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PMC:7417788 / 73296-74109 JSONTXT

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LitCovid-PMC-OGER-BB

Id Subject Object Predicate Lexical cue
T1507 122-133 NCBITaxon:1 denotes individuals

LitCovid-PD-FMA-UBERON

Id Subject Object Predicate Lexical cue fma_id
T541 107-112 Body_part denotes cells http://purl.org/sig/ont/fma/fma68646
T542 143-147 Body_part denotes cell http://purl.org/sig/ont/fma/fma68646
T543 221-224 Body_part denotes NKs http://purl.org/sig/ont/fma/fma63147
T544 298-301 Body_part denotes NKs http://purl.org/sig/ont/fma/fma63147
T545 525-530 Body_part denotes cells http://purl.org/sig/ont/fma/fma68646
T546 560-565 Body_part denotes cells http://purl.org/sig/ont/fma/fma68646

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T141 637-640 Disease denotes SNE http://purl.obolibrary.org/obo/MONDO_0018859

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T1186 107-112 http://purl.obolibrary.org/obo/GO_0005623 denotes cells
T1187 143-152 http://purl.obolibrary.org/obo/CL_0000000 denotes cell type
T1188 209-212 http://purl.obolibrary.org/obo/CLO_0050938 denotes TCs
T1189 209-212 http://purl.obolibrary.org/obo/CL_0000084 denotes TCs
T1190 221-224 http://purl.obolibrary.org/obo/CL_0000623 denotes NKs
T1191 233-236 http://purl.obolibrary.org/obo/CL_0000236 denotes BCs
T1192 245-248 http://purl.obolibrary.org/obo/CL_0000576 denotes MCs
T1193 259-262 http://purl.obolibrary.org/obo/CL_0000451 denotes DCs
T1194 286-289 http://purl.obolibrary.org/obo/CLO_0050938 denotes TCs
T1195 286-289 http://purl.obolibrary.org/obo/CL_0000084 denotes TCs
T1196 298-301 http://purl.obolibrary.org/obo/CL_0000623 denotes NKs
T1197 310-313 http://purl.obolibrary.org/obo/CL_0000236 denotes BCs
T1198 322-325 http://purl.obolibrary.org/obo/CL_0000576 denotes MCs
T1199 336-339 http://purl.obolibrary.org/obo/CL_0000451 denotes DCs
T1200 525-530 http://purl.obolibrary.org/obo/GO_0005623 denotes cells
T1201 560-565 http://purl.obolibrary.org/obo/GO_0005623 denotes cells
T1202 679-680 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T411 0-41 Sentence denotes Mass cytometry visualizing and clustering
T412 42-153 Sentence denotes We created mass cytometry datasets for analysis by concatenating cells from all individuals for each cell type.
T413 154-365 Sentence denotes In this way, we created downsampled datasets of 95,316 TCs, 35,254 NKs, 22,042 BCs, 39,144 MCs and 8,244 DCs in cohort-1 and 57,910 TCs, 34,857 NKs, 13,812 BCs, 45,431 MCs and 7,990 DCs in cohort-2 for analysis.
T414 366-396 Sentence denotes We used FlowCore (65 flowCore:
T415 397-491 Sentence denotes Basic structures for flow cytometry data.) to read and process FCS files for further analysis.
T416 492-614 Sentence denotes For sample with more than 20,000 cells, we randomly selected 20,000 cells to ensure that samples were equally represented.
T417 615-813 Sentence denotes At last, we run the t-SNE dimensionality reduction algorithm on a combined data sample using the Seurat package based on harmony embedding (https://github.com/immunogenomics/harmony, version 1.0.0).

LitCovid-PubTator

Id Subject Object Predicate Lexical cue
1499 712-718 Chemical denotes Seurat