Cell Ranger alternatives to generate gene-count matrices for 10X data

This count workflow generates gene-count matrices from 10X FASTQ data using alternative methods other than Cell Ranger.

Prepare input data and import workflow

1. Run cellranger_workflow to generate FASTQ data

You can skip this step if your data are already in FASTQ format.

Otherwise, you need to first run cellranger_workflow to generate FASTQ files from BCL raw data for each sample. Please follow cellranger_workflow manual.

Notice that you should set run_mkfastq to true to get FASTQ output. You can also set run_count to false if you want to skip Cell Ranger count, and only use the result from count workflow.

For Non-Broad users, you’ll need to build your own docker for bcl2fastq step. Instructions are here.

2. Import count

Import count workflow to your workspace.

See the Terra documentation for adding a workflow. The count workflow is under Broad Methods Repository with name “cumulus/count”.

Moreover, in the workflow page, click the Export to Workspace... button, and select the workspace to which you want to export count workflow in the drop-down menu.

3. Prepare a sample sheet

3.1 Sample sheet format:

The sample sheet for count workflow should be in TSV format, i.e. columns are seperated by tabs not commas. Please note that the columns in the TSV can be in any order, but that the column names must match the recognized headings.

The sample sheet describes how to identify flowcells and generate channel-specific count matrices.

A brief description of the sample sheet format is listed below (required column headers are shown in bold).

Column Description
Sample Contains sample names. Each 10x channel should have a unique sample name.
Flowcells Indicates the Google bucket URLs of folder(s) holding FASTQ files of this sample.

The sample sheet supports sequencing the same 10x channel across multiple flowcells. If a sample is sequenced across multiple flowcells, simply list all of its flowcells in a comma-seperated way. In the following example, we have 2 samples sequenced in two flowcells.

Example:

Sample  Flowcells
sample_1        gs://fc-e0000000-0000-0000-0000-000000000000/VK18WBC6Z4/sample_1_fastqs,gs://fc-e0000000-0000-0000-0000-000000000000/VK10WBC9Z2/sample_1_fastqs
sample_2        gs://fc-e0000000-0000-0000-0000-000000000000/VK18WBC6Z4/sample_2_fastqs

Moreover, if one flowcell of a sample contains multiple FASTQ files for each read, i.e. sequences from multiple lanes, you should keep your sample sheet as the same, and count workflow will automatically merge lanes altogether for the sample before performing counting.

3.2 Upload your sample sheet to the workspace bucket:

Use gsutil (you already have it if you’ve installed Google cloud SDK) in your unix terminal to upload your sample sheet to workspace bucket.

Example:

gsutil cp /foo/bar/projects/sample_sheet.tsv gs://fc-e0000000-0000-0000-0000-000000000000/

4. Launch analysis

In your workspace, open count in WORKFLOWS tab. Select the desired snapshot version (e.g. latest). Select Process single workflow from files as below

_images/single_workflow1.png

and click SAVE button. Select Use call caching and click INPUTS. Then fill in appropriate values in the Attribute column. Alternative, you can upload a JSON file to configure input by clicking Drag or click to upload json.

Once INPUTS are appropriated filled, click RUN ANALYSIS and then click LAUNCH.

Workflow inputs

Below are inputs for count workflow. Notice that required inputs are in bold.

Name Description Example Default
input_tsv_file Input TSV sample sheet describing metadata of each sample. “gs://fc-e0000000-0000-0000-0000-000000000000/sample_sheet.tsv”  
genome Genome reference name. Current support: GRCh38, mm10. “GRCh38”  
chemistry 10X genomics’ chemistry name. Current support: “tenX_v3” (for V3 chemistry), “tenX_v2” (for V2 chemistry), “dropseq” (for Drop-Seq). “tenX_v3”  
output_directory GS URL of output directory. “gs://fc-e0000000-0000-0000-0000-000000000000/count_result”  
run_count If you want to run count tools to generate gene-count matrices. true true
count_tool

Count tool to generate result. Options:

 “StarSolo” “StarSolo”
docker_registry

Docker registry to use. Notice that docker image for Bustools is seperate.

  • “quay.io/cumulus” for images on Red Hat registry;
  • “cumulusprod” for backup images on Docker Hub.
 “quay.io/cumulus” “quay.io/cumulus”
config_version Version of config docker image to use. This docker is used for parsing the input sample sheet for downstream execution. Available options: 0.2, 0.1. “0.2” “0.2”
zones Google cloud zones to consider for execution. “us-east1-d us-west1-a us-west1-b” “us-central1-a us-central1-b us-central1-c us-central1-f us-east1-b us-east1-c us-east1-d us-west1-a us-west1-b us-west1-c”
num_cpu
Number of CPUs to request for count per channel.
Notice that when use Optimus for count, this input only affects steps of copying files. Optimus uses CPUs due to its own strategy.
 32 32
disk_space
Disk space in GB needed for count per channel.
Notice that when use Optimus for count, this input only affects steps of copying files. Optimus uses disk space due to its own strategy.
 500 500
memory
Memory size in GB needed for count per channel.
Notice that when use Optimus for count, this input only affects steps of copying files. Optimus uses memory size due to its own strategy.
 120 120
preemptible
Number of maximum preemptible tries allowed.
Notice that when use Optimus for count, this input only affects steps of copying files. Optimus uses preemptible tries due to its own strategy.
 2 2
merge_fastq_memory Memory size in GB needed for merge fastq per channel. 32 32
starsolo_star_version
STAR version to use. Currently only support “2.7.3a”.
This input only works when setting count_tool to StarSolo.
 “2.7.3a” “2.7.3a”
alevin_version
Salmon version to use. Currently only support “1.1”.
This input only works when setting count_tool to Alevin.
 “1.1” “1.1”
bustools_output_loom
If BUSTools generates gene-count matrices in loom format.
This input only works when setting count_tool to Bustools.
 false false
bustools_output_h5ad
If BUSTools generates gene-count matrices in h5ad format.
This input only works when setting count_tool to Bustools.
 false false
bustools_docker
Docker image used for Kallisto BUSTools count.
This input only works when setting count_tool to Bustools.
 “shaleklab/kallisto-bustools” “shaleklab/kallisto-bustools”
bustools_version
kb version to use. Currently only support “0.24.4”.
This input only works when setting count_tool to Bustools.
 “0.24.4” “0.24.4”
optimus_output_loom
If Optimus generates gene-count matrices in loom format.
This input only works when setting count_tool to Optimus.
 true true

Workflow outputs

See the table below for count workflow outputs.

Name Type Description
output_folder String Google Bucket URL of output directory. Within it, each folder is for one sample in the input sample sheet.