Immunothrombolytic monocyte-neutrophil axes dominate the single-cell landscape of human thrombosis

Original Data for the manuscript:

Immunothrombolytic monocyte-neutrophil axes dominate the single-cell landscape of human thrombosis

The manuscript is accessible in bioRxiv: https://www.biorxiv.org/content/10.1101/2024.01.10.574518v1 . Please cite the preprint and any subsequent journal publications.

Processed scRNA-seq data

seurat_humancombined_libintSubsetGroups.Rds -> fully processed Seurat objects

objGroups_libint_conditions.tsv -> annotations for main Seurat object

integrated_mouse_thrombus.rds -> mouse thrombus dataset

Original Data (scRNA-seq)

pat1_raw_feature_bc_matrix.h5 -> Sample 21053_0001

pat2_raw_feature_bc_matrix.h5 -> Sample 21053_0003

pat3_raw_feature_bc_matrix.h5 -> Sample sample_Thr3

pat4_5_raw_feature_bc_matrix.h5 -> Sample sample_Thr4

pat6_raw_feature_bc_matrix.h5 -> Sample sample_Thr5

pat7_raw_feature_bc_matrix.h5 -> Sample samples_ATTHR

mt_raw_feature_bc_matrix.h5 -> Mouse

Original Data (spliced/unspliced by velocyto; matching above sample names):
pat1_velocyto.loom -> Sample 21053_0001

pat2_velocyto.loom -> Sample 21053_0003

pat3_velocyto.loom -> Sample sample_Thr3

pat4_5_velocyto.loom -> Sample sample_Thr4

pat6_velocyto.loom -> Sample sample_Thr5

pat7_velocyto.loom -> Sample samples_ATTHR

Scripts:
functions.R -> script with helper utilities

mt_process.R -> script for processing the mouse data

process.R -> script for processing the main data set

process_de_obj.R -> script for performing DE analysis

process_label_transfer.R -> script for doing label transfer between human and mouse dataset and further analyses

process_label_transfer.ipynb -> script for doing label transfer between human and mouse dataset and further analyses

process_monocle.R -> script for doing monocle-based analyses

process_wgcna.R -> script for doing wgcna-based analyses

subset_velocities_step1.R -> Seurat to file-based data

subset_velocities_step2.py -> scvelo-based script for processing each subset

velocities_step1.R -> Seurat to file-based data

velocities_step2.py-> scvelo-based script for processing full dataset

revision_velocities_step2.py -> scvelo-based script for processing each subset (now with nice colors)