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cellranger-arc-count.cwl
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cellranger-arc-count.cwl
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cwlVersion: v1.0
class: CommandLineTool
requirements:
- class: InlineJavascriptRequirement
- class: InitialWorkDirRequirement
listing: |
${
var listing = [
{
"entry": inputs.gex_fastq_file_r1,
"entryname": "gex_S1_L001_R1_001.fastq",
"writable": true
},
{
"entry": inputs.gex_fastq_file_r2,
"entryname": "gex_S1_L001_R2_001.fastq",
"writable": true
},
{
"entry": inputs.atac_fastq_file_r1,
"entryname": "atac_S1_L001_R1_001.fastq",
"writable": true
},
{
"entry": inputs.atac_fastq_file_r2,
"entryname": "atac_S1_L001_R2_001.fastq",
"writable": true
},
{
"entry": inputs.atac_fastq_file_r3,
"entryname": "atac_S1_L001_R3_001.fastq",
"writable": true
},
{
"entry":`fastqs,sample,library_type
${runtime.outdir},gex,Gene Expression
${runtime.outdir},atac,Chromatin Accessibility`,
"entryname": "libraries.csv"
}
]
if (inputs.gex_fastq_file_i1){
listing.push(
{
"entry": inputs.gex_fastq_file_i1,
"entryname": "gex_S1_L001_I1_001.fastq",
"writable": true
}
);
};
if (inputs.gex_fastq_file_i2){
listing.push(
{
"entry": inputs.gex_fastq_file_i2,
"entryname": "gex_S1_L001_I2_001.fastq",
"writable": true
}
);
};
if (inputs.atac_fastq_file_i1){
listing.push(
{
"entry": inputs.atac_fastq_file_i1,
"entryname": "atac_S1_L001_I1_001.fastq",
"writable": true
}
);
};
return listing;
}
hints:
- class: DockerRequirement
dockerPull: cumulusprod/cellranger-arc:2.0.0
inputs:
gex_fastq_file_r1:
type: File
doc: |
GEX FASTQ read 1 file (will be staged into workdir as gex_S1_L001_R1_001.fastq)
gex_fastq_file_r2:
type: File
doc: |
GEX FASTQ read 2 file (will be staged into workdir as gex_S1_L001_R2_001.fastq)
gex_fastq_file_i1:
type: File?
doc: |
GEX FASTQ index i7 file (will be staged into workdir as gex_S1_L001_I1_001.fastq)
gex_fastq_file_i2:
type: File?
doc: |
GEX FASTQ index i5 file (will be staged into workdir as gex_S1_L001_I2_001.fastq)
atac_fastq_file_r1:
type: File
doc: |
ATAC FASTQ read 1 file (will be staged into workdir as atac_S1_L001_R1_001.fastq)
atac_fastq_file_r2:
type: File
doc: |
ATAC FASTQ read 2 (it's actually index i5) file (will be staged into workdir as atac_S1_L001_R2_001.fastq)
atac_fastq_file_r3:
type: File
doc: |
ATAC FASTQ read 3 (it's actually read 2) file (will be staged into workdir as atac_S1_L001_R3_001.fastq)
atac_fastq_file_i1:
type: File?
doc: |
ATAC FASTQ index i7 file (will be staged into workdir as atac_S1_L001_I1_001.fastq)
indices_folder:
type: Directory
inputBinding:
position: 5
prefix: "--reference"
doc: |
Compatible with Cell Ranger ARC reference folder that includes
STAR and BWA indices. Should be generated by "cellranger-arc mkref"
command
exclude_introns:
type: boolean?
inputBinding:
position: 6
prefix: "--gex-exclude-introns"
doc: |
Disable counting of intronic reads. In this mode, only reads that are exonic
and compatible with annotated splice junctions in the reference are counted.
Note: using this mode will reduce the UMI counts in the feature-barcode matrix
force_min_atac_counts:
type: int?
inputBinding:
position: 7
prefix: "--min-atac-count"
doc: |
Cell caller override: define the minimum number of ATAC transposition events
in peaks (ATAC counts) for a cell barcode.
Note: this option must be specified in conjunction with `--min-gex-count`.
With `--min-atac-count=X` and `--min-gex-count=Y` a barcode is defined as a cell
if it contains at least X ATAC counts AND at least Y GEX UMI counts
force_min_gex_counts:
type: int?
inputBinding:
position: 8
prefix: "--min-gex-count"
doc: |
Cell caller override: define the minimum number of GEX UMI counts for a cell barcode.
Note: this option must be specified in conjunction with `--min-atac-count`.
With `--min-atac-count=X` and `--min-gex-count=Y` a barcode is defined as a cell
if it contains at least X ATAC counts AND at least Y GEX UMI counts
force_peaks_bed_file:
type: File?
inputBinding:
position: 9
prefix: "--peaks"
doc: |
Peak caller override: specify peaks to use in downstream analyses from supplied 3-column BED file.
The supplied peaks file must be sorted by position and not contain overlapping peaks;
comment lines beginning with `#` are allowed
threads:
type: int?
inputBinding:
position: 10
prefix: "--localcores"
doc: |
Set max cores the pipeline may request at one time.
Default: all available
memory_limit:
type: int?
inputBinding:
position: 11
prefix: "--localmem"
doc: |
Set max GB the pipeline may request at one time
Default: all available
virt_memory_limit:
type: int?
inputBinding:
position: 12
prefix: "--localvmem"
doc: |
Set max virtual address space in GB for the pipeline
Default: all available
outputs:
web_summary_report:
type: File
outputBinding:
glob: "sample/outs/web_summary.html"
doc: |
Run summary metrics and charts in HTML format
metrics_summary_report:
type: File
outputBinding:
glob: "sample/outs/summary.csv"
doc: |
Run summary metrics in CSV format
barcode_metrics_report:
type: File
outputBinding:
glob: "sample/outs/per_barcode_metrics.csv"
doc: |
ATAC and GEX read count summaries generated for every
barcode observed in the experiment. The columns contain
the paired ATAC and Gene Expression barcode sequences,
ATAC and Gene Expression QC metrics for that barcode,
as well as whether this barcode was identified as a
cell-associated partition by the pipeline.
More details:
https://support.10xgenomics.com/single-cell-multiome-atac-gex/software/pipelines/latest/output/per_barcode_metrics
gex_possorted_genome_bam_bai:
type: File
outputBinding:
glob: "sample/outs/gex_possorted_bam.bam"
secondaryFiles:
- .bai
doc: |
GEX position-sorted reads aligned to the genome and transcriptome annotated with barcode
information in BAM format
atac_possorted_genome_bam_bai:
type: File
outputBinding:
glob: "sample/outs/atac_possorted_bam.bam"
secondaryFiles:
- .bai
doc: |
ATAC position-sorted reads aligned to the genome annotated with barcode
information in BAM format
filtered_feature_bc_matrix_folder:
type: Directory
outputBinding:
glob: "sample/outs/filtered_feature_bc_matrix"
doc: |
Filtered feature barcode matrix stored as a CSC sparse matrix in MEX format.
The rows consist of all the gene and peak features concatenated together
(identical to raw feature barcode matrix) and the columns are restricted to
those barcodes that are identified as cells.
filtered_feature_bc_matrix_h5:
type: File
outputBinding:
glob: "sample/outs/filtered_feature_bc_matrix.h5"
doc: |
Filtered feature barcode matrix stored as a CSC sparse matrix in hdf5 format.
The rows consist of all the gene and peak features concatenated together
(identical to raw feature barcode matrix) and the columns are restricted to
those barcodes that are identified as cells.
raw_feature_bc_matrices_folder:
type: Directory
outputBinding:
glob: "sample/outs/raw_feature_bc_matrix"
doc: |
Raw feature barcode matrix stored as a CSC sparse matrix in MEX format.
The rows consist of all the gene and peak features concatenated together
and the columns consist of all observed barcodes with non-zero signal for
either ATAC or gene expression.
raw_feature_bc_matrices_h5:
type: File
outputBinding:
glob: "sample/outs/raw_feature_bc_matrix.h5"
doc: |
Raw feature barcode matrix stored as a CSC sparse matrix in hdf5 format.
The rows consist of all the gene and peak features concatenated together
and the columns consist of all observed barcodes with non-zero signal for
either ATAC or gene expression.
secondary_analysis_report_folder:
type: Directory
outputBinding:
glob: "sample/outs/analysis"
doc: |
Various secondary analyses that utilize the ATAC data, the GEX data, and their
linkage: dimensionality reduction and clustering results for the ATAC and GEX
data, differential expression, and differential accessibility for all clustering
results above and linkage between ATAC and GEX data.
gex_molecule_info_h5:
type: File
outputBinding:
glob: "sample/outs/gex_molecule_info.h5"
doc: |
Count and barcode information for every GEX molecule observed in the experiment
in hdf5 format.
loupe_browser_track:
type: File
outputBinding:
glob: "sample/outs/cloupe.cloupe"
doc: |
Loupe Browser visualization file with all the analysis outputs
atac_fragments_file:
type: File
outputBinding:
glob: "sample/outs/atac_fragments.tsv.gz"
secondaryFiles:
- .tbi
doc: |
Count and barcode information for every ATAC fragment observed in
the experiment in TSV format.
atac_peaks_bed_file:
type: File
outputBinding:
glob: "sample/outs/atac_peaks.bed"
doc: |
Locations of open-chromatin regions identified in this sample.
These regions are referred to as "peaks".
atac_cut_sites_bigwig_file:
type: File
outputBinding:
glob: "sample/outs/atac_cut_sites.bigwig"
doc: |
Genome track of observed transposition sites in the experiment
smoothed at a resolution of 400 bases in BIGWIG format.
atac_peak_annotation_file:
type: File
outputBinding:
glob: "sample/outs/atac_peak_annotation.tsv"
doc: |
Annotations of peaks based on genomic proximity alone.
Note that these are not functional annotations and they
do not make use of linkage with GEX data.
stdout_log:
type: stdout
stderr_log:
type: stderr
baseCommand: ["cellranger-arc", "count", "--disable-ui", "--libraries", "libraries.csv", "--id", "sample"]
stdout: cellranger_arc_count_stdout.log
stderr: cellranger_arc_count_stderr.log
$namespaces:
s: http://schema.org/
$schemas:
- https://github.com/schemaorg/schemaorg/raw/main/data/releases/11.01/schemaorg-current-http.rdf
label: "Cell Ranger ARC Count Chromatin Accessibility and Gene Expression"
s:name: "Cell Ranger ARC Count Chromatin Accessibility and Gene Expression"
s:alternateName: "Quantifies chromatin accessibility and gene expression from a single-cell Multiome ATAC/RNA-Seq library"
s:downloadUrl: https://raw.githubusercontent.com/Barski-lab/sc-seq-analysis/main/tools/cellranger-arc-count.cwl
s:codeRepository: https://github.com/Barski-lab/sc-seq-analysis
s:license: http://www.apache.org/licenses/LICENSE-2.0
s:isPartOf:
class: s:CreativeWork
s:name: Common Workflow Language
s:url: http://commonwl.org/
s:creator:
- class: s:Organization
s:legalName: "Cincinnati Children's Hospital Medical Center"
s:location:
- class: s:PostalAddress
s:addressCountry: "USA"
s:addressLocality: "Cincinnati"
s:addressRegion: "OH"
s:postalCode: "45229"
s:streetAddress: "3333 Burnet Ave"
s:telephone: "+1(513)636-4200"
s:logo: "https://www.cincinnatichildrens.org/-/media/cincinnati%20childrens/global%20shared/childrens-logo-new.png"
s:department:
- class: s:Organization
s:legalName: "Allergy and Immunology"
s:department:
- class: s:Organization
s:legalName: "Barski Research Lab"
s:member:
- class: s:Person
s:name: Michael Kotliar
s:email: mailto:[email protected]
s:sameAs:
- id: http://orcid.org/0000-0002-6486-3898
doc: |
Cell Ranger ARC Count Chromatin Accessibility and Gene Expression
Quantifies chromatin accessibility and gene expression from a
single-cell Multiome ATAC/RNA-Seq library.
Parameters set by default:
--disable-ui - no need in any UI when running in Docker container
--id - hardcoded to `sample` to simplify output files location
--libraries - points to the file libraries.csv generated based on
the input FASTQ files
No implemented parameters:
--no-bam - we want to always generate BAM files
--dry
--noexit
--nopreflight
--description
--uiport
--overrides
--jobinterval
--maxjobs
--mempercore
--jobmode (we will use local by default)
Why do we need to rename input files?
https://support.10xgenomics.com/single-cell-multiome-atac-gex/software/pipelines/latest/using/using/fastq-input