###### tags: `ノート` `TS` `解析` `single-cell RNA-seq` # 22-01： ES由来セルトリ細胞scRNAseq解析　FTSLC_scRNAseq (cellranger aggr) <br> #### 2026/04/06 #### 【 作業場所＆保存場所 】 • rowdata (fastq) /analysisdata/rawseq/fastq/SHARED/000042/E10-5_XX/ :XXのE10.5 /analysisdata/rawseq/fastq/SHARED/000042/E10-5_XY/ :XYのE10.5 /analysisdata/rawseq/fastq/SHARED/000042/E11-5_XX/ :XXのE11.5 /analysisdata/rawseq/fastq/SHARED/000042/E11-5_XY/ :XYのE11.5 /analysisdata/rawseq/fastq/SHARED/000042/E12-5_XX/ :XXのE12.5 /analysisdata/rawseq/fastq/SHARED/000042/E12-5_XY/ :XYのE12.5 Induced_D6/ :XXのESから分化誘導6⽇⽬ (FOSLCs) /analysisdata/rawseq/fastq/SHARED/000128/JN00006966/10x-ig168/ :XYのESから分化誘導6⽇⽬ (FTSLCs) • 作業場所 　~/osc-fs/22_TS_FTSLC_scRNAseq_2022 --- ### 1. CellRangerかける * cell_ranger_job.sh ``` #!/bin/bash #$ -S /bin/bash #$ -cwd #$ -pe smp 4 ## $1 id ## $2 fastq directory cellranger count --id=$1 \ --transcriptome=$HOME/ProgramFiles/Cell_Ranger/refdata-cellranger-mm10-3.0.0 \ --fastqs=$2 \ --expect-cells=8000 \ --localcores=2 ``` キューイング ``` qsub -N XX_E10.5 cell_ranger_job.sh E10-5_XX //analysisdata/rawseq/fastq/SHARED/000042/E10-5_XX qsub -N XY_E10.5 cell_ranger_job.sh E10-5_XY //analysisdata/rawseq/fastq/SHARED/000042/E10-5_XY qsub -N XX_E11.5 cell_ranger_job.sh E11-5_XX //analysisdata/rawseq/fastq/SHARED/000042/E11-5_XX qsub -N XY_E11.5 cell_ranger_job.sh E11-5_XY //analysisdata/rawseq/fastq/SHARED/000042/E11-5_XY qsub -N XX_E12.5 cell_ranger_job.sh E12-5_XX //analysisdata/rawseq/fastq/SHARED/000042/E12-5_XX qsub -N XY_E12.5 cell_ranger_job.sh E12-5_XY //analysisdata/rawseq/fastq/SHARED/000042/E12-5_XY qsub -N XX_FOSLCs cell_ranger_job.sh Induced_D6 //analysisdata/rawseq/fastq/SHARED/000042/Induced_D6 qsub -N XY_FTSLCs cell_ranger_job.sh 10x-ig168 //analysisdata/rawseq/fastq/SHARED/000128/JN00006966/10x-ig168 ``` <br> ### 2 . cellranger aggr https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/using/aggregate#cbc の"Aggregating libraries with differentchemistry versions"セクション まず集計CSVファイルを作成する XX_XY_aggr.csv ``` sample_id,molecule_h5,batch XX_E10.5,//osc-fs_home/s-maeda/22_TS_FTSLC_scRNAseq_2022/E10-5_XX/outs/molecule_info.h5,v2_lib XX_E11.5,//osc-fs_home/s-maeda/22_TS_FTSLC_scRNAseq_2022/E11-5_XX/outs/molecule_info.h5,v2_lib XX_E12.5,//osc-fs_home/s-maeda/22_TS_FTSLC_scRNAseq_2022/E12-5_XX/outs/molecule_info.h5,v2_lib XY_E10.5,//osc-fs_home/s-maeda/22_TS_FTSLC_scRNAseq_2022/E10-5_XY/outs/molecule_info.h5,v2_lib XY_E11.5,//osc-fs_home/s-maeda/22_TS_FTSLC_scRNAseq_2022/E11-5_XY/outs/molecule_info.h5,v2_lib XY_E12.5,//osc-fs_home/s-maeda/22_TS_FTSLC_scRNAseq_2022/E12-5_XY/outs/molecule_info.h5,v2_lib XX_FOSLCs,//osc-fs_home/s-maeda/22_TS_FTSLC_scRNAseq_2022/Induced_D6/outs/molecule_info.h5,v2_lib XY_FTSLCs,//osc-fs_home/s-maeda/22_TS_FTSLC_scRNAseq_2022/10x-ig168/outs/molecule_info.h5,v3.1_lib ``` cell_ranger_aggr.sh ``` #!/bin/bash #$ -S /bin/bash #$ -cwd #$ -pe smp 4 ## $1 id ## $2 csv file cellranger aggr --id = $1 \ --csv = $2 \ --normalize =mapped ``` ``` qsub -q bigmem.q -N aggr cell_ranger_aggr.sh agger_XX_XY XX_XY_aggr.csv ``` <br> ### 3 . Setup the Seurat Object ```r= library(dplyr) library(Seurat) library(patchwork) #Load the PBMC dataset aggr.data <- Read10X(data.dir = "/osc-fs_home/s-maeda/22_TS_FTSLC_scRNAseq_2022/agger_XX_XY/outs/count/filtered_feature_bc_matrix") #Initialize the Seurat object with the raw (non-normalized data) aggr <- CreateSeuratObject(counts = aggr.data , project = "FTSLC") ```