Label-free single-cell RNA Multiplexing leveraging genetic variability
Single-cell RNA-seq · human · 29 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
- 29 samples: 8 × Heart_2_bulkRNA-seq Patient vs 5 × PBMC_bulkRNA-seq Patient vs 5 × Heart_bulkRNA-seq_Patient vs 4 × Kidney_bulkRNA-seq_PatientGroups 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
- Label-free single-cell RNA multiplexing leveraging genetic variabilityNature communications · 2024
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 GSE247708_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 PRJNA1040187 and SRA study SRP471822. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 22 samples.
How we read this: 4 replicated groups read from 29 sample titles; they account for 22 of them. 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.
- GSM7899143 PBMC_bulkRNA-seq Patient_1 PBMC_bulkRNA-seq Patient
- GSM7899144 PBMC_bulkRNA-seq Patient_2 PBMC_bulkRNA-seq Patient
- GSM7899145 PBMC_bulkRNA-seq Patient_3 PBMC_bulkRNA-seq Patient
- GSM7899146 PBMC_bulkRNA-seq Patient_4 PBMC_bulkRNA-seq Patient
- GSM7899147 PBMC_bulkRNA-seq Patient_5 PBMC_bulkRNA-seq Patient
- GSM7899148 Heart_bulkRNA-seq_Patient_6 Heart_bulkRNA-seq_Patie…
- GSM7899149 Heart_bulkRNA-seq_Patient_7 Heart_bulkRNA-seq_Patie…
- GSM7899150 Heart_bulkRNA-seq_Patient_8 Heart_bulkRNA-seq_Patie…
- GSM7899151 Heart_bulkRNA-seq_Patient_9 Heart_bulkRNA-seq_Patie…
- GSM7899152 Heart_bulkRNA-seq_Patient_10 Heart_bulkRNA-seq_Patie…
- GSM7899153 Pooled scRNA-seq PBMC
- GSM7899154 CellPlex labeling PBMC
- GSM7899155 Pooled snRNA-seq Heart
- GSM7899156 CellPlex labeling Heart
- GSM7899157 Hashtag labeling Heart
- GSM8397021 Heart_2_bulkRNA-seq Patient_11 Heart_2_bulkRNA-seq Pat…
- GSM8397022 Heart_2_bulkRNA-seq Patient_12 Heart_2_bulkRNA-seq Pat…
- GSM8397023 Heart_2_bulkRNA-seq Patient_13 Heart_2_bulkRNA-seq Pat…
- GSM8397024 Heart_2_bulkRNA-seq Patient_14 Heart_2_bulkRNA-seq Pat…
- GSM8397025 Heart_2_bulkRNA-seq Patient_15 Heart_2_bulkRNA-seq Pat…
- GSM8397026 Heart_2_bulkRNA-seq Patient_16 Heart_2_bulkRNA-seq Pat…
- GSM8397027 Heart_2_bulkRNA-seq Patient_17 Heart_2_bulkRNA-seq Pat…
- GSM8397028 Heart_2_bulkRNA-seq Patient_18 Heart_2_bulkRNA-seq Pat…
- GSM8397029 Kidney_bulkRNA-seq_Patient_19 Kidney_bulkRNA-seq_Pati…
- GSM8397030 Kidney_bulkRNA-seq_Patient_20 Kidney_bulkRNA-seq_Pati…
- GSM8397031 Kidney_bulkRNA-seq_Patient_21 Kidney_bulkRNA-seq_Pati…
- GSM8397032 Kidney_bulkRNA-seq_Patient_22 Kidney_bulkRNA-seq_Pati…
- GSM8397033 Pooled scRNA-seq Heart_2
- GSM8397034 Pooled scRNA-seq Kidney
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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.