We are analyzing https://link.springer.com/article/10.1186/s13059-017-1349-1.

Title:
xCell: digitally portraying the tissue cellular heterogeneity landscape | Genome Biology
Description:
Tissues are complex milieus consisting of numerous cell types. Several recent methods have attempted to enumerate cell subsets from transcriptomes. However, the available methods have used limited sources for training and give only a partial portrayal of the full cellular landscape. Here we present xCell, a novel gene signature-based method, and use it to infer 64 immune and stromal cell types. We harmonized 1822 pure human cell type transcriptomes from various sources and employed a curve fitting approach for linear comparison of cell types and introduced a novel spillover compensation technique for separating them. Using extensive in silico analyses and comparison to cytometry immunophenotyping, we show that xCell outperforms other methods. xCell is available at http://xCell.ucsf.edu/ .
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Keywords {🔍}

cell, types, type, data, scores, gene, samples, expression, cells, signatures, xcell, additional, file, pubmed, article, methods, tumor, mixtures, cancer, enrichment, google, scholar, sources, microenvironment, genes, method, spillover, matrix, score, analysis, mixture, generated, cas, source, profiles, figure, immune, cytometry, fig, human, set, related, simulated, central, analyses, tumors, performed, signature, cellular, compensation,

Topics {✒️}

org/immport-open/public/study/study/displaystudydetail/sdy311 org/immport-open/public/study/study/displaystudydetail/sdy420 }_{ij}=\raisebox{1ex}{$\left high-throughput genomic profiling systematic pan-cancer analysis article download pdf cross-platform transcriptome measurements single-cell rna-seq }_{ij}-\min \left gov/geo/query/acc gene expression profiling visualizing high-dimensional data single-cell rna-sequencing microarray-based datasets separately expressing immune-specific genes cell type-specific scores cell-type enrichment analysis van allen em microarray-based data sources microarray-based spillover matrix individual cell types sequencing-based data sources unlike signature-based methods article aran sequencing-based spillover matrix robust multi-array average toil enables reproducible privacy choices/manage cookies cell type-adjusted scores immune-specific genes identified sequencing-based data sets flow cytometry counts gene signature-based methods mabbott na gene signature-based method full cellular landscape average single-sample gsea simulated expression profile tissue expression profiles median expression profile full cellular heterogeneity flow cytometry analyses gene expression profiles flow cytometry parameters raisebox{-1ex}{$\left dvir aran creative commons license rna-seq data activation states previously published signatures

Questions {❓}

Tackling the cancer stem cells--what challenges do they pose?

Schema {🗺️}

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         description:Tissues are complex milieus consisting of numerous cell types. Several recent methods have attempted to enumerate cell subsets from transcriptomes. However, the available methods have used limited sources for training and give only a partial portrayal of the full cellular landscape. Here we present xCell, a novel gene signature-based method, and use it to infer 64 immune and stromal cell types. We harmonized 1822 pure human cell type transcriptomes from various sources and employed a curve fitting approach for linear comparison of cell types and introduced a novel spillover compensation technique for separating them. Using extensive in silico analyses and comparison to cytometry immunophenotyping, we show that xCell outperforms other methods. xCell is available at http://xCell.ucsf.edu/ .
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      headline:xCell: digitally portraying the tissue cellular heterogeneity landscape
      description:Tissues are complex milieus consisting of numerous cell types. Several recent methods have attempted to enumerate cell subsets from transcriptomes. However, the available methods have used limited sources for training and give only a partial portrayal of the full cellular landscape. Here we present xCell, a novel gene signature-based method, and use it to infer 64 immune and stromal cell types. We harmonized 1822 pure human cell type transcriptomes from various sources and employed a curve fitting approach for linear comparison of cell types and introduced a novel spillover compensation technique for separating them. Using extensive in silico analyses and comparison to cytometry immunophenotyping, we show that xCell outperforms other methods. xCell is available at http://xCell.ucsf.edu/ .
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         Spillover Matrix
         Cell Type Enrichment
         Cancer Cell Line Encyclopedia (CCLE)
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         Plant Genetics and Genomics
         Microbial Genetics and Genomics
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