The ScPCA Portal download packages include gene expression data, a QC report, and associated metadata for each processed sample. These files are delivered as a zip file.

For all downloads, sample folders (indicated by the SCPCS prefix) contain the files for all libraries (SCPCL prefix) derived from that biological sample. Most samples only have one library that has been sequenced. For multiplexed sample libraries, the sample folder name will be an underscore-separated list of all samples found in the library files that the folder contains.

The files associated with each library are (example shown for a library with ID SCPCL000000):

• An unfiltered counts file: SCPCL000000_unfiltered.rds,

• A filtered counts file: SCPCL000000_filtered.rds,

• A quality control report: SCPCL000000_qc.html,

Every download also includes a single single_cell_metadata.tsv file containing metadata for all libraries included in the download.

The folder structure within the zip file is determined by whether individual samples or all samples associated with a project are selected for download.

If a project contains bulk RNA-seq data, two tab-separated value files, bulk_quant.tsv and bulk_metadata.tsv, will be included in the download. The bulk_quant.tsv file contains a gene by sample matrix (each row a gene, each column a sample) containing raw gene expression counts quantified by Salmon. The bulk_metadata.tsv file contains associated metadata for all samples with bulk RNA-seq data.

Note that if a sample selected for download contains a spatial transcriptomics library, the files included will be different than pictured above. See the description of the Spatial transcriptomics output section below.

## Gene expression data

Single-cell or single-nuclei gene expression data is provided in two forms - as an unfiltered counts file and a filtered counts file.

The unfiltered counts file, SCPCL000000_unfiltered.rds, is an RDS file containing a SingleCellExperiment object. Within the SingleCellExperiment object is the counts matrix, where the rows correspond to genes or features and the columns correspond to cell barcodes. Here, all potential cell barcodes that are identified after running alevin-fry are included in the counts matrix. The object also includes summary statistics for each cell barcode and gene, as well as metadata about that particular library, such as the reference index and software versions used for mapping and quantification.

The filtered counts file, SCPCL000000_filtered.rds is also an RDS file containing a SingleCellExperiment object with the same structure as above. The cells in this file are those that remain after filtering using emptyDrops. As a result, this file only contains cell barcodes that are likely to correspond to true cells.

See Single-cell gene expression file contents for more information about the contents of the SingleCellExperiment objects and the included statistics and metadata. See also Using the provided RDS files in R.

## QC Report

The included QC report serves as a general overview of each library, including processing information, summary statistics and general visualizations of cell metrics.

The single_cell_metadata.tsv file is a tab-separated table with one row per library and the following columns.

column_id

contents

scpca_sample_id

Sample ID in the form SCPCS000000

scpca_library_id

Library ID in the form SCPCL000000

seq_unit

cell for single-cell samples or nucleus for single-nucleus samples

technology

10X kit used to process library

filtered_cell_count

Number of cells after filtering with emptyDrops

submitter_id

Original sample identifier from submitter

participant_id

Original participant id, if there are multiple samples from the same participant

submitter

Submitter name/id

age

Age at time sample was obtained

sex

Sex of patient that the sample was obtained from

diagnosis

Tumor type

subdiagnosis

Subcategory of diagnosis or mutation status (if applicable)

tissue_location

Where in the body the tumor sample was located

disease_timing

What stage of disease was the sample obtained? At diagnosis or recurrence?

Additional metadata may also be included, specific to the disease type and experimental design of the project. Examples of this include treatment or outcome. Metadata pertaining to processing will also be available in this table and inside of the SingleCellExperiment object. See the Experiment metadata section for more information on metadata columns that can be found in this file as well as inside the SingleCellExperiment object.

For projects with bulk RNA-seq data, the bulk_metadata.tsv file will be included for project downloads. This file will contain fields equivalent to those found in the single_cell_metadata.tsv related to processing the sample, but will not contain patient or disease specific metadata (e.g. age, sex, diagnosis, subdiagnosis, tissue_location, or disease_timing).

## Multiplexed sample libraries

For libraries where multiple biological samples were combined via cellhashing or similar technology (see the FAQ section about multiplexed samples), the organization of the downloaded files and metadata is slightly different.

For project downloads, the counts and QC files will be organized by the set of samples that comprise each library, rather than in individual sample folders. These sample set folders are named with an underscore-separated list of the sample ids for the libraries within, e.g., SCPCS999990_SCPCS999991_SCPCS999992. Bulk RNA-seq data, if present, will follow the same format as bulk RNA-seq for single-sample libraries.

Because we do not perform demultiplexing to separate cells from multiplexed libraries into sample-specific count matrices, sample downloads from a project with multiplexed data will include all libraries that contain the sample of interest, but these libraries will still contain cells from other samples.

For more on the specific contents of multiplexed library SingleCellExperiment objects, see the Additional SingleCellExperiment components for multiplexed libraries section.

The metadata file for multiplexed libraries (single_cell_metadata.tsv) will have the same format as for individual samples, but each row will represent a particular sample/library pair, meaning that there may be multiple rows for each scpca_library_id, one for each scpca_sample_id within that library.

## Spatial transcriptomics libraries

If a sample includes a library processed using spatial transcriptomics, the spatial transcriptomics output files will be available as a separate download from the single-cell/single-nuclei gene expression data.

For all spatial transcriptomics libraries, a SCPCL000000_spatial folder will be nested inside the corresponding sample folder in the download. Inside that folder will be the following folders and files:

A full description of all files included in the download for spatial transcriptomics libraries can also be found in the spaceranger count documentation.

Every download also includes a single spatial_metadata.tsv file containing metadata for all libraries included in the download.