Multiomic analyses uncover immunological signatures in acute and chronic coronary syndromes
收藏NIAID Data Ecosystem2026-05-01 收录
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https://zenodo.org/record/10815145
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资源简介：
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
创建时间：
2024-04-18
