Effect of constitutive Grn KO on BMDM transcriptome [HEX000747_BMDM]
RNA-seq (gene expression) · mouse · 8 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
- 8 samples: 8 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 GSE272358_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 PRJNA1136510 and SRA study SRP520271. 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 8 sample titles: 8 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.
- GSM8399370 BMDM, WT, DMSO, replicate 1 [HEX000747_BMDM]
- GSM8399371 BMDM, WT, DMSO, replicate 2 [HEX000747_BMDM]
- GSM8399372 BMDM, WT, DMSO, replicate 3 [HEX000747_BMDM]
- GSM8399373 BMDM, WT, DMSO, replicate 4 [HEX000747_BMDM]
- GSM8399374 BMDM, GrnKO, DMSO, replicate 1 [HEX000747_BMDM]
- GSM8399375 BMDM, GrnKO, DMSO, replicate 2 [HEX000747_BMDM]
- GSM8399376 BMDM, GrnKO, DMSO, replicate 3 [HEX000747_BMDM]
- GSM8399377 BMDM, GrnKO, DMSO, replicate 4 [HEX000747_BMDM]
- GSE327962 Effects of CRISPR-mediated knockout of Mitf, Tfe3 and Tfeb on the transcriptome of mouse BMDMs from WT and Grn KO animals [hex001130] 16 samples shares bmdm
- GSE272363 Effect of lysosomal acidification on Grn knockout primary microglia transcriptome [HEX000747_MG] 16 samples shares hex000747
- GSE226704 Effect of COQ6 D316Y homozygosity on BMDM transcriptome 12 samples shares bmdm
- GSE289356 Effects of type I IFN signaling on gene expression of Mycobacterium tuberculosis-infected bone marrow-derived macrophages (BMDMs) 34 samples shares bmdm
- GSE281340 Effect of depletion of Med23 on gene expression during VSV infection of MEF and BMDM cells. 24 samples shares bmdm
- GSE252101 The effect of STING knockout on gene expression in DMXAA-induced BMDMs and BMDCs 24 samples shares bmdm
- GSE78849 Investigation of the effect of succinate and dimethyl malonate on murine bone-marrow derived macrophages (BMDMs) treated with or without LPS 21 samples shares bmdm
- GSE276416 Data Mining of IFNgamma-induced macrophage and Atherosclerotic Plaque Transcriptomes predicts a macrophage-specific role of STAT1 in human atherosclerosis [BMDM] 18 samples shares bmdm
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.