GEO series

Programmable transcript-specific enrichment for single-cell sequencing enables profiling of rare cell states

GSE262355 Homo sapiens (human) Single-cell RNA-seq 23 samples Submitted 2024/03/26 Platform GPL18573Platform GPL24676Platform GPL24247Platform GPL34284

At a glance

Single-cell RNA-seq · human · 23 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: 23 samples: 22 distinct titles, 1 of them repeatedGroups 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: Transcript-specific enrichment enables profiling rare cell states via scRNA-seqbioRxiv : the preprint server for biology · 2024

Summary (written by the submitters)

The widespread application of single-cell genomics technologies has accelerated our understanding of the breadth and depth of heterogeneity of cell states across diverse contexts. As single-cell RNA sequencing (scRNA-seq) has been the most popular modality used for profiling, many populations have been described primarily based on specific marker transcript profiles compared to classical cytometry approaches relying on protein expression.

Read the full summary ↓

Additionally, many single cell studies require the isolation of nuclei from tissue, eliminating the ability to enrich learned rare cell states based on extranuclear protein markers. To address this limitation, we describe Programmable Enrichment via RNA Flow-FISH by sequencing (PERFF-seq), a scalable assay that enables single cell and single nuclei RNA-seq profiling from subpopulations of complex cellular mixtures solely defined by the abundance of RNA transcripts. Across vignettes of immune cell populations as well as nuclei from fresh frozen and formalin-fixed paraffin-embedded brain tissue, we demonstrate the enrichment of cell populations via RNA-based cytometry upstream of high-throughput scRNA-seq. Together, our approach provides a rational, programmable method for studying cell identities and transcriptional heterogeneity of rare populations identifiable by as few as one marker transcript, advancing the rational study of cellular diversity across fresh and archived tissue materials.

Published in

Transcript-specific enrichment enables profiling rare cell states via scRNA-seq

Abay T, Stickels RR, Takizawa MT et al. · bioRxiv : the preprint server for biology 2024 · PMID 38586040 · doi:10.1101/2024.03.27.587039

This dataset

Open GSE262355 in finder → Find more datasets →

Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE262355_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA1091573 and SRA study SRP497622. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38586040) ↗

Study design

22 distinct titles, 1 of them repeated

Loss of Y chromosome, Pool ×2

How we read this: Read from 23 sample titles: 22 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.

Samples in this study

GSM8163764 Development_A
GSM8163765 Development_B
GSM8163766 Development_C
GSM8163767 Development_D
GSM8163768 Development_E
GSM8163769 Development_F
GSM8163770 Development_G
GSM8163771 Development_H
GSM8163772 Development_I
GSM8163773 Development_J
GSM8163774 Development_K
GSM8163775 Development_L
GSM8163776 Pilot_Flex
GSM8163777 PERFFseq_TFPool
GSM8163778 PERFFseq_GBMPool
GSM8163779 PERFFseq_LogicPool
GSM8163780 PERFFseq_IL3RAminus
GSM8163781 PERFFseq_IL3RAplus
GSM8163782 PERFFseq_Mobpminus
GSM8163783 PERFFseq_Mobpplus
GSM8163784 PERFFseq_CD3Pool
GSM8607450 Loss of Y chromosome, Pool1
GSM8607451 Loss of Y chromosome, Pool2

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