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Space Ranger

Space Ranger is a set of analysis pipelines that process Visium spatial RNA-seq output as well as brightfield and fluorescence microscope images in order to detect tissue, align reads, generate feature-spot matrices, perform clustering and place spots in spatial context on the slide image.

Space Ranger is available as a module on Apocrita.

Deprecated feature

Space Ranger no longer supports targeted gene expression analysis.

Usage

To run the default installed version of Space Ranger, simply load the spaceranger module:

$ module load spaceranger
$ spaceranger

Process 10x Genomics Spatial Gene Expression data

USAGE:
    spaceranger <SUBCOMMAND>

FLAGS:
    -h, --help       Prints help information
    -V, --version    Prints version information
...

For more information regarding each analysis pipeline, pass the --help key after the pipeline sub-command (i.e. spaceranger count --help).

Local operating mode

The local mode will execute the pipeline on a single machine, usually within a cluster job. To run all executions inside a single job, this is the desired mode.

Cores and Memory Requests

To avoid overloading a node, set the --localcores ${NSLOTS} option to restrict Space Ranger to use the specified number of cores to execute pipeline rather than all cores available.

To prevent your job from being killed by the scheduler for using more memory than requested, set the --localmem option to restrict Space Ranger to use specified amount of memory (in GB) to execute pipeline stages rather than to use 90% of total memory available.

Example job

Serial job

Here is an example job running on 4 cores and 16GB of memory to generate spatial feature counts for a single library using automatic fiducial alignment and tissue detection, in local mode:

#!/bin/bash
#$ -cwd
#$ -j y
#$ -pe smp 4
#$ -l h_rt=1:0:0
#$ -l h_vmem=4G

module load spaceranger

spaceranger count   --id=1234 \
                    --transcriptome=example_transcriptome \
                    --create-bam true \
                    --fastqs=raw_data.fastq \
                    --image=sample_1234.tif \
                    --slide=V19J01-123 \
                    --area=A1 \
                    --disable-ui \
                    --localcores ${NSLOTS} \
                    --localmem 4

Reference