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Sample GSM5643580 Query DataSets for GSM5643580
Status Public on Nov 08, 2021
Title chemo baseline scRNAseq tech rep 1
Sample type SRA
 
Source name chemo baseline scRNAseq tech rep 1
Organism Mus musculus
Characteristics tissue: bone marrow
disease state: baseline
timepoint: baseline
molecule type: poly A mRNA
Treatment protocol Cells were transduced with GFP SPLINTR barcode libraries in polybrene (8.5 mg/mL) via spinfection (90 minutes at 1250 g). After the expansion period, barcoded cells were transplanted into either sub-lethally irradiated (5.5 Gy) Ptprca or non-irradiated NSG mice via lateral tail vein injection. Each mouse received 1x106 barcoded cells.
Growth protocol Secondary bone marrow cells from MLL-AF9 KRASG12D (KRAStm4Tyj/J) mice were cultured in RPMI-1640 medium supplemented with mouse IL-3 (10 ng/mL), human IL-6 (10 ng/mL), mouse SCF (50 ng/mL) 20% fetal bovine serum (FBS), streptomycin (100 ug/mL), penicillin (100 units/mL) and 2 mM glutamax in 5% CO2 at 37 °C.
Extracted molecule total RNA
Extraction protocol Viable cells were sorted on the BD FACSAria III directly into Eppendorf tubes. The cells were then washed twice with PBS + 0.04% BSA. Cells were then spun down and resuspended in PBS + 0.04% BSA + 0.4 U/ uL RNase Inhibitor (Roche) to a final cell concentrationof >1500 cells per uL. The final cell suspension was put through a cell strainer then onto a 10X Chromium Chip
Single cells were captured in droplet emulsions using the 10X Chromium Single-Cell Instrument and reverse transcription, cDNA amplification and library preparation were performed based on the manufacturer’s protocol using the Chromium Single Cell 3′ Library & Gel Bead Kit v3 (10X Genomics)
 
Library strategy RNA-Seq
Library source transcriptomic
Library selection cDNA
Instrument model Illumina NovaSeq 6000
 
Description baseline scRNAseq
Data processing Count matrices were generated from demultiplexed scRNA-seq fastq files using the 10X Genomics Cell Ranger v3.1.0 count pipeline against the mm10/GRCm38 genome.
scRNA-seq quality control was performed using Seurat v3.2 in R. Low quality cells were removed by filtering out cells that had fewer than 500 genes or 1000 unique molecular identifiers (UMIs). Cells with greater than 15% mitochondrial content were also removed.
For detection of the SPLINTR barcodes from single cell data, unmapped reads (which contain reads corresponding to barcode transcripts) were extracted from BAM alignment files for each scRNAseq library using SAMtools v1.9.
BAM entries containing SPLINTR barcode reads were identified and extracted using a regular expression specific to the barcode structure.
Barcode reads were mapped to the corresponding reference library using Bowtie v1.2.2 end-to-end alignment allowing a maximum of two mismatches.
Genome_build: mm10
Supplementary_files_format_and_content: matrix of gene names, matrix of gene names, matrix of 10x cell barcodes
Supplementary_files_format_and_content: matrix of gene counts - hashtag libraries, matrix of gene names - hashtag libraries, matrix of 10x cell barcodes - hashtag libraries
 
Submission date Oct 21, 2021
Last update date Nov 08, 2021
Contact name Mark Dawson
E-mail(s) mark.dawson@petermac.org
Organization name Peter MacCallum Cancer Centre
Street address 305 Grattan Street
City Melbourne
State/province VIC
ZIP/Postal code 3000
Country Australia
 
Platform ID GPL24247
Series (2)
GSE161676 Identifying non-genetic determinants of malignant clonal fitness at single cell resolution
GSE186305 Identifying non-genetic determinants of malignant clonal fitness at single cell resolution [chemo scRNAseq]
Relations
BioSample SAMN22458211
SRA SRX12722925

Supplementary file Size Download File type/resource
GSM5643580_KF16_TP0_1_barcodes.tsv.gz 96.5 Kb (ftp)(http) TSV
GSM5643580_KF16_TP0_1_features.tsv.gz 272.8 Kb (ftp)(http) TSV
GSM5643580_KF16_TP0_1_matrix.mtx.gz 289.8 Mb (ftp)(http) MTX
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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