For convenient multi-sample analysis, the spaceranger aggr
pipeline generates output files that contain all the data from the individual input jobs, aggregated into single output files. The capture area suffix of each barcode is updated to prevent barcode collisions.
A successful spaceranger aggr
run should conclude with a message similar to this:
Outputs:
- Aggregation metrics summary HTML: /opt/runs/AGG123/outs/web_summary.html
- Aggregation metrics summary JSON: /opt/runs/AGG123/outs/summary.json
- Secondary analysis output CSV: /opt/runs/AGG123/outs/analysis
- Filtered feature-barcode matrices MEX: /opt/runs/AGG123/outs/filtered_feature_bc_matrix
- Filtered feature-barcode matrices HDF5: /opt/runs/AGG123/outs/filtered_feature_bc_matrix.h5
- Copy of the input aggregation CSV: /opt/runs/AGG123/outs/aggregation.csv
- Loupe Browser file: /opt/runs/AGG123/outs/cloupe.cloupe
- Aggregated tissue positions list: /opt/runs/AGG123/outs/aggr_tissue_positions.csv
- Spatial folder containing spatial images and scalefactors: /opt/runs/AGG123/outs/spatial
Pipestance completed successfully!
Upon completion, all the main pipeline outputs can be found in the outs/
subfolder which has the following structure from the example code:
outs
├── aggregation.csv
├── aggr_tissue_positions.csv
├── analysis
│ ├── clustering
│ ├── diffexp
│ ├── pca
│ ├── tsne
│ └── umap
├── cloupe.cloupe
├── filtered_feature_bc_matrix
│ ├── barcodes.tsv.gz
│ ├── features.tsv.gz
│ └── matrix.mtx.gz
├── filtered_feature_bc_matrix.h5
├── spatial
│ ├── LV123
│ │ ├── scalefactors_json.json
│ │ ├── tissue_hires_image.png
│ │ └── tissue_lowres_image.png
│ ├── LB456
│ │ ├── scalefactors_json.json
│ │ ├── tissue_hires_image.png
│ │ └── tissue_lowres_image.png
│ └── LP789
│ ├── scalefactors_json.json
│ ├── tissue_hires_image.png
│ └── tissue_lowres_image.png
├── summary.json
└── web_summary.html
The files are similar to the spaceranger count
pipeline outputs. The aggr
pipeline also outputs a copy of the input aggregation.csv
.
spaceranger aggr
does not perform a spot-calling step, it simply aggregates the spot calls from each input job into a final set of spot calls.The outputs for multi-library spaceranger aggr
run will be identical the outputs for single library, with the inclusion of the Antibody specific metrics in the web_summary.html
, summary.json
file and in the filtered feature-barcode matrices.
The spaceranger aggr
pipeline outputs summary.json
that contains metrics relating to the aggregated datasets. Note: Square brackets denote a variable that depends on the pipeline input, such as, [library_id]_frac_reads_kept
means that if your aggregation contains two libraries with IDs sample123
and sample456
, there are two output metrics sample123_frac_reads_kept
and sample456_frac_reads_kept
.
For aggregated datasets that contain both Gene and Protein Expression libraries, there are additional metrics for Protein Capture that include [Antibody]
in the metric name.
Metric | Description |
---|---|
filtered_bcs_transcriptome_union | The estimated number of barcodes associated with a spot under tissue, summed across all input libraries. |
[pre/post]_total_reads | Total number of sequenced reads, summed across all input libraries. |
[pre/post]_multi_transcriptome_total_raw_reads_per_filtered_bc | total_reads divided by filtered_bcs_transcriptome_union |
[library_id]_pre_normalization_raw_reads_per_filtered_bc | The mean total reads per spot prior to depth normalization, for the library denoted by library_id |
[library_id]_pre_normalization_cmb_reads_per_filtered_bc | The mean confidently mapped and barcoded (CMB) reads per spot prior to depth normalization, for the library denoted by library_id . |
[library_id]_frac_reads_kept | The fraction of reads that were retained after depth normalization for the library denoted by library_id |
lowest_frac_reads_kept | The lowest fraction of reads retained, corresponding to the library which lost the most reads during normalization. A low value may indicate a large disparity in the initial depth of the input libraries. |
If one or more of the aggregated samples was a Targeted Gene Expression sample, these additional metrics will also appear:
Metric | Description |
---|---|
[library_id]_pre_normalization_targeted_reads_per_filtered_bc | The mean targeted reads per spot prior to depth normalization, for the library denoted by library_id |
[library_id]_frac_targeted_reads_kept | The fraction of reads mapped uniquely and confidently to targeted genes that were retained after depth normalization for the library denoted by library_id . This field will be shown instead of the metric [library_id]_frac_reads_kept above |