Run STARsolo to generate gene-count matrices from FASTQ files¶
star_solo workflow generates gene-count matrices from FASTQ data using STARsolo.
Prepare input data and import workflow¶
cellranger_workflow to generate FASTQ data¶
You can skip this step if your data are already in FASTQ format.
Otherwise, for 10X data, 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
trueto get FASTQ output. You can also set run_count to
falseto skip Cell Ranger count step.
For Non-Broad users, you’ll need to build your own docker for bcl2fastq step. Instructions are here.
Import star_solo workflow to your workspace.
See the Terra documentation for adding a workflow. The star_solo workflow is under
Broad Methods Repositorywith name “cumulus/star_solo”.
Moreover, in the workflow page, click the
Export to Workspace...button, and select the workspace to which you want to export star_solo workflow in the drop-down menu.
3. Prepare a sample sheet¶
3.1 Sample sheet format:
The sample sheet for star_solo workflow should be in TSV format, i.e. columns are separated 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 sample/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 sample or 10X channel should have a unique sample name. Flowcells Indicates the Google bucket URLs of folder(s) holding FASTQ files of this sample.
For 10X data, 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
Alternatively, if you want to specify Read 1 and 2 FASTQ files yourself, you should prepare the sample sheet of the following format:Sample R1 R2 sample_1 gs://your-bucket/sample_1_L001_R1.fastq.gz,gs://your-bucket/sample_1_L002_R1.fastq.gz gs://your-bucket/sample_1_L001_R2.fastq.gz,gs://your-bucket/sample_1_L002_R2.fastq.gz sample_2 gs://your-bucket/sample_2_L001_R1.fastq.gz gs://your-bucket/sample_2_L001_R2.fastq.gz
where FASTQ files in R1 and R2 should be in one-to-one correspondence if the sample has multiple R1 FASTQ files.
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
WORKFLOWStab. Select the desired snapshot version (e.g. latest). Select
Process single workflow from filesas below
Use call cachingand click
INPUTS. Then fill in appropriate values in the
Attributecolumn. 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 ANALYSISand then click
Below are inputs for count workflow. Notice that required inputs are in bold.
|input_tsv_file||Input TSV sample sheet describing metadata of each sample.||“gs://fc-e0000000-0000-0000-0000-000000000000/sample_sheet.tsv”|
Genome reference. It can be either of the following two formats:
|chemistry||Chemistry name. Available options: “tenX_v3” (for 10X V3 chemistry), “tenX_v2” (for 10X V2 chemistry), “DropSeq”, and “SeqWell”.||“tenX_v3”|
|output_directory||GS URL of output directory.||“gs://fc-e0000000-0000-0000-0000-000000000000/count_result”|
Docker registry to use:
|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 sample.||32||32|
|disk_space||Disk space in GB needed for count per sample.||500||500|
|memory||Memory size in GB needed for count per sample.||120||120|
|preemptible||Number of maximum preemptible tries allowed.||2||2|
|star_version||STAR version to use. Currently only support
|config_version||Version of docker image to run configuration on the sample sheet. Currently only has version “0.1”.||“0.1”||“0.1”|
See the table below for star_solo workflow outputs.
|output_folder||String||Google Bucket URL of output directory. Within it, each folder is for one sample in the input sample sheet.|