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Understanding Outputs

Understanding Outputs

Cell Ranger ARC strives to maintain compatibility with common analysis tools by using standard output file formats whenever possible. The Chromium-specific data, including cellular and molecular barcodes, can be accessed by third-party tools or scripts that can parse the additional elements utilized by Cell Ranger ARC.

All pipeline outputs are produced in a single pipeline output directory, which is specified by the --id argument for cellranger-arc (defaults to the flow cell serial number, e.g., HAWT7ADXX when the --id argument is not specified).

Output files are saved in the outs/ subdirectory within this pipeline output directory. The contents include:

Example subdirectory structure of the /outs directory:

├── analysis │ ├── clustering │ │ ├── atac │ │ │ ├── peaks_graphclust │ │ │ │ ├── clusters.csv │ │ │ │ ├── differential_accessibility.csv │ │ │ │ └── differential_expression.csv │ │ │ ├── peaks_kmeans_2_clusters │ │ │ │ ├── clusters.csv │ │ │ │ ├── differential_accessibility.csv │ │ │ │ └── differential_expression.csv │ │ │ ├── peaks_kmeans_3_clusters │ │ │ │ ├── clusters.csv │ │ │ │ ├── differential_accessibility.csv │ │ │ │ └── differential_expression.csv │ │ │ ├── peaks_kmeans_4_clusters │ │ │ │ ├── clusters.csv │ │ │ │ ├── differential_accessibility.csv │ │ │ │ └── differential_expression.csv │ │ │ └── peaks_kmeans_5_clusters │ │ │ ├── clusters.csv │ │ │ ├── differential_accessibility.csv │ │ │ └── differential_expression.csv │ │ └── gex │ │ ├── gene_expression_graphclust │ │ │ ├── clusters.csv │ │ │ ├── differential_accessibility.csv │ │ │ └── differential_expression.csv │ │ ├── gene_expression_kmeans_2_clusters │ │ │ ├── clusters.csv │ │ │ ├── differential_accessibility.csv │ │ │ └── differential_expression.csv │ │ ├── gene_expression_kmeans_3_clusters │ │ │ ├── clusters.csv │ │ │ ├── differential_accessibility.csv │ │ │ └── differential_expression.csv │ │ ├── gene_expression_kmeans_4_clusters │ │ │ ├── clusters.csv │ │ │ ├── differential_accessibility.csv │ │ │ └── differential_expression.csv │ │ └── gene_expression_kmeans_5_clusters │ │ ├── clusters.csv │ │ ├── differential_accessibility.csv │ │ └── differential_expression.csv │ ├── dimensionality_reduction │ │ ├── atac │ │ │ ├── lsa_components.csv │ │ │ ├── lsa_dispersion.csv │ │ │ ├── lsa_features_selected.csv │ │ │ ├── lsa_projection.csv │ │ │ ├── lsa_variance.csv │ │ │ ├── tsne_projection.csv │ │ │ └── umap_projection.csv │ │ └── gex │ │ ├── pca_components.csv │ │ ├── pca_dispersion.csv │ │ ├── pca_features_selected.csv │ │ ├── pca_projection.csv │ │ ├── pca_variance.csv │ │ ├── tsne_projection.csv │ │ └── umap_projection.csv │ ├── feature_linkage │ │ ├── feature_linkage.bedpe │ │ └── feature_linkage_matrix.h5 │ └── tf_analysis │ ├── filtered_tf_bc_matrix │ │ ├── barcodes.tsv.gz │ │ ├── matrix.mtx.gz │ │ └── motifs.tsv │ ├── filtered_tf_bc_matrix.h5 │ └── peak_motif_mapping.bed ├── cell_types │ ├── 10x_Cloud # for cloud-based annotation models │ │ ├── cell_annotation_differential_expression.csv │ │ ├── cell_annotation_results.json.gz │ │ └── cell_types.csv │ └── Azimuth │ ├── cell_annotation_differential_expression.csv │ └── cell_types.csv ├── atac_cut_sites.bigwig ├── atac_fragments.tsv.gz ├── atac_fragments.tsv.gz.tbi ├── atac_peak_annotation.tsv ├── atac_peaks.bed ├── cloupe.cloupe ├── filtered_feature_bc_matrix │ ├── barcodes.tsv.gz │ ├── features.tsv.gz │ └── matrix.mtx.gz ├── filtered_feature_bc_matrix.h5 ├── gex_molecule_info.h5 ├── per_barcode_metrics.csv ├── raw_feature_bc_matrix │ ├── barcodes.tsv.gz │ ├── features.tsv.gz │ └── matrix.mtx.gz ├── raw_feature_bc_matrix.h5 ├── summary.csv └── web_summary.html

More information about the contents of the pipeline output directory can be found in the Pipestance Structure page.

Brief description of output files:

File NameDescription
web_summary.htmlRun summary metrics and charts in HTML format.
summary.csvRun summary metrics in CSV format.
raw_feature_bc_matrix.h5Raw 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.
raw_feature_bc_matrixRaw 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.
per_barcode_metrics.csvATAC and GEX read count summaries generated for every barcode observed in the experiment. For more details see Per-barcode metrics.
gex_possorted_bam.bamGEX reads aligned to the genome and transcriptome annotated with barcode information in BAM format.
gex_possorted_bam.bam.baiIndex for gex_possorted_bam.bam.
gex_molecule_info.h5Count and barcode information for every GEX molecule observed in the experiment in hdf5 format.
filtered_feature_bc_matrix.h5Filtered 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.
filtered_feature_bc_matrixFiltered 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.
cloupe.cloupeLoupe Browser visualization file with all the analysis outputs.
atac_possorted_bam.bamATAC reads aligned to the genome annotated with barcode information in BAM format.
atac_possorted_bam.bam.baiIndex for atac_possorted_bam.bam.
atac_peaks.bedLocations of open-chromatin regions identified in this sample. These regions are referred to as "peaks".
atac_peak_annotation.tsvAnnotations 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.
atac_fragments.tsv.gzCount and barcode information for every ATAC fragment observed in the experiment in TSV format.
atac_fragments.tsv.gz.tbiIndex for atac_fragments.tsv.gz.
atac_cut_sites.bigwigGenome track of observed transposition sites in the experiment smoothed at a resolution of 400 bases in BIGWIG format.
analysisVarious 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. See Analysis Overview for more information.