Comparative transcriptomic profiling between two radiologic phenotypes in lungs from patients with pulmonary disease caused by Mycobacterium avium complex
RNA-seq (gene expression) · human · 42 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
- 42 samples: 42 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
- Radiologic phenotype-specific transcriptomic signatures in lung tissues from patients with Mycobacterium avium complex pulmonary diseaseEuropean journal of medical research · 2026
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 GSE270278_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 PRJNA1126117 and SRA study SRP514951. 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 42 sample titles: 42 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.
- GSM8338744 T-002-NL
- GSM8338745 T-003-NL
- GSM8338746 T-007-NL
- GSM8338747 T-009-F-NL
- GSM8338748 T-010-F-NL
- GSM8338749 T-016-F-NL
- GSM8338750 T-020-F-NL
- GSM8338751 T-022-F-NL
- GSM8338752 T-027-F-NL
- GSM8338753 T-029-F-NL
- GSM8338754 T-030-F-NL
- GSM8338755 T-034-F-NL
- GSM8338756 T-048-F-NL
- GSM8338757 T-051-F-NL
- GSM8338758 T-052-F-NL
- GSM8338759 T-058-F-NL
- GSM8338760 T-059-F-NL
- GSM8338761 T-060-F-NL
- GSM8338762 T-017-F-NL
- GSM8338763 T-061-F-NL
- GSM8338764 T-063-F-NL
- GSM8338765 T-009-F-NB
- GSM8338766 T-016-F-NB
- GSM8338767 T-020-F-NB
- GSM8338768 T-029-F-NB
- GSM8338769 T-030-F-NB
- GSM8338770 T-034-F-NB
- GSM8338771 T-051-F-NB
- GSM8338772 T-058-F-NB
- GSM8338773 T-059-F-NB
- GSM8338774 T-060-F-NB
- GSM8338775 T-063-F-NB
- GSM8338776 T-002-C
- GSM8338777 T-003-C
- GSM8338778 T-007-C
- GSM8338779 T-010-F-UC
- GSM8338780 T-022-F-UC
- GSM8338781 T-027-F-UC
- GSM8338782 T-048-F-UC
- GSM8338783 T-052-F-UC
+ 2 more — browse all 42 samples with per-sample file links →
- GSE288604 Whole blood transcriptomics characterize molecular phenotypes of pulmonary Mycobacterium avium complex disease 200 samples shares mycobacterium, phenotypes, pulmonary, complex
- GSE226099 Single-cell RNA sequencing analysis of the course of Mycobacterium avium complex pulmonary disease 21 samples shares mycobacterium, pulmonary, complex
- GSE226473 Single-cell RNA sequencing analysis according to the clinical course of Mycobacterium avium complex pulmonary disease 42 samples shares mycobacterium, pulmonary, complex
- GSE267774 Specific CD4+ T cell phenotypes associate with bacterial control in people who ‘resist’ infection with Mycobacterium tuberculosis 3076 samples shares mycobacterium, phenotypes
- GSE216985 A unique Mitochondrial Quality Control (MQC) mechanism reverses the phagosome maturation arrest caused by Mycobacterium tuberculosis 36 samples shares mycobacterium, caused
- GSE199345 Siglec-1−/FSClow alveolar macrophages exhibit pro-inflammatory phenotypes in chronic obstructive pulmonary disease 24 samples shares phenotypes, pulmonary
- GSE282384 Substrate Stiffness Dictates Unique Doxorubicin-induced Senescence-associated Secretory Phenotypes and Transcriptomic Signatures in Human Pulmonary Fibroblasts 12 samples shares phenotypes, pulmonary
- GSE295447 On target: Transcriptomic analysis of 12 human iPSC-derived cell phenotypes shows precision in an extensive pharmacological investigation [set 2] 840 samples shares phenotypes
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.