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Cell Ranger是一个10X genomics公司的单细胞分析软件，将原始的fastq文件生成后续分析的feature-barcode表达矩阵。 其中包括很多模块，本次主要介绍cellranger mkfastq、cellranger count，cellranger aggr 和 cellranger reanalyze四个功能模块。 
1.1 下载
进入cellranger官网（https://support./）后，发现支持的分析模块有很多，先介绍单细胞转录组。选择单细胞转录组模块，点击进入 
软件-下载-选择你想要的cellranger版本， https://support./single-cell-gene-expression/software/downloads/latest 
1）curl ，wget 和 直接网页下载，三种方式均可； 2）记得下载注释文件 3）注意查看md5值（很重要） 1.2 安装Step1：解压下载的软件安装包 #进入文件存放的位置，示例为opt
$ cd /opt
#解压
$ tar -xzvf cellranger-6.0.1.tar.gz解压缩到一个名为cellranger-6.0.1的新目录，包含Cell Ranger及其依赖项和Cell Ranger脚本。 Step2：同样的方式解压参考文件 $ tar -xzvf refdata-gex-GRCh38-2020-A.tar.gzStep3：配置环境 将Cell Ranger目录添加到$PATH中，注意路径要准确，示例为/opt ， $ export PATH=/opt/cellranger-6.0.1:$PATH为使用方便可以添加到.bashrc文件中。 1.3 测试安装可以查看一下版本和帮助，或者参考官网的Site Check Script 的方式。 cellranger -V
cellranger -h下载：https://support./single-cell-gene-expression/software/downloads/latest 安装：https://support./single-cell-gene-expression/software/pipelines/latest/installation cellranger使用mkfastq功能来拆分Illumina 原始数据（raw base call (BCL)），输出 FASTQ 文件。
2.1 下载示例数据点击下载即可 
2.2 Running mkfastq with a Simple CSV Samplesheet1）首先示例矩阵数据解压缩，当前目录下生成cellranger-tiny-bcl-1.2.0文件夹 tar -xvzf cellranger-tiny-bcl-1.2.0.tar.gz2）Simple CSV Samplesheet文件 格式：三列(Lane、Sample、Index)，逗号分隔，不太容易出现格式错误。示例数据cellrangerver -tiny-bcl-simple-1.2.0.csv如下: Lane,Sample,Index
1,test_sample,SI-TT-D9Lane | Which lane(s) of the flowcell to process. Can be either a single lane, a range (e.g., 2-4) or '*' for all lanes in the flowcell. | Sample | The name of the sample. This name is the prefix to all the generated FASTQs, and corresponds to the --sample argument in all downstream 10x pipelines.
Sample names must conform to the Illumina bcl2fastq naming requirements. Only letters, numbers, underscores and hyphens area allowed; no other symbols, including dots (".") are allowed. | Index | The 10x sample index that was used in library construction, e.g., SI-TT-D9 or SI-GA-A1 |
3）run mkfastq 需要安装且配置bcl2fastq软件 $ cellranger mkfastq --id=cellranger-tiny-bcl-1.2.0 \
--run=/path/to/cellranger-tiny-bcl-1.2.0 \
--csv=cellranger-tiny-bcl-simple-1.2.0.csvid ：即为解压后的文件夹名字 run：为解压后的文件夹的绝对路径 在id名的新文件夹中既有生成的fastq文件了，可以用于后续的count分析。 另一种请参考https://support./single-cell-gene-expression/software/pipelines/latest/using/mkfastq 此处使用转录组数据进行count分析，通过fastq文件得到细胞和基因的定量结果。 3.1 必要参数$ cellranger count --id=sample345 \
--transcriptome=/opt/refdata-gex-GRCh38-2020-A \
--fastqs=/home/jdoe/runs/HAWT7ADXX/outs/fastq_path \
--sample=mysample \
--expect-cells=1000 \--id= 名称
--fastqs= fastq.gz文件保存的绝对路径
--sample= fastq.gz文件名"-"之前的字段
--transcriptome= 参考基因组路径 --expect-cells= 期望细胞数（可选） 3.2 参数列表参数详细介绍详见： https://support./single-cell-gene-expression/software/pipelines/latest/using/count#args中的Command-Line Argument Reference 部分 可以注意下以下参数： --expect-cells | (optional) Expected number of recovered cells. Default: 3,000 cells. | 和实验匹配 | --nosecondary | (optional) Add this flag to skip secondary analysis of the feature-barcode matrix (dimensionality reduction, clustering and visualization). Set this if you plan to use cellranger reanalyze or your own custom analysis. | 仅获得表达矩阵，不进行后续的降维，聚类和可视化分析 | --chemistry | (optional) Assay configuration. NOTE: by default the assay configuration is detected automatically, which is the recommended mode. You should only specify chemistry if there is an error in automatic detection. Select one of: |
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3.3 结果文件结果文件列表以及简要描述说明 File Name | Description |
| web_summary.html | Run summary metrics and charts in HTML format | 网页简版报告以及可视化 | metrics_summary.csv | Run summary metrics in CSV format |
| possorted_genome_bam.bam | Reads aligned to the genome and transcriptome annotated with barcode information |
| possorted_genome_bam.bam.bai | Index for possorted_genome_bam.bam |
| filtered_feature_bc_matrix | Filtered feature-barcode matrices containing only cellular barcodes in MEX format. (In Targeted Gene Expression samples, the non-targeted genes are not present.) | 过滤掉的barcode信息 | filtered_feature_bc_matrix_h5.h5 | Filtered feature-barcode matrices containing only cellular barcodes in HDF5 format. (In Targeted Gene Expression samples, the non-targeted genes are not present.) | 过滤掉的barcode信息HDF5 format； | raw_feature_bc_matrices | Unfiltered feature-barcode matrices containing all barcodes in MEX format | 原始barcode信息 | raw_feature_bc_matrix_h5.h5 | Unfiltered feature-barcode matrices containing all barcodes in HDF5 format | 原始barcode信息HDF5 format | analysis | Secondary analysis data including dimensionality reduction, cell clustering, and differential expression |
| molecule_info.h5 | Molecule-level information used by cellranger aggr to aggregate samples into larger datasets |
| cloupe.cloupe | Loupe Browser visualization and analysis file | Loupe Cell Browser 输入文件 | feature_reference.csv | (Feature Barcode only) Feature Reference CSV file |
| target_panel.csv | (Targeted GEX only) Targed panel CSV file |
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参考资料：https://support./single-cell-gene-expression/software/pipelines/latest/using/mkfastq 精心整理（含图PLUS版）|R语言生信分析，可视化（R统计，ggplot2绘图，生信图形可视化汇总）
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