Iron regulatory protein 1 deficient mice exhibit hypospermatogenesis
RNA-seq (gene expression) · mouse · 11 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
- 11 samples: 4 × Irp1_KO vs 4 × WT vs 3 × Irp2_KOGroups 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.
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 GSE273580_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 PRJNA1142461 and SRA study SRP523353. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 11 samples.
How we read this: 3 replicated groups read from 11 sample titles; they account for 11 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.
- GSM8432634 Irp1_KO_1 Irp1_KO
- GSM8432635 Irp1_KO_2 Irp1_KO
- GSM8432636 Irp1_KO_6 Irp1_KO
- GSM8432637 Irp1_KO_7 Irp1_KO
- GSM8432638 Irp2_KO_1 Irp2_KO
- GSM8432639 Irp2_KO_2 Irp2_KO
- GSM8432640 Irp2_KO_3 Irp2_KO
- GSM8432641 WT_1 WT
- GSM8432642 WT_2 WT
- GSM8432643 WT_3 WT
- GSM8432644 WT_4 WT
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- GSE267584 Enhancer-driven gene regulatory networks reveal transcription factors governing T cell adaptation and differentiation in the tumor microenvironment. 22 samples shares regulatory, iron
- GSE292261 A dynamic gene regulatory code drives synaptic development of hippocampal granule cells [SS2] 576 samples shares regulatory
- GSE290574 Gene Regulatory Networks Orchestrating Oocyte Fate Bifurcation in Primordial Follicles Revealed by Single-Cell Transcriptomics 386 samples shares regulatory
- GSE288803 Proteasome inhibition alleviates proteinuria in Lmx1b knock-in mice with dysfunctional LIM domains 35 samples shares protein
- GSE217662 Decoding Trp53 regulatory program with knockout cell transcriptomic landscape analyses [scRNA-seq] 247 samples shares regulatory
- GSE270727 Analysis of striatal zinc finger protein (ZFP) repression of mutant Huntingtin (HTT) in the zQ175DN knock-in mouse model of Huntington's disease (bulk RNA-seq) 233 samples shares protein
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.