Data for Tutorial 4 of Ocelli, available at https://ocelli.readthedocs.io. Includes processed data from the Gene Expression Omnibus under accession numbers GSE132188 [1] and GSE115943 [2]. [1] Bastidas-Ponce A, Tritschler S, Dony L, Scheibner K et al. Comprehensive single cell mRNA profiling reveals a detailed roadmap for pancreatic endocrinogenesis. Development 2019 Jun 17;146(12). [2] Schiebinger G, Shu J, Tabaka M, Cleary B et al. Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming. Cell 2019 Feb 7;176(4):928-943.e22.

ObjectiveOsteosarcoma (OS) is a common bone malignancy with poor prognosis. We aimed to investigate the relationship between cuproptosis-related lncRNAs (CRLncs) and the survival outcomes of patients with OS.MethodsTranscriptome and clinical data of 86 patients with OS were downloaded from The Cancer Genome Atlas (TCGA). The GSE16088 dataset was downloaded from the Gene Expression Omnibus (GEO) database. The 10 cuproptosis-related genes (CRGs) were obtained from a recently published article on cuproptosis in Science. Combined analysis of OS transcriptome data and the GSE16088 dataset identified differentially expressed CRGs related to OS. Next, pathway enrichment analysis was performed. Co-expression analysis obtained CRLncs related to OS. Univariate COX regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used to construct the risk prognostic model of CRLncs. The samples were divided evenly into training and test groups to verify the accuracy of the model. Risk curve, survival, receiver operating characteristic (ROC) curve, and independent prognostic analyses were performed. Next, principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) analysis were performed. Single-sample gene set enrichment analysis (ssGSEA) was used to explore the correlation between the risk prognostic models and OS immune microenvironment. Drug sensitivity analysis identified drugs with potential efficacy in OS. Real-time quantitative PCR, Western blotting, and immunohistochemistry analyses verified the expression of CRGs in OS. Real-time quantitative PCR was used to verify the expression of CRLncs in OS.ResultsSix CRLncs that can guide OS prognosis and immune microenvironment were obtained, including three high-risk CRLncs (AL645608.6, AL591767.1, and UNC5B-AS1) and three low-risk CRLncs (CARD8-AS1, AC098487.1, and AC005041.3). Immune cells such as B cells, macrophages, T-helper type 2 (Th2) cells, regulatory T cells (Treg), and immune functions such as APC co-inhibition, checkpoint, and T-cell co-inhibition were significantly downregulated in high-risk groups. In addition, we obtained four drugs with potential efficacy for OS: AUY922, bortezomib, lenalidomide, and Z.LLNle.CHO. The expression of LIPT1, DLAT, and FDX1 at both mRNA and protein levels was significantly elevated in OS cell lines compared with normal osteoblast hFOB1.19. The mRNA expression level of AL591767.1 was decreased in OS, and that of AL645608.6, CARD8-AS1, AC005041.3, AC098487.1, and UNC5B-AS1 was upregulated in OS.ConclusionCRLncs that can guide OS prognosis and the immune microenvironment and drugs that may have a potential curative effect on OS obtained in this study provide a theoretical basis for OS survival research and clinical decision-making.

Data for Tutorial 6 of Ocelli, available at https://ocelli.readthedocs.io. Includes processed data from the Gene Expression Omnibus under accession number GSE212588 [1].[1] Stuart, Tim, et al. "Nanobody-tethered transposition enables multifactorial chromatin profiling at single-cell resolution." Nature biotechnology 41.6 (2023): 806-812.

Data for Tutorials 4-5 of Ocelli, available at https://ocelli.readthedocs.io. Includes processed data from the Gene Expression Omnibus under accession number GSE156478 [1].[1] Mimitou EP, Lareau CA, Chen KY, Zorzetto-Fernandes AL et al. Scalable, multimodal profiling of chromatin accessibility, gene expression and protein levels in single cells. Nat Biotechnol 2021 Oct;39(10):1246-1258.

Data for Tutorials 2-3 of Ocelli, available at https://ocelli.readthedocs.io. Includes processed data from the Gene Expression Omnibus under accession number GSE140203 [1].[1] Ma S, Zhang B, LaFave LM, Earl AS et al. Chromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin. Cell 2020 Nov 12;183(4):1103-1116.e20.

Data for Tutorial 3 of Ocelli, available at https://ocelli.readthedocs.io. Includes processed data from the Gene Expression Omnibus under accession number GSE156478 [1]. [1] Mimitou EP, Lareau CA, Chen KY, Zorzetto-Fernandes AL et al. Scalable, multimodal profiling of chromatin accessibility, gene expression and protein levels in single cells. Nat Biotechnol 2021 Oct;39(10):1246-1258.