Multiomic analyses uncover immunological signatures in acute and chronic coronary syndromes

The uploaded data contains the following files for the coronary syndrome (CS) dataset:

1)     Sample Meta Data Information

a.      Merged_Sample_Data.csv: contains meta-information about the samples (age, gender, clinical data, sc-data library)

o   ‘sample_id’: identifier of sample (concatenation of subject-id and timepoint)

o   ‘Subject’: identifier of a subject

o   ‘measurement’: specifies the timepoint of measurement (TP0 – TP4)

o   ‘library’: specifies the single-cell library in which the scRNA-seq data of the sample was prepared

o   ‘sequence’: specifies the sequence of the hashtag for the demultiplexing

o   ‘hashtag’: HTO hashtag used for the demultiplexing of the scRNA-seq data

o   ‘sc_rna_seq_data’: specifies whether scRNA-seq data for this sample is available

o   ‘age’: age of the subject

o   ‘sex’: gender of the subject

o   ‘classification’: clinical classification of the subject, either:

§  ‘acs_subacute’ = ‘acs_with delayed recanalization after vessel occlusion’

§   ‘acs_w_infection’ = ‘acs acquiring hospital infection’

§  ‘acs_w_o_infection’ = ‘sterile acs’

§  ‘ccs’ =’coronary vessel disease’

§  ‘koronarsklerose’ = ‘coronary sclerosis’

§  ‘vollstaendiger_ausschluss’ = ‘healthy coronaries’

o   ‘group’: clinical classification of the subject (parent categories: ‘ccs’, ‘no_ccs’, ‘acs’ of ‘classification’)

o   ‘delta_ef_value_group: classification of the subject based on the ef value

o   ‘delta_ef_value’: delta ef (ejection fraction) value of the subject

o   ‘delta_ef_value_class’: classification of the subject in ‘good’ , ‘intermediate’ or ‘bad’ outcome based on the ef value

o   ‘CK’: measured CK value of the subject

o   ‘CK_MB’: measured CK_MB value of the subject

o   ‘Troponin’: measured Troponin value of the subject

o   ‘CRP’: measured CRP value of the subject

2)     Single-Cell Data:

a.      For each library (XX ; libraries 01-14) the count output of cellranger including barcodes and features:

-        L00XX_matrix.mtx

-        L00XX_features.csv

-        L00XX_barcodes.tsv

b.      Prepared_sc_Data.h5ad: preprocessed scRNA-seq data after QC used as input for the MOFA model, contains normalized, log transformed and scaled values for highly variable genes and raw counts on all genes (= input for MOFA model).

Annotation of cells (.obs) includes:

o   ‘sample_id’: identifier of sample (concatenation of subject-id and timepoint)

o   ‘Subject’: identifier of a subject

o   ‘B2_Scanorama_Singlet_rb_mt_cluster’: cell-type cluster resulting from the clustering based on the Scanorama embedding (as shown in UMAP in manuscript)

o   ‘cluster_cell_type_Scanorama’: cell type clusters including annotations (as shown in UMAP in manuscript)

o   ‘cell_type_Scanorama’: higher level annotation of cell-types

o   ‘library’: sequencing library the cell was included in (L1-L14)

o   ‘in_sample’: dummy column (used in the pseudobulk aggregation)

o   ‘classification’: clinical classification of the sample (see: Sample Meta Data information)

3)     Other Omic Data

a.      Prepared_Neutrophil_Data.csv: contains the neutrophil counts that were used as input for the MOFA model and further downstream analysis

o   ‘sample_id’: identifier of sample (concatenation of subject-id and timepoint)

o   Gene columns (‘ENSG…’): specifies the gene that was measured

b.      Prepared_Cytokine_Data.csv: contains the cytokine measurements that were used as input for the MOFA model and further downstream analysis

o   ‘sample_id’: identifier of sample (concatenation of subject-id and timepoint)

o   ‘Cytokine columns’: each column specifies the name of the cytokine that was measured

c.      Prepared_Proteomic_Data.csv: contains the proteomic measurements that were used as input for the MOFA model and further downstream analysis

o   ‘sample_id’: identifier of sample (concatenation of subject-id and timepoint)

o   ‘Proteomic columns’ each column specifies the name of the protein that was measured

4)     Cell-Type Annotations

a.      Cell_Type_Annotation.csv: includes Scanorama based manual annotation and Azimuth based automatic annotation of cells

o   ‘sample_id’: identifier of sample (concatenation of subject-id and timepoint)

o   ‘cell_library’: barcode and library of the cell

o   ‘B2_Scanorama_Singlet_rb_mt_cluster’:: cell-type cluster resulting from the clustering based on the Scanorama embedding (as shown in UMAP in manuscript)

o   ‘cluster_cell_type_Scanorama’: cell type clusters including annotations (as shown in UMAP in manuscript)

o   ‘cell_type_Scanorama’: higher level annotation of cell-types

o   ‘library’: sequencing library the cell was included in (L1-L14)

o   ‘predicted.celltype.l2’ : azimuth based cell-type prediction

o   ‘predicted.celltype.l2.score’: score of the the azimuth cell-type prediction

b.      ‘Cell_Type_Annotation_Levels.csv’: includes a mapping of different levels of cell-types

5)     FACS data:

a.       Prepared_FACS_data.csv: includes cell type percentages of the FACS assay

o   ‘sample_id’: identifier of sample (concatenation of subject-id and timepoint)

o   ‘TP’: specifies the timepoint of measurement (TP0 – TP4)

o   ‘cell_type_facs’: FACS cell-type

o   ‘percentage’: percentage of cells for the cell-type of the sample given as character string

o   ‘percentage_numeric’: percentage of cells for the cell-type of the sample given as numeric value

6)     Grace-Score:

a.      Grace_Score.csv: contains the computed GRACE scores for each sample (used for evaluation of the prediction of the MOFA factors)

o   ‘sample_id’: identifier of sample (concatenation of subject-id and timepoint)

o   Grace_Score: calculated grace-score for the sample (for more details refer to the manuscript)

7)     Pathway Selection:

a.      REACTOME_Immune_System_Pathways.csv: contains all the immune System pathways that were extracted from REACTOME

b.      KEGG_pathways_categorized.csv: contains all the KEGG pathways with their categories

8)     Plot Configuration Files: contain specifications for the violin plots of the manuscript loaded within the scripts to define which genes will be ploted

a.      Plot_Config_Violin.csv: for violin plots included in main figures

b.      Plot_Config_Violin_Supp.csv: for violin plots included in supplementary figures