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(1) Effect of KLHL6 loss on the transcriptome in DLBCL upon NOTCH ligand stimulation. (2) Effect of KLHL6 and NOTCH2 loss on the transcriptome in DLBCL. (3) Effect of DLBCL-associated NOTCH2 mutants on the transcriptome in DLBCL.

GSE231624 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2024/05/03 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 48 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
Homo sapiens (human)
Topic
Diffuse large B-cell lymphomaThis series is part of our curated briefing on it.
Samples
48 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)
(1) Assessment of the transcriptional changes regulated by KLHL6 upon NOTCH ligand stimulation. Bulk RNA-seq in KLHL6 WT or KO U2932 cells was performed upon incubation with stromal OP9 cells stably expressing NOTCH ligand DLL1. (2) Assessment of the transcriptional changes regulated by the KLHL6-NOTCH2 axis in a xenotransplant model of DLBCL.
Read the full summary ↓
Bulk RNA-seq was performed in in KLHL6+/+NOTCH2+/+(WT), KLHL6-/-NOTCH2+/+(K6-KO), KLHL6+/+NOTCH2-/-(N2-KO), KLHL6-/-NOTCH2-/-(DKO) U2932 cells xenotranplanted in NSG mice trated with CHOP. (3) Assessment of the transcriptional changes regulated by the DLBCL-associated NOTCH2 mutants. Bulk RNA-seq was performed inU2932 cells stably expressing NOTCH2(WT), NOTCH2(S2156A), NOTCH2(R2400*) or NOTCH2(Q2140*).
This dataset
Open GSE231624 in finder → Find more human RNA-seq datasets → Diffuse large B-cell lymphoma landscape →
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.

Series matrix ↓
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 GSE231624_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA967024 and SRA study SRP435810. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
16 conditions, mostly in triplicate
U2932_KLHL6_WT_OP9_DLL1_0h_biol ×3 U2932_KLHL6_WT_OP9_DLL1_3h_biol ×3 U2932_KLHL6_WT_OP9_DLL1_8h_biol ×3 U2932_KLHL6_WT_OP9_DLL1_12h_biol ×3 U2932_KLHL6_KO_OP9_DLL1_0h_biol ×3 U2932_KLHL6_KO_OP9_DLL1_3h_biol ×3 U2932_KLHL6_KO_OP9_DLL1_8h_biol ×3 U2932_KLHL6_KO_OP9_DLL1_12h_biol ×3 +8 more

Supports a between-group comparison across 48 samples.

How we read this: 16 replicated groups read from 48 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

+ 8 more — browse all 48 samples with per-sample file links →

More Diffuse large B-cell lymphoma datasets

Search all human RNA-seq datasets in GEO →

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