BCL11A is required for normal erythropoiesis [RNA-seq_Sorted]
RNA-seq (gene expression) · human · 38 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)
- Samples
- 38 samples: 38 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
- BCL11A-deficient human erythropoiesis is impaired in vitro and after xenotransplantation into miceBlood advances · 2025
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 GSE283796_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 PRJNA1195591 and SRA study SRP550074. 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 38 sample titles: 38 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.
- GSM8672415 Dnr10_UT_D7_CD71_0_2003912
- GSM8672416 Dnr10_gCD33_D7_CD71_0_2003913
- GSM8672417 Dnr10_g1617_D7_CD71_0_2003914
- GSM8672418 Dnr10_g34_D7_CD71_0_2003917
- GSM8672419 Dnr10_UT_D7_ProE_0_2003918
- GSM8672420 Dnr10_gCD33_D7_ProE_0_2003919
- GSM8672421 Dnr10_g1617_D7_ProE_0_2003920
- GSM8672422 Dnr10_g34_D7_ProE_0_2003923
- GSM8672423 Dnr10_UT_D7_BasoE_0_2003924
- GSM8672424 Dnr10_gCD33_D7_BasoE_0_2003925
- GSM8672425 Dnr10_g1617_D7_BasoE_0_2003926
- GSM8672426 Dnr10_g34_D7_BasoE_0_2003929
- GSM8672427 Dnr11_UT_D7_CD71_1_2174371
- GSM8672428 Dnr11_gCD33_D7_CD71_2_2174379
- GSM8672429 Dnr11_g1617_D7_CD71_1_2174382
- GSM8672430 Dnr11_g34_D7_CD71_1_2174388
- GSM8672431 Dnr11_UT_D7_ProE_1_2174372
- GSM8672432 Dnr11_gCD33_D7_ProE_2_2174380
- GSM8672433 Dnr11_g1617_D7_ProE_1_2174383
- GSM8672434 Dnr11_g34_D7_ProE_1_2174389
- GSM8672435 Dnr11_UT_D7_BasoE_1_2174373
- GSM8672436 Dnr11_gCD33_D7_BasoE_2_2174381
- GSM8672437 Dnr11_g1617_D7_BasoE_1_2174384
- GSM8672438 Dnr11_g34_D7_BasoE_1_2174390
- GSM8672439 Dnr11_UT_D7_CD71_2_2174374
- GSM8672440 Dnr11_UT_D7_ProE_2_2174375
- GSM8672441 Dnr11_UT_D7_BasoE_2_2174376
- GSM8672442 DnrCL_gCD33_D7_CD71_0_2284550
- GSM8672443 DnrCL_g1617_D7_CD71_0_2284553
- GSM8672444 DnrCL_g34_D7_CD71_0_2284556
- GSM8672445 DnrCL_gCD33_D7_ProE_0_2284551
- GSM8672446 DnrCL_g1617_D7_ProE_0_2284554
- GSM8672447 DnrCL_g34_D7_ProE_0_2284557
- GSM8672448 DnrCL_gCD33_D7_BasoE_0_2284552
- GSM8672449 DnrCL_g1617_D7_BasoE_0_2284555
- GSM8672450 DnrCL_g34_D7_BasoE_0_2284558
- GSM8672451 Dnr10_UT_NO_D13_PolyE_0_2003930
- GSM8672452 Dnr10_UT_NO_D5_Bulk_0_2003906
- GSE327707 Sorted bulk RNA-seq profiling of human peripheral blood mononuclear cell populations across diverse in vitro immune stimuli 150 samples shares rna-seq, sorted
- GSE308103 Single-nucleus RNA-sequencing (snRNA-seq) analysis of normal lung tissues, precursor lung lesions and invasive lung adenocarcinomas 75 samples shares rna-seq, normal
- GSE292858 RNA-Seq analysis of tumor and matched normal samples from colorectal cancer patients. 73 samples shares rna-seq, normal
- GSE210077 Single nuclei RNA-sequencing of normal and diseased liver 40 samples shares rna-seq, normal
- GSE294300 Single-cell gene expression profiles of cells from primary colorectal cancer and adjacent normal tissue [scRNA-Seq] 36 samples shares rna-seq, normal
- GSE341753 Cohesin loading at regulatory elements shapes 3D genome folding during erythropoiesis [RNA-Seq] 12 samples shares erythropoiesis, rna-seq
- GSE319641 RNA-Seq profiling of pre- and on-treatment tumor samples from breast cancer patients enrolled in the NeoTRIP trial. 401 samples shares rna-seq
- GSE205154 Bulk RNA-Seq gene expression data for 289 primary and metastatic pancreatic ductal adenocarcinoma (PDAC) tumor samples from FFPE blocks. 289 samples shares rna-seq
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.