10X cellplex

简介

cellplex，即Cell Multiplexing，即对每个样本的每个cell增加一个label，然后将其与其他的样本混合后通过细胞封装，建库，测序后可以通过这个label区分cell来自于哪个样本

优势：

• 在单个实验中增加样品通量
• 在单个实验中检测的细胞数量增加
• 在单个实验中增加可能的重复次数
• 在分析之前检测多重谱及其去除

分析: cellranger

使用流程为 ：cellranger multi （v.6.0）Loupe6.0.0

https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/using/multi#cmoreference

https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/using/tutorial_cp#data

Loupe: https://support.10xgenomics.com/single-cell-gene-expression/software/downloads/latest#loupe

测试数据

背景: 两种cell line (Jurkat和Raji), 分别被两种CMO标记，混合后测序

https://www.10xgenomics.com/resources/datasets/10-k-1-1-mixture-of-raji-and-jurkat-cells-multiplexed-2-cm-os-3-1-standard-6-0-0

• fastq

https://s3-us-west-2.amazonaws.com/10x.files/samples/cell-exp/6.0.0/SC3_v3_NextGem_DI_CellPlex_Human_PBMC_10K_Multiplex/SC3_v3_NextGem_DI_CellPlex_Human_PBMC_10K_Multiplex_fastqs.tar

• config file

https://cf.10xgenomics.com/samples/cell-exp/6.0.0/SC3_v3_NextGem_DI_CellPlex_Human_PBMC_10K_Multiplex/SC3_v3_NextGem_DI_CellPlex_Human_PBMC_10K_Multiplex_config.csv
https://cf.10xgenomics.com/samples/cell-exp/6.0.0/SC3_v3_NextGem_DI_CellPlex_Human_PBMC_10K_Multiplex/SC3_v3_NextGem_DI_CellPlex_Human_PBMC_10K_Multiplex_count_feature_reference.csv

config file

Multi Config CSV

格式：

具体解释

[gene-expression]部分

• reference (R) ： 参考基因组位置
• except-cells: 期望cell数量
• min-assignment-confidence: 通过计算Cell Multiplexing Oligo(cmo)与目标Cell Multiplexing Oligo 的相似度来过滤数据
• cmo-set：cmo序列文件，具体格式为， （定制cmo时提供）

id,name,read,pattern,sequence,feature_type
CMO301,CMO301,R2,5P(BC),ATGAGGAATTCCTGC,Multiplexing Capture
CMO302,CMO302,R2,5P(BC),CATGCCAATAGAGCG,Multiplexing Capture
CMO303,CMO303,R2,5P(BC),CCGTCGTCCAAGCAT,Multiplexing Capture

• target-panel: Optional. Path to a target panel CSV file or name of a 10x Genomics fixed gene panel (pathway, pan-cancer, immunology, neuroscience).
• no-target-umi-filter： Optional. Disable targeted UMI filtering stage. See Targeted Algorithms for details. Default: false.
• r1/r2-length: Hard trim the input Read 1 / 2of gene expression libraries to this length before analysis
• chemistry: 试剂版本
• force-cells： Force pipeline to use this number of cells, bypassing cell detection.
• include-introns： Include intronic reads in count.
• no-secondary： Disable secondary analysis
• no-bam： Do not generate a bam file

[feature]

• refernrnce: Feature reference CSV file, declaring Feature Barcode constructs and associated barcodes. Required for Feature Barcode libraries, otherwise optional.
• r1 / r2-length: 同上

[libraries]

• fastq_id (R) : fastq文件前缀
• fastqs (R) : fastq文件位置
• lanes: 样品在那个lane上，默认全部
• physical_library_id： 文库类型，会根据指定feature_types自动检测，一般无需指定
• feature_types (R) ：基础文库类型，Gene Expression, Antibody Capture, CRISPR Guide Capture, Multiplexing Capture.
• subsample_rate: 从fastq中抽取的reads数量

[sample]

• smaple_id (R) : A name to identify a multiplexed sample. Must be alphanumeric with hyphens and/or underscores, and less than 64 characters. Required for cell multiplexing libraries.
• cmo_ids (R) : CMO的id， 如果有多种则使用 |分隔
• description: 描述信息

运行命令

cellranger multi --id=sample345 --csv=/home/jdoe/sample345.csv --localcores <int> --localmem <int>

几个例子

• eg1

• eg2

• eg3：

测试

路径

/SGRNJ03/randd/user/liuzihao/work/cellplex/

测试命令

export PATH="$PATH":/SGRNJ03/randd/user/liuzihao/work/cellplex/cellranger-6.1.2
cellranger multi \
     --id=test_cellplex \
     --csv=/SGRNJ03/randd/user/liuzihao/work/cellplex/SC3_v3_NextGem_DI_CellPlex_Human_PBMC_10K_Multiplex_config.csv \
     --localcores 4 \
     --localmem 30

config文件

结果输出

https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/output/cellplex

主要输出文件

四个文件 (multiplexing_analysis/):

assignment_confidence_table: 每个barcode对应的是哪个CMO的概率

cells_per_tag.json: 每个CMO对应的barcode有哪些json格式

tag_calls_per_cell.csv: 每个barcode的CMO的umi数量

tag_calls_summary.csv: 总体情况分析

feathure-barcode(count/)