Journal: Nature biotechnology

Article Title: Integrative single-cell analysis of allele-specific copy number alterations and chromatin accessibility in cancer

doi: 10.1038/s41587-021-00911-w

Figure Lengend Snippet: (a) Genotype profiles for six example regions for cells in scATAC-seq data. The regions are taken from segmentation of matched whole exome sequencing (WES) data. Each dot represents a cell-specific (ρ^ir,θ^ir) pair. Cells are colored by annotation derived from peak signals25, Tumor: tumor cells, Fibro: fibroblasts, Endo: Endothelial cells]. Density contours are computed for each cell type (tumor, fibroblasts, endothelial) separately and shown by color on the plot. The lower-case letters following the chromosome number in the titles denote the ordered genomic segments. (b) Pipeline for multi-omics analysis integrating allele-specific copy number estimates and chromatin accessibility peak signals on ATAC-seq data. (c) Hierarchical clustering of cells by major haplotype proportion (θ^) allows the separation of tumor cells from normal cells, as well as the differentiation of a subclone within the tumor cells. The marker region on chr4a separating the two tumor subclones is highlighted. (d) Integrated visualization of chr4a major haplotype proportion (θ^ir) and genome-wide peak profile. Left: UMAP projection of the 788 cells in the dataset by their genome-wide peak profile, colored by θ^ir. The cell type annotation (endothelial, fibroblasts, and tumor cells) is labeled in the plot. Middle: UMAP projection of only the 308 tumor cells by their genome-wide peak profile shows two well-separated clusters: peaks1 and peaks2. Right: Density of θ^ir values for the peaks1 and peaks2 subpopulations. (e) Intratumor heterogeneity of SU008 is shaped by a subclonal LOH of chr4a followed by subsequent genome-wide chromatin remodeling leading to three subpopulations: Clone 1 which does not carry the chr4a LOH (peaks cluster 1), Clone 2 carrying the chr4a LOH (peaks cluster 1), and remodeled clone 2 (peaks cluster 2).

Article Snippet: Raw sequencing reads of the SNU601 scATAC-seq sample was de-multiplexed with the 10x Genomics Cell Ranger ATAC Software (v.1.2.0; https://support.10xgenomics.com/single-cell-atac/software/pipelines/latest/algorithms/overview ) and aligned to the GRCh38 reference genome.

Techniques: Sequencing, Derivative Assay, Biomarker Discovery, Marker, Genome Wide, Labeling

Journal: Cell

Article Title: Time-resolved systems immunology reveals a late juncture linked to fatal COVID-19

doi: 10.1016/j.cell.2021.02.018

Figure Lengend Snippet:

Article Snippet: This was determined using the “raw_clonotype_id” of the filtered_contig_annotations.csv output from CellRanger ( https://support.10xgenomics.com/single-cell-vdj/software/pipelines/latest/algorithms/annotation ).

Techniques: Clone Assay, Recombinant, Multiplex Assay, Sequencing, Software

Journal: Immunity

Article Title: Immune landscape of viral- and carcinogen-driven head and neck cancer

doi: 10.1016/j.immuni.2019.11.014

Figure Lengend Snippet: Key Resources Table

Article Snippet: Software and Algorithms CellRanger (version 2.1.0) 10X Genomics https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/what-is-cell-ranger FlowJo version 10 TreeStar https://www.flowjo.com/ R version 3.5.1 (“Feather Spray”) The R Foundation for Statistical Computing https://www.r-project.org/ Seurat Andrew Butler, Paul Hoffman, Peter Smibert, Efthymia Papalexi, Rahul Satija Citation: Butler et al ( Butler et al., 2018 ) Hosted on: https://satijalab.org/seurat/ caret Kuhn, M. Wing, J. Weston, S. Williams, A. Keefer, C. Engelhardt, A. Cooper, T. Mayer, Z. Kenkel, B. R Core Team.

Techniques: Recombinant, Staining, Sequencing, Gene Expression, Software