shRNA-mediated silencing of candidate pluripotency regulators in mouse epibladst stem cells
RNA-seq (gene expression) · mouse · 798 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
- 798 samples: 798 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 GSE199855_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 PRJNA821828 and SRA study SRP366912. 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 the first 400 of 798 sample titles: 400 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.
- GSM5988848 032916-10_12705_TRCN0000095235
- GSM5988849 032916-11_17129_TRCN0000068271
- GSM5988850 032916-12_22772_TRCN0000095250
- GSM5988851 032916-14_17354_TRCN0000072136
- GSM5988852 032916-15_18021_TRCN0000308369
- GSM5988853 032916-17_68750_TRCN0000367160
- GSM5988854 032916-18_12705_TRCN0000095237
- GSM5988855 032916-19_18612_TRCN0000055129
- GSM5988856 032916-20_22772_TRCN0000095249
- GSM5988857 032916-22_17354_TRCN0000072137
- GSM5988858 032916-23_18813_TRCN0000236753
- GSM5988859 032916-25_68750_TRCN0000376248
- GSM5988860 032916-27_18612_TRCN0000295466
- GSM5988861 032916-28_11568_TRCN0000031351
- GSM5988862 032916-30_17684_TRCN0000055104
- GSM5988863 032916-31_18813_TRCN0000236756
- GSM5988864 032916-32_21849_TRCN0000071366
- GSM5988865 032916-33_68750_TRCN0000376250
- GSM5988866 032916-35_18612_TRCN0000055130
- GSM5988867 032916-36_11568_TRCN0000307526
- GSM5988868 032916-38_17684_TRCN0000234123
- GSM5988869 032916-39_18813_TRCN0000236755
- GSM5988870 032916-40_22608_TRCN0000333885
- GSM5988871 032916-41_239102_TRCN0000234214
- GSM5988872 032916-44_11568_TRCN0000287914
- GSM5988873 032916-46_17684_TRCN0000257264
- GSM5988874 032916-47_20893_TRCN0000226078
- GSM5988875 032916-48_22608_TRCN0000333886
- GSM5988876 032916-49_239102_TRCN0000234213
- GSM5988877 032916-52_13017_TRCN0000109335
- GSM5988878 032916-55_20893_TRCN0000226076
- GSM5988879 032916-56_22608_TRCN0000334022
- GSM5988880 032916-57_12014_TRCN0000084329
- GSM5988881 032916-60_13017_TRCN0000295115
- GSM5988882 032916-63_20893_TRCN0000226075
- GSM5988883 032916-65_12014_TRCN0000432631
- GSM5988884 032916-67_20183_TRCN0000027052
- GSM5988885 032916-68_13017_TRCN0000295114
- GSM5988886 032916-69_16842_TRCN0000225790
- GSM5988887 032916-73_12014_TRCN0000436191
+ 758 more — browse all 798 samples with per-sample file links →
- GSE270036 Investigate the functions of core pluripotency transcription factors in embryonic stem cells 30 samples shares pluripotency, stem
- GSE274864 Epigenetic regulators of clonal hematopoiesis control CD8 T cell stemness during immunotherapy [RNA-seq] 17 samples shares regulators, stem
- GSE284988 Epigenetic profiling of hematopoietic stem cells identifies KDR and PU.1 as regulators of aging transcriptome and caloric restriction response 58 samples shares regulators, stem
- GSE274865 Epigenetic regulators of clonal hematopoiesis control CD8 T cell stemness during immunotherapy [CUT&Tag] 36 samples shares regulators, stem
- GSE274863 Epigenetic regulators of clonal hematopoiesis control CD8 T cell stemness during immunotherapy [ATAC-seq] 16 samples shares regulators, stem
- GSE243942 Spatio-temporal X-linked gene reactivation in the mouse germline reveals site-specific retention of epigenetic silencing [RNA-seq] 125 samples shares silencing
- GSE264615 Emerging cooperativity between Oct4 and Sox2 governs the pluripotency network in mouse early embryos [RNA-seq] 123 samples shares pluripotency
- GSE243373 Genome-wide 5mC and 5hmC patterns determine unique transcriptional signatures,regulators and exon inclusion of neural cell types in mouse brain [RNA-Seq] 15 samples shares regulators
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.