Transcriptome analysis of adult patients with severe Obstructive Sleep Apnea before and after CPAP treatment.
RNA-seq (gene expression) · human · 71 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
- 71 samples: 71 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.
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 GSE283703_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 PRJNA1195065 and SRA study SRP549816. 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 71 sample titles: 71 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.
- GSM8669956 Healthy1_AM_AMC6t1
- GSM8669957 Healthy2_AM_C16t3
- GSM8669958 Healthy3_AM_C22t3
- GSM8669959 Healthy4_AM_F2D12t1
- GSM8669960 Healthy5_AM_CB7t1
- GSM8669961 Healthy6_AM_CB14t1
- GSM8669962 Healthy7_AM_CB16t1
- GSM8669963 Healthy8_AM_AMC4t1
- GSM8669964 Healthy9_AM_AMC7t1
- GSM8669965 Healthy2_PM_C16t1
- GSM8669966 Healthy3_PM_C22t1
- GSM8669967 Healthy4_PM_F2D12t3
- GSM8669968 Healthy5_PM_CB7t3
- GSM8669969 Healthy6_PM_CB14t3
- GSM8669970 Healthy7_PM_CB16t3
- GSM8669971 Healthy8_PM_AMC4t3
- GSM8669972 Healthy9_PM_AMC7t3
- GSM8669973 Healthy10_PM_C12t1
- GSM8669974 OSA1_AM_D4t3
- GSM8669975 OSA2_AM_D5t3
- GSM8669976 OSA3_AM_D6t3
- GSM8669977 OSA4_AM_D8t3
- GSM8669978 OSA5_AM_D11t3
- GSM8669979 OSA6_AM_D15t3
- GSM8669980 OSA7_AM_D18t3
- GSM8669981 OSA8_AM_D25t3
- GSM8669982 OSA1_PM_D4t1
- GSM8669983 OSA2_PM_D5t1
- GSM8669984 OSA3_PM_D6t1
- GSM8669985 OSA4_PM_D8t1
- GSM8669986 OSA5_PM_D11t1
- GSM8669987 OSA6_PM_D15t1
- GSM8669988 OSA7_PM_D18t1
- GSM8669989 OSA8_PM_D25t1
- GSM8669990 OSA9_PM_D1t1
- GSM8669991 OSA1_Short_Treat_AM_T1_D4t1
- GSM8669992 OSA2_Short_Treat_AM_T1_D5t1
- GSM8669993 OSA3_Short_Treat_AM_T1_D6t1
- GSM8669994 OSA4_Short_Treat_AM_T1_D8t1
- GSM8669995 OSA5_Short_Treat_AM_T1_D11t1
+ 31 more — browse all 71 samples with per-sample file links →
- GSE290782 Benralizumab treatment in patients with severe asthma: A comparative analysis of T-cell gene expression profiles and identification of response-associated genes 34 samples shares treatment, severe
- GSE283522 The spatially informed mFISHseq assay resolves biomarker discordance and predicts treatment response in breast cancer 1254 samples shares treatment
- GSE301357 The airway transcriptome in type2 cytokine biomarker-high and -low severe asthma 129 samples shares severe
- GSE310252 Transcriptome-based classification of resected pancreatic ductal adenocarcinoma enhances prognostic modelling accuracy of overall survival following adjuvant treatment 118 samples shares treatment
- GSE334345 Exploratory investigation of changes in blood transcriptome following mepolizumab treatment for asthma 54 samples shares treatment
- GSE319641 RNA-Seq profiling of pre- and on-treatment tumor samples from breast cancer patients enrolled in the NeoTRIP trial. 401 samples shares treatment
- GSE254951 Impact of Hydroxycarbamide Treatment on the Whole Blood Transcriptome in Sickle Cell Disease 50 samples shares treatment
- GSE222196 Treatment of prostate cancer cell lines with Androgen Receptor and Receptor Tyrosine Kinase inhibitors 246 samples shares treatment
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.