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Epigenetic and transcriptional alterations with Kmt2c and Kmt2d knockout

GSE264514 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 50 samples Submitted 2024/08/09 Platform GPL21103
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 50 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
50 samples: 16 conditions, mostly in triplicateGroups 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.
Summary (written by the submitters)
KMT2C and KMT2D are two of the most frequently mutated genes in bladder cancer and in histologically normal urothelium. In this study, we developed mouse models to investigate the molecular mechanism of Kmt2c/d loss in urothelial tumorigenesis.
This dataset
Download · which file do I need?

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.

1 · Just have a look

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.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE264514_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

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 peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1102881 and SRA study SRP503160. Searching any of these in the dataset finder brings you back here.

Study design
16 conditions, mostly in triplicate
RNAseq_WT_DMSO ×3 RNAseq_WT_MI503 ×3 RNAseq_dKO_DMSO ×3 RNAseq_dKO_MI503 ×3 ATACseq_WT ×3 ATACseq_dKO ×3 ChIPseq_H3K27ac_WT ×3 ChIPseq_H3K27ac_dKO ×3 +10 more

Supports a between-group comparison across 48 samples.

How we read this: 16 replicated groups read from 50 sample titles; they account for 48 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.

Samples in this study

+ 10 more — browse all 50 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.