PoreMeth2: decoding the evolution of methylome alterations with Nanopore sequencing.
DNA methylation · human · 33 samples
- What it is
- DNA methylationChemical marks on DNA that help switch genes on or off.
- Organism
- Homo sapiens (human)
- Samples
- 33 samples: 33 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.
- Paper
- PoreMeth2 for decoding the evolution of methylome alterations with nanopore sequencingGenome research · 2025
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 GSE277456_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: Look for beta-value tables or raw IDAT files among the supplementary files.
Also filed as BioProject PRJNA1162461. 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 33 sample titles: 33 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.
- GSM8522662 RNAseq Replicate 1 from AML patient AML2 after Relapse
- GSM8522663 RNAseq Replicate 2 from AML patient AML2 after Relapse
- GSM8522664 RNAseq Replicate 3 from AML patient AML2 after Relapse
- GSM8522665 RNAseq Replicate 1 from AML patient AML2 at initial diagnosis
- GSM8522666 RNAseq Replicate 2 from AML patient AML2 at initial diagnosis
- GSM8522667 RNAseq Replicate 3 from AML patient AML2 at initial diagnosis
- GSM8522668 RNAseq Replicate 1 from AML patient UD10 after Relapse
- GSM8522669 RNAseq Replicate 2 from AML patient UD10 after Relapse
- GSM8522670 RNAseq Replicate 3 from AML patient UD10 after Relapse
- GSM8522671 RNAseq Replicate 1 from AML patient UD10 at initial diagnosis
- GSM8522672 RNAseq Replicate 2 from AML patient UD10 at initial diagnosis
- GSM8522673 RNAseq Replicate 3 from AML patient UD10 at initial diagnosis
- GSM8522674 RNAseq Replicate 1 from AML patient UD5 after Relapse
- GSM8522675 RNAseq Replicate 2 from AML patient UD5 after Relapse
- GSM8522676 RNAseq Replicate 3 from AML patient UD5 after Relapse
- GSM8522677 RNAseq Replicate 1 from AML patient UD5 at initial diagnosis
- GSM8522678 RNAseq Replicate 2 from AML patient UD5 at initial diagnosis
- GSM8522679 RNAseq Replicate 1 from HPGC before GPCR treatment
- GSM8522680 RNAseq Replicate 2 from HPGC before GPCR treatment
- GSM8522681 RNAseq Replicate 3 from HPGC before GPCR treatment
- GSM8522682 RNAseq Replicate 4 from HPGC before GPCR treatment
- GSM8522683 RNAseq Replicate 1 from HPGC after GPCR treatment
- GSM8522684 RNAseq Replicate 2 from HPGC after GPCR treatment
- GSM8522685 RNAseq Replicate 3 from HPGC after GPCR treatment
- GSM8522686 RNAseq Replicate 4 from HPGC after GPCR treatment
- GSM8522687 DNA sequencing from HPGC before GPCR treatment
- GSM8522688 DNA sequencing from HPGC after GPCR treatment
- GSM8522689 DNA sequencing from AML patient AML2 after Relapse
- GSM8522690 DNA sequencing from AML patient AML2 at initial diagnosis
- GSM8522691 DNA sequencing from AML patient UD10 after Relapse
- GSM8522692 DNA sequencing from AML patient UD10 at initial diagnosis
- GSM8522693 DNA sequencing from AML patient UD5 after Relapse
- GSM8522694 DNA sequencing from AML patient UD5 at initial diagnosis
- GSE149250 Pancreatic Ductal Adenocarcinoma methylome analysis identifies differentially methylated genes in the Calcium signaling pathway and early methylation alterations. 15 samples shares alterations, methylome
- GSE337533 A Single-Cell Atlas of Transcriptional and Immunoglobulin Repertoire Evolution in Early B Cell Development 66 samples shares evolution
- GSE226741 Expression changes of ecDNA in colorectal epithelium-adenoma-adenocarcinoma evolution 30 samples shares evolution
- GSE269478 Single-cell multimodal profiling of monocytes reveals diverse phenotypes and alterations linked to cardiovascular disease risks [CITE-seq] 30 samples shares alterations
- GSE56046 Transcriptomics and methylomics of human monocytes [methylome] 1202 samples shares methylome
- GSE63818 The Transcriptome and DNA Methylome Landscapes of Human Primordial Germ Cells 364 samples shares methylome
- GSE290074 Evolutionarily divergent transcriptomic programs in ovarian folliculogenesis across mice, monkeys and humans [Human] 297 samples shares evolution
- GSE288172 Influence of NIPBL Knockdown-Induced Alterations in Cohesin Loop Extrusion on CTCF Loops, Enhancer-Promoter Connectivity, and PRC Domain Contacts During hESC Differentiation into Pancreatic Lineages 263 samples shares alterations
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.