Longitudinal single-cell multiomics data for different severity of COVID-19
Single-cell RNA-seq · human · 100 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 100 samples: 100 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- Tracking antigen-specific TCR clonotypes in SARS-CoV-2 infection reveals distinct severity trajectoriesJournal of medical virology · 2023
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE196198_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA803889. Searching any of these in the dataset finder brings you back here.
Supports a case/control comparison: 92 samples read as cases, 8 as controls.
How we read this: Read from 100 sample titles: 100 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM5862479 PBMCs, Healthy donor 1 5' Expression
- GSM5862480 PBMCs, Healthy donor 1 TCR
- GSM5862481 PBMCs, Healthy donor 1 BCR
- GSM5862482 PBMCs, Healthy donor 1 Feature Barcode
- GSM5862483 PBMCs, Healthy donor 2 5' Expression
- GSM5862484 PBMCs, Healthy donor 2 TCR
- GSM5862485 PBMCs, Healthy donor 2 BCR
- GSM5862486 PBMCs, Healthy donor 2 Feature Barcode
- GSM5862487 PBMCs, Asymptomatic patient 1 5' Expression
- GSM5862488 PBMCs, Asymptomatic patient 1 TCR
- GSM5862489 PBMCs, Asymptomatic patient 1 BCR
- GSM5862490 PBMCs, Asymptomatic patient 1 Feature Barcode
- GSM5862491 PBMCs, Asymptomatic patient 2 5' Expression
- GSM5862492 PBMCs, Asymptomatic patient 2 TCR
- GSM5862493 PBMCs, Asymptomatic patient 2 BCR
- GSM5862494 PBMCs, Asymptomatic patient 2 Feature Barcode
- GSM5862495 PBMCs, Mild patient 1 (1st week of infection) 5' Expression
- GSM5862496 PBMCs, Mild patient 1 (1st week of infection) TCR
- GSM5862497 PBMCs, Mild patient 1 (1st week of infection) BCR
- GSM5862498 PBMCs, Mild patient 1 (1st week of infection) Feature Barcode
- GSM5862499 PBMCs, Mild patient 1 (2nd week of infection) 5' Expression
- GSM5862500 PBMCs, Mild patient 1 (2nd week of infection) TCR
- GSM5862501 PBMCs, Mild patient 1 (2nd week of infection) BCR
- GSM5862502 PBMCs, Mild patient 1 (2nd week of infection) Feature Barcode
- GSM5862503 PBMCs, Mild patient 1 (4th week of infection) 5' Expression
- GSM5862504 PBMCs, Mild patient 1 (4th week of infection) TCR
- GSM5862505 PBMCs, Mild patient 1 (4th week of infection) BCR
- GSM5862506 PBMCs, Mild patient 1 (4th week of infection) Feature Barcode
- GSM5862507 PBMCs, Mild patient 2 (1st week of infection) 5' Expression
- GSM5862508 PBMCs, Mild patient 2 (1st week of infection) TCR
- GSM5862509 PBMCs, Mild patient 2 (1st week of infection) BCR
- GSM5862510 PBMCs, Mild patient 2 (1st week of infection) Feature Barcode
- GSM5862511 PBMCs, Mild patient 2 (2nd week of infection) 5' Expression
- GSM5862512 PBMCs, Mild patient 2 (2nd week of infection) TCR
- GSM5862513 PBMCs, Mild patient 2 (2nd week of infection) BCR
- GSM5862514 PBMCs, Mild patient 2 (2nd week of infection) Feature Barcode
- GSM5862515 PBMCs, Mild patient 2 (4th week of infection) 5' Expression
- GSM5862516 PBMCs, Mild patient 2 (4th week of infection) TCR
- GSM5862517 PBMCs, Mild patient 2 (4th week of infection) BCR
- GSM5862518 PBMCs, Mild patient 2 (4th week of infection) Feature Barcode
+ 60 more — browse all 100 samples with per-sample file links →
- GSE253661 Longitudinal single-cell transcriptomics of monocytes, Tfh and gd Tcells following a control human malaria infection. 16 samples shares longitudinal, single-cell
- GSE282122 A longitudinal single-cell atlas of anti-tumour necrosis factor treatment in inflammatory bowel disease 216 samples shares longitudinal, single-cell
- GSE328048 Single-cell transcriptome reveals keratinocyte subclusters that contribute to altered differentiation and inflammatory responses in atopic dermatitis 116 samples shares single-cell, different
- GSE292623 A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma 18 samples shares longitudinal, single-cell
- GSE339365 Genome-wide H3K4me3 profiling of circulating immune cells reveals dynamic epigenetic reprogramming during acute critical COVID-19 120 samples shares covid-19
- GSE271370 Spatial transcriptomics unveils the in situ cellular and molecular hallmarks of the lung in fatal COVID-19 23 samples shares covid-19
- GSE279392 Single-cell RNA and TCR sequencing from skin, blood and cerebral spinal fluid (CSF) samples from Degos disease patients 116 samples shares single-cell
- GSE309593 Longitudinal Analysis of Multiple Myeloma: Therapeutic Response and Immune Microenvironment Dynamics in the Context of Tumor Heterogeneity [CITE-Seq] 91 samples shares longitudinal
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.