The U6 snRNA m6A methyltransferase METTL16 regulates SAM synthetase intron retention
Single-nucleus RNA-seq · human · 12 samples
- What it is
- Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
- Organism
- Homo sapiens (human)
- Samples
- 12 samples: 3 × siCtrl input vs 3 × siMETTL16 input vs 3 × siCtrl m6A IP vs 3 × siMETT16 m6A IPGroups 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 GSE90914_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA356403 and SRA study SRP094637. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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.
- GSM2417471 siCtrl input_rep1 siCtrl input
- GSM2417472 siCtrl input_rep2 siCtrl input
- GSM2417473 siCtrl input_rep3 siCtrl input
- GSM2417474 siMETTL16 input_rep1 siMETTL16 input
- GSM2417475 siMETTL16 input_rep2 siMETTL16 input
- GSM2417476 siMETTL16 input_rep3 siMETTL16 input
- GSM2417477 siCtrl m6A IP_rep1 siCtrl m6A IP
- GSM2417478 siCtrl m6A IP_rep2 siCtrl m6A IP
- GSM2417479 siCtrl m6A IP_rep3 siCtrl m6A IP
- GSM2417480 siMETT16 m6A IP_rep1 siMETT16 m6A IP
- GSM2417481 siMETT16 m6A IP_rep2 siMETT16 m6A IP
- GSM2417482 siMETT16 m6A IP_rep3 siMETT16 m6A IP
- GSE302781 snRNASeq of Metastatic Urothelial carcinoma samples 15 samples shares sam, snrna
- GSE274836 Two unrelated distal genes activated by a shared enhancer benefit from localizing inside the same small topological domain 97 samples shares sam
- GSE320155 scRNA‑seq of human intra‑hepatic CD4⁺ T cells reveals unique Treg transcriptional identities and two steady‑state tissue‑adaptation programs across healthy and HCC liver samples 60 samples shares sam
- GSE302214 scRNAseq and TCRseq of tumor infiltrating CD8 T cells from samples 22 samples shares sam
- GSE73801 DNA methylation data from CNS-PNETs and various other brain tumor samples 593 samples shares sam
- GSE72774 DNA methylation profiles of human blood samples from Caucasian subjects with Parkinson's disease 508 samples shares sam
- GSE319641 RNA-Seq profiling of pre- and on-treatment tumor samples from breast cancer patients enrolled in the NeoTRIP trial. 401 samples shares sam
- GSE72775 DNA methylation profiles of human blood samples from Hispanics and Caucasians 335 samples shares sam
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.