Bulk RNA-seq profiling of p53-deficient mammary tumors driven by Runx1 and/or Rb1 loss
RNA-seq (gene expression) · mouse · 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
- Mus musculus (mouse)
- Samples
- 14 samples: 8 × Rb1/p53-null mammary tumor # vs 4 × p53/Runx1/Rb1-null mammary tumor # vs 2 × Runx1/p53-null mammary tumor #Groups 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 GSE316271_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 PRJNA1402139 and SRA study SRP661771. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 14 samples.
How we read this: 3 replicated groups read from 14 sample titles; they account for 14 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.
- GSM9448648 Runx1/p53-null mammary tumor #1 Runx1/p53-null mammary …
- GSM9448649 Runx1/p53-null mammary tumor #2 Runx1/p53-null mammary …
- GSM9448650 Rb1/p53-null mammary tumor #1 Rb1/p53-null mammary tu…
- GSM9448651 Rb1/p53-null mammary tumor #2 Rb1/p53-null mammary tu…
- GSM9448652 Rb1/p53-null mammary tumor #3 Rb1/p53-null mammary tu…
- GSM9448653 Rb1/p53-null mammary tumor #4 Rb1/p53-null mammary tu…
- GSM9448654 Rb1/p53-null mammary tumor #5 Rb1/p53-null mammary tu…
- GSM9448655 Rb1/p53-null mammary tumor #6 Rb1/p53-null mammary tu…
- GSM9448656 Rb1/p53-null mammary tumor #7 Rb1/p53-null mammary tu…
- GSM9448657 Rb1/p53-null mammary tumor #8 Rb1/p53-null mammary tu…
- GSM9448658 p53/Runx1/Rb1-null mammary tumor #1 p53/Runx1/Rb1-null mamm…
- GSM9448659 p53/Runx1/Rb1-null mammary tumor #2 p53/Runx1/Rb1-null mamm…
- GSM9448660 p53/Runx1/Rb1-null mammary tumor #3 p53/Runx1/Rb1-null mamm…
- GSM9448661 p53/Runx1/Rb1-null mammary tumor #5 p53/Runx1/Rb1-null mamm…
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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.