CPU:Minimum: 8 cores, 16 or more cores recommended.
RAM: Minimum: 16 GB, Recommended: 64 GB or more.
Disk Space: Minimum: 500 GB of available space. Recommended: 1 TB or
more.
Operating System: Linux (Ubuntu 16.04 or later, CentOS 6 or later)
Dependencies:GCC 6.1 or higher. Python 3.6 or later
Example of Recommended System Configuration
CPU: 32-core
Memory: 128 GB RAM.
Storage: 2 TB SSD
OS: CentOS 7. Python Version: Python 3.7.
# Use Ubuntu as the base image
FROM ubuntu:20.04
# Install necessary packages
RUN apt-get update && apt-get install -y wget bzip2
# Download and install CellRanger
RUN wget -qO- https://cf.10xgenomics.com/releases/cell-exp/cellranger-7.0.0.tar.gz | tar xz
# Set the environment variable to include CellRanger in the PATH
ENV PATH="/cellranger-7.0.0:$PATH"
# Set the working directory
WORKDIR /data
# Default command
CMD ["cellranger"]docker build -t cellranger-docker .Sample run
docker run -v /path/to/your/data:/data cellranger-docker count --id=SampleA_GEX \
--transcriptome=/data/reference/transcriptomes/Mouse_GEX_2020/refdata-gex-mm10-2020-A \
--fastqs=/data/raw_data/SampleA \
--sample=SampleA \
--expect-cells=10000Human : refdata-gex-GRCh38-2020-A
Mouse : refdata-gex-mm10-2020-A
Human+Mouse : refdata-gex-mm10-GRCh38-2020-A
(I will update cellranger reference location in rcapps5 later.I have
them in the server.)
To combine data from multiple samples processed by the cellranger count command.
csv file: required
library_id,molecule_h5
SampleA,/data/SampleA/outs/molecule_info.h5
SampleB,/data/SampleB/outs/molecule_info.h5Sample run
docker run -v /path/to/local_data:/data cellranger:7.0.0 aggr \
--id=aggregated_output \
--csv=/data/aggregation.csv