Structure For each modality, the first folders represent a "subproject", which you can view as one run of the 10X Chromium. Inside it, you will find all the gel-bead-in-emulsion ids (GEM ids), which correspond to the output from a single 10X Chip Channel (see Cellranger glossary for more information). Inside each GEM-specific folder, you can find the most relevant files from the "outs" folder produced by CR. This include the expression/accessibility matrices, fragment files, web summaries (html with QC reports), and more. Here you can find a more detailed explanation of every output.To access processed data in the form of Seurat objects please check this other Zenodo repository. To access the data, documentation and reasoning behind each annotation in the tonsil atlas, please check the HCATonsilData package. Finally, to annotate cells from secondary lymphoid organs using the tonsil atlas as reference, check the Azimuth reference. Metadata We provide two levels of metadata:- Donor-level metadata: file "tonsil_atlas_donor_metadata.csv". For each of the 17 donors, this file specifies the hospital in which the tonsil was sampled (Clinic, CIMA or Newcastle), the sex, age, age group (child, young adult or old adult), the reason for tonsillectomy (tonsillitis, sleep apnea, or surgery for another condition), and the cohort type (discovery or validation). Note that for the four tonsils sampled in Newcastle we include the link between the original ids and the ones specific for this article (e.g. BCLL-20-T / TIP01)- Library-specific metadata: for each sequencing library, this metadata documents the subproject, GEM well (10X Chip Channel, see above), library name, library id, library type, and donor id. The donor_id column allows to link this table with the previous one (donor-level), and the gem_id column is important to understand which libraries were derived from the same GEM well. For instance, multiome GEM wells contain two library_ids per GEM well (RNA+ATAC).

This repository contains all the expression and accessibility matrices for each of the five data modalities (scRNA-seq, scATAC-seq, Multiome, CITE-seq+scVDJ-seq, and spatial transcriptomics) associated with the article "An Atlas of Cells in The Human Tonsil," published in Immunity in 2024. In particular, each modality was produced with different platforms from 10X Genomics and processed with different versions of CellRanger. This repository contains the most important outputs from each CellRanger run of each library. In addition, it also includes de expression and accessiblity matrices for the two mantle cell lymphoma (MCL) patients analyzed in the paper. Version 3.0 of this repository corrects the error with the scATAC-seq.zip folder as reported in an issue in the TonsilAtlas GitHub repo.