Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The . gov means it’s official. Federal government websites often end in . gov or . mil VSports app下载. Before sharing sensitive information, make sure you’re on a federal government site. .

Https

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely V体育官网. .

. 2023 Jan 6;51(D1):D1425-D1431.
doi: 10.1093/nar/gkac959.

TISCH2: expanded datasets and new tools for single-cell transcriptome analyses of the tumor microenvironment

Ya Han  1   2 , Yuting Wang  1   2 , Xin Dong  1   2 , Dongqing Sun  1   2 , Zhaoyang Liu  1   2 , Jiali Yue  1   2 , Haiyun Wang  2 , Taiwen Li  3 , Chenfei Wang  1   2
Affiliations

V体育安卓版 - TISCH2: expanded datasets and new tools for single-cell transcriptome analyses of the tumor microenvironment

V体育安卓版 - Ya Han et al. Nucleic Acids Res. .

"V体育ios版" Abstract

The Tumor Immune Single Cell Hub 2 (TISCH2) is a resource of single-cell RNA-seq (scRNA-seq) data from human and mouse tumors, which enables comprehensive characterization of gene expression in the tumor microenvironment (TME) across multiple cancer types. As an increasing number of datasets are generated in the public domain, in this update, TISCH2 has included 190 tumor scRNA-seq datasets covering 6 million cells in 50 cancer types, with 110 newly collected datasets and almost tripling the number of cells compared with the previous release. Furthermore, TISCH2 includes several new functions that allow users to better utilize the large-scale scRNA-seq datasets. First, in the Dataset module, TISCH2 provides the cell-cell communication results in each dataset, facilitating the analyses of interacted cell types and the discovery of significant ligand-receptor pairs between cell types VSports手机版. TISCH2 also includes the transcription factor analyses for each dataset and visualization of the top enriched transcription factors of each cell type. Second, in the Gene module, TISCH2 adds functions for identifying correlated genes and providing survival information for the input genes. In summary, TISCH2 is a user-friendly, up-to-date and well-maintained data resource for gene expression analyses in the TME. TISCH2 is freely available at http://tisch. comp-genomics. org/. .

PubMed Disclaimer

"VSports注册入口" Figures

Figure 1.
Figure 1.
Comparison of the data in TISCH1 and TISCH2. (A and B) The dataset number comparison between the TISCH1 (blue) and TISCH2 (red) at the tissue level (A) and the treatment strategy level (B).
Figure 2.
Figure 2.
Overview of the current TISCH2 workflow and features. The words marked in red are updated datasets, newly added functions and features. TISCH2 automatically parsed and collected tumor scRNA-seq datasets from GEO or ArrayExpress databases. All datasets were then uniormly processed with a standardized workflow, including quality control, batch effect removal, cell clustering, differential expression analysis and cell type annotation at multiple levels. TISCH2 displays datasets with relevant study information, including species, treatment, the number of patients and cells, technology platform and the original study. In the Dataset module, TISCH2 provides cell type annotation visualization, multiple gene expression visualization, DEGs, functional enrichment analysis for single or multiple datasets, CCI exploration and TF enrichment analysis for cluster levels. In the Gene module, TISCH2 provides single gene expression visualization across multiple datasets and cell types, the clinical effect of the gene by survival analysis and gene–gene correlation visualization. TISCH2 provides a download page for users to access all the above data and analysis results.
Figure 3.
Figure 3.
The novel functions of TISCH2. (A and B) The TF enrichment result of HNSC_GSE103322. (A) The heatmap shows the TF enrichment score from LISA of each cluster. The color indicates the scaled enrichment P-value. (B) The dot plot shows the 50 top ranked enriched TFs of cluster 18, which is a subset of Mono/Macro. The color of the circles represents the average expression level of corresponding genes. The names of the top 10 TFs are labeled on the graph. (C and D) The overview of the cell communication result of HNSC_GSE103322. The heatmap displays the number of interactions between any two clusters, and the circus plot exhibits detailed interaction probability for cluster 18 with other clusters. (E) The significant communicated ligand–receptor pairs for the source and target cluster is shown as a bubble plot. (F) The lollipop plot represents the hazard ratio of SPI1. The HR equals 1 as an intercept point, a HR >1 means an increased risk and HR <1 suggests decreased risk. The color represents the significance, where red and blue are significant and light red and light blue are non-significant. (G) A real-time updated heatmap showing the gene–gene correlations of SPI1 across cancer type datasets. Users can select the different cell lineage levels to explore the gene–gene correlation in detail. The title of the heatmap is consistent with the selected gene and cell lineage.
See this image and copyright information in PMC

References

    1. Rozenblatt-Rosen O., Regev A., Oberdoerffer P., Nawy T., Hupalowska A., Rood J.E., Ashenberg O., Cerami E., Coffey R.J., Demir E.et al. .. The human tumor atlas network: charting tumor transitions across space and time at single-cell resolution. Cell. 2020; 181:236–249. - PMC - PubMed
    1. Zhang Q., He Y., Luo N., Patel S.J., Han Y., Gao R., Modak M., Carotta S., Haslinger C., Kind D.et al. .. Landscape and dynamics of single immune cells in hepatocellular carcinoma. Cell. 2019; 179:829–845. - PubMed
    1. Chen B., Scurrah C.R., McKinley E.T., Simmons A.J., Ramirez-Solano M.A., Zhu X., Markham N.O., Heiser C.N., Vega P.N., Rolong A.et al. .. Differential pre-malignant programs and microenvironment chart distinct paths to malignancy in human colorectal polyps. Cell. 2021; 184:6262–6280. - PMC - PubMed
    1. Pardoll D.M. The blockade of immune checkpoints in cancer immunotherapy. Nat. Rev. Cancer. 2012; 12:252–264. - PMC (VSports手机版) - PubMed
    1. Martin J.C., Chang C., Boschetti G., Ungaro R., Giri M., Grout J.A., Gettler K., Chuang L.S., Nayar S., Greenstein A.J.et (V体育ios版) al. .. Single-cell analysis of Crohn's disease lesions identifies a pathogenic cellular module associated with resistance to anti-TNF therapy. Cell. 2019; 178:1493–1508. - PMC - PubMed

Publication types