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06-xCell: A R package and web-to

06-xCell: A R package and web-to

作者: 六六_ryx | 来源:发表于2018-05-24 05:54 被阅读47次

    Overview

    • xCell is a webtool and a R package that performs cell type enrichment analysis from gene expression data for 64 immune and stroma cell types.
    • xCell is also a gene signatures-based method containing thousands of pure cell types from 6 various sources.
    • xCell applies a novel technique for reducing associations between closley related cell types.
    • xCell signatures were validated using extensive in-silico simulations and also cytometry immunophenotyping, and were shown to outperform previous methods.
    • xCell allows researchers to reliably portray the cellular heterogeneity landscape of tissue expression profiles.

    Data sources:
    The signature gene expression profiles based on RNA-sequencing and array from six sources:

    • the FANTOM5 project;
    • the ENCODE project;
    • the Blueprint project;
    • the IRIS project;
    • the Novershtern et al. study;
    • the Human Primary Cells Atlas (HPCA)
    gene signatue data sources

    Cell types:
    The gene signature have 64 cell types including Lymphoids sub-types, stem sub-types, myeloids sub-types, stromal cell sub-types and other cells.

    cell types

    pipeline of using xCell

    xCell provide webtools only required human gene expression data file in tab delimited text format or csv (up to 1Gb), which should be genes in rows and samples in columns. The rownames should be gene symbols, and normalizing to gene length (RPKM/FPKM/TPM/RSEM) is required.

    • prepare the expression data
      the expression data format like this :rownames are gene symbols, column names are the samples name, the expression value are nornalized such as RPKM/FPKM/TPM , all the fields are in tab delimited.
        GSM565269   GSM565270   GSM565271 ...
    A1CF    5.9528  6.2118  6.0946
    A2M 5.4145  5.4929  5.296
    A4GALT  6.0914  5.7378  6.051
    A4GNT   6.1141  6.0271  6.0217
    AAAS    8.1466  7.8885  8.0305
    AACS    6.703   6.4519  6.8497
    ...
    

    Based on webtools

    • Open http://xcell.ucsf.edu/ ;
    • upload gene expression data ;
    • write email address ;
    • click run
    • download results from email link when the task finished.
    workflow

    Based on R package

    source("https://bioconductor.org/biocLite.R")
    biocLite("GSVA")
    biocLite("GSEABase")
    devtools::install_github('dviraran/xCell')
    library(xCell)
    
    • Run xCell
    exprMatrix = read.table(expr_file,header=TRUE,row.names=1, as.is=TRUE)
    xCellAnalysis(exprMatrix)
    

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