muon
• Figure6_S12/Figure_6F_CD4na_DAPs.ipynb
• ATAC: Differentially Accessable Peaks in CD4 Naive T cells

Figure7_S13_Treatment_effect

• Figure7_S13_Treatment_effect/Figure_7BDG_ABT_treatment.ipynb
• Abatacept responders and Non-responders analysis plots
• Figure7_S13_Treatment_effect/Figure_7CE_TNFi_Treatment.ipynb
• Abatacept TNFi treatment plots
• Figure7_S13_Treatment_effect/Figure_7F
• NABP1 expression in ABT responders
• Figure7_S13_Treatment_effect/Figure_7H.ipynb
• Gene signature validation for Abatacept treatment
• Figure7_S13_Treatment_effect/Figure_S13_AB.ipynb
• DEGs in Abatacept Responders and Non-responders

FigureS15

• FigureS15/FigS15_A_B_C.ipynb
• Celltype score plot
• FigureS15/FigS15_D.ipynb
• Batch 182 effect in major celltypes

Usage

Clone the repository and run the notebooks in order. See yaml files under Environment folder for dependencies.

For questions, contact the repository maintainer.