RNA-seq data for MCF-7 cells with ER knockdown or GDC-9545 treatment
RNA-seq (gene expression) · human · 14 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
- 14 samples: 14 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.
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 GSE246364_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 PRJNA1032623 and SRA study SRP468667. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 14 sample titles: 14 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.
- GSM7867672 SAM24352870_MCF-7, mock, DMSO, rep1
- GSM7867673 SAM24352871_MCF-7, mock, DMSO, rep2
- GSM7867674 SAM24352872_MCF-7, mock, GDC-9545, rep1
- GSM7867675 SAM24352873_MCF-7, mock, GDC-9545, rep2
- GSM7867676 SAM24352874_MCF-7, mock, GDC-0927, rep1
- GSM7867677 SAM24352875_MCF-7, mock, GDC-0927, rep2
- GSM7867678 SAM24352876_MCF-7, siRNA, NTC, 48 hrs, rep1
- GSM7867679 SAM24352877_MCF-7, siRNA, NTC, 48 hrs, rep2
- GSM7867680 SAM24352878_MCF-7, siRNA ER, 48 hrs, rep1
- GSM7867681 SAM24352879_MCF-7, siRNA ER, 48 hrs, rep2
- GSM7867682 SAM24352880_MCF-7, siRNA, NTC, 72 hrs, rep1
- GSM7867683 SAM24352881_MCF-7, siRNA, NTC, 72 hrs, rep2
- GSM7867684 SAM24352882_MCF-7, siRNA ER, 72 hrs , rep1
- GSM7867685 SAM24352883_MCF-7, siRNA ER, 72 hrs, rep2
- GSE319641 RNA-Seq profiling of pre- and on-treatment tumor samples from breast cancer patients enrolled in the NeoTRIP trial. 401 samples shares treatment, rna-seq
- GSE175617 RNA-Seq Analysis of p53 Knockdown and Knock out Human Cancer cells 36 samples shares knockdown, rna-seq
- GSE278450 Glioblastoma scRNA-seq shows treatment-induced, immune-dependent increase in mesenchymal cancer cells and structural variants in distal neural stem cells 22 samples shares treatment, rna-seq
- GSE291124 snRNA-seq dataset of 17 treatment-naive human PDAC patient-derived tumors 17 samples shares treatment, rna-seq
- GSE180948 RNA-Seq based transcriptome analysis of colorectal cancer cells in response to lactate treatment 12 samples shares treatment, rna-seq
- GSE274335 RNA-Seq analysis LPCAT3 knockdown effect on primary human endometrial stromal cells(HESC). 6 samples shares knockdown, rna-seq
- GSE305389 Stromal and Endothelial Transcriptional Changes during Progression from MGUS to Myeloma and after Treatment Response [RNA-Seq] 25 samples shares treatment, rna-seq
- GSE338087 Patient tumor bulk RNA-seq analysis of the pre-axi-cel treatment tumor microenvironment in large B cell lymphoma 19 samples shares treatment, rna-seq
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.