### single cell data for manuscript: Multiomics approach identifies novel age-, time- and treatment-related immunopathological signatures in MIS-C and pediatric COVID-19 ### Files: 1. misc_SeuratObj_submission.rds -- Seurat object contains all count data used for the manuscript - raw sequencing data are not provided due to privacy issue - metadata is included in the Seurat object 2. MIS-C_cohort_citeseq.xlsx -- sample meta data 3. immcant_bcr_ighl_filtered.csv -- single cell BCR data 4. TCR_filtered_contig_annotations.csv -- single cell TCR data ### SessionInfo for major packages used when creating the Seurat object > sessionInfo() R version 3.6.1 (2019-07-05) Platform: x86_64-conda_cos6-linux-gnu (64-bit) Running under: Red Hat Enterprise Linux Server 7.9 (Maipo) Matrix products: default locale: [1] en_US.UTF-8 attached base packages: [1] parallel stats4 stats graphics grDevices utils datasets methods base other attached packages: [1] openxlsx_4.2.3 RColorBrewer_1.1-2 reshape2_1.4.4 org.Hs.eg.db_3.10.0 [5] AnnotationDbi_1.48.0 IRanges_2.20.2 S4Vectors_0.24.4 Biobase_2.46.0 [9] BiocGenerics_0.32.0 clusterProfiler_3.14.3 viridis_0.5.1 viridisLite_0.3.0 [13] pheatmap_1.0.12 parallelDist_0.2.4 genefilter_1.68.0 forcats_0.5.1 [17] stringr_1.4.0 dplyr_1.0.4 purrr_0.3.4 readr_1.4.0 [21] tidyr_1.1.2 tibble_3.1.0 ggplot2_3.3.3 tidyverse_1.2.1 [25] plyr_1.8.6 matrixStats_0.58.0 Seurat_3.1.0 loaded via a namespace (and not attached): [1] utf8_1.1.4 reticulate_1.18 R.utils_2.9.2 tidyselect_1.1.0 [5] RSQLite_2.2.0 htmlwidgets_1.5.3 grid_3.6.1 BiocParallel_1.20.1 [9] Rtsne_0.15 munsell_0.5.0 codetools_0.2-18 mutoss_0.1-12 [13] ica_1.0-2 future_1.21.0 withr_2.4.1 colorspace_2.0-0 [17] GOSemSim_2.12.1 rstudioapi_0.13 ROCR_1.0-11 DOSE_3.12.0 [21] listenv_0.8.0 Rdpack_2.1.1 labeling_0.4.2 urltools_1.7.3 [25] mnormt_2.0.2 polyclip_1.10-0 bit64_4.0.5 farver_2.1.0 [29] parallelly_1.23.0 vctrs_0.3.6 generics_0.1.0 TH.data_1.0-10 [33] R6_2.5.0 graphlayouts_0.7.1 rsvd_1.0.3 bitops_1.0-6 [37] cachem_1.0.3 fgsea_1.12.0 gridGraphics_0.5-1 assertthat_0.2.1 [41] SDMTools_1.1-221.1 scales_1.1.1 multcomp_1.4-13 ggraph_2.0.0 [45] enrichplot_1.4.0 debugme_1.1.0 gtable_0.3.0 globals_0.14.0 [49] tidygraph_1.1.2 sandwich_3.0-0 rlang_0.4.10 splines_3.6.1 [53] lazyeval_0.2.2 broom_0.7.5 europepmc_0.4 BiocManager_1.30.10 [57] yaml_2.2.0 modelr_0.1.8 backports_1.2.1 qvalue_2.16.0 [61] tools_3.6.1 ggplotify_0.0.5 ellipsis_0.3.1 ggridges_0.5.3 [65] TFisher_0.2.0 Rcpp_1.0.6 progress_1.2.2 RCurl_1.98-1.2 [69] prettyunits_1.1.1 pbapply_1.4-3 cowplot_1.1.1 zoo_1.8-8 [73] haven_2.1.0 ggrepel_0.9.1 cluster_2.1.1 magrittr_2.0.1 [77] data.table_1.14.0 DO.db_2.9 lmtest_0.9-38 triebeard_0.3.0 [81] RANN_2.6.1 tmvnsim_1.0-2 mvtnorm_1.1-1 fitdistrplus_1.1-3 [85] hms_1.0.0 xtable_1.8-4 XML_3.99-0.3 readxl_1.3.1 [89] gridExtra_2.3 compiler_3.6.1 KernSmooth_2.23-18 crayon_1.4.1 [93] R.oo_1.24.0 htmltools_0.5.1.1 RcppParallel_5.0.3 lubridate_1.7.10 [97] DBI_1.1.1 tweenr_1.0.1 MASS_7.3-53.1 Matrix_1.3-2 [101] cli_2.3.1 R.methodsS3_1.8.1 rbibutils_2.0 metap_1.4 [105] igraph_1.2.6 pkgconfig_2.0.3 sn_1.6-2 rvcheck_0.1.8 [109] numDeriv_2016.8-1.1 plotly_4.9.0 xml2_1.3.2 annotate_1.64.0 [113] multtest_2.42.0 rvest_0.3.6 digest_0.6.27 sctransform_0.2.0 [117] RcppAnnoy_0.0.18 tsne_0.1-3 cellranger_1.1.0 leiden_0.3.7 [121] fastmatch_1.1-0 uwot_0.1.8 lifecycle_1.0.0 nlme_3.1-152 [125] jsonlite_1.7.2 fansi_0.4.2 pillar_1.5.0 lattice_0.20-41 [129] fastmap_1.1.0 httr_1.4.2 plotrix_3.8-1 survival_3.2-7 [133] GO.db_3.10.0 glue_1.4.2 zip_2.1.1 UpSetR_1.4.0 [137] png_0.1-7 bit_4.0.4 ggforce_0.3.2 stringi_1.5.3 [141] blob_1.2.1 memoise_2.0.0 mathjaxr_1.4-0 irlba_2.3.3 [145] future.apply_1.6.0 ape_5.4-1