Multimodal Genome-wide Survey of Progressing and Non-progressing Breast Ductal Carcinoma In-Situ [RNA-seq]
RNA-seq (gene expression) · human · 123 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 123 samples
- 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
- Multimodal genome-wide survey of progressing and non-progressing breast ductal carcinoma in-situBreast cancer research : BCR · 2024
Read the full summary ↓
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 GSE281303_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1183345. Searching any of these in the dataset finder brings you back here.
The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Sample titles run Exp.Sample.16 … Exp.Sample.29 and carry no group information.
- GSM8618121 Exp.Sample.16
- GSM8618122 Exp.Sample.19
- GSM8618123 Exp.Sample.23
- GSM8618124 Exp.Sample.24
- GSM8618125 Exp.Sample.26
- GSM8618126 Exp.Sample.32
- GSM8618127 Exp.Sample.35
- GSM8618128 Exp.Sample.37
- GSM8618129 Exp.Sample.41
- GSM8618130 Exp.Sample.44
- GSM8618131 Exp.Sample.47
- GSM8618132 Exp.Sample.49
- GSM8618133 Exp.Sample.53
- GSM8618134 Exp.Sample.64
- GSM8618135 Exp.Sample.66
- GSM8618136 Exp.Sample.68
- GSM8618137 Exp.Sample.72
- GSM8618138 Exp.Sample.73
- GSM8618139 Exp.Sample.75
- GSM8618140 Exp.Sample.77
- GSM8618141 Exp.Sample.79
- GSM8618142 Exp.Sample.81
- GSM8618143 Exp.Sample.83
- GSM8618144 Exp.Sample.85
- GSM8618145 Exp.Sample.87
- GSM8618146 Exp.Sample.90
- GSM8618147 Exp.Sample.92
- GSM8618148 Exp.Sample.94
- GSM8618149 Exp.Sample.96
- GSM8618150 Exp.Sample.106
- GSM8618151 Exp.Sample.108
- GSM8618152 Exp.Sample.111
- GSM8618153 Exp.Sample.112
- GSM8618154 Exp.Sample.114
- GSM8618155 Exp.Sample.116
- GSM8618156 Exp.Sample.119
- GSM8618157 Exp.Sample.121
- GSM8618158 Exp.Sample.125
- GSM8618159 Exp.Sample.129
- GSM8618160 Exp.Sample.131
+ 83 more — browse all 123 samples with per-sample file links →
- GSE260842 Multimodal single cell analyses reveal mechanisms of perianal fistula in diverse Crohn’s disease [scRNA-seq] 34 samples shares multimodal, rna-seq
- GSE271456 Locus-specific and genome-wide analysis of adaptations to hypoxia in iPSC-derived endothelium from a population adapted to high altitude [RNA-Seq] 20 samples shares genome-wide, rna-seq
- GSE237281 Integrative Analysis of Genome-Wide Epigenetic and Transcriptomic Alterations Reveals Molecular Markers for Diagnosing Pediatric Obstructive Sleep Apnea in Black Females [RNA-Seq] 19 samples shares genome-wide, rna-seq
- GSE253903 High-Dimensional Single-Cell Multimodal Landscape of Human Carotid Atherosclerosis [scRNA-seq] 12 samples shares multimodal, rna-seq
- GSE301286 Multimodal antigenic escape to GPRC5D-targeted T-cell engagers in multiple myeloma [scRNA-seq] 4 samples shares multimodal, rna-seq
- GSE302399 Multimodal Transcriptomic Profiling of T Cell Responses to Triple-Negative Breast Cancer-Derived Exosomes 73 samples shares multimodal, breast
- GSE247519 Multimodal measurement of the transcriptome and proteome in single cells using nanoSPLITS 192 samples shares multimodal
- GSE269335 Single-cell multimodal profiling of monocytes reveals diverse phenotypes and alterations linked to cardiovascular disease risks 118 samples shares multimodal
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.