GEO series

Dual-transcriptomic analysis of human nasal transcriptome and microbiome reveals host-bacteria interactions associated with symptomatic respiratory infection

GSE309135 Homo sapiens (human) RNA-seq (gene expression) 202 samples Submitted 2025/12/06 Platform GPL15520Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 202 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: 202 samples: 202 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.

SuperSeries — this record groups several sub-series.

Summary (written by the submitters)

This SuperSeries is composed of the SubSeries listed below.

This dataset

Open GSE309135 in finder → Find more human RNA-seq datasets →

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 GSE309135_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 PRJNA1334194. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

202 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 202 sample titles: 202 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.

Samples in this study

GSM9261706 Covid infection, Asymptomatic, V1, Batch1, 1003-1-C, RNA_seq
GSM9261707 Covid infection, Symptomatic, V1, Batch1, 1001-3-A, RNA_seq
GSM9261708 Covid infection, Symptomatic, V1, Batch1, 1022-2-A, RNA_seq
GSM9261709 Covid infection, Symptomatic, V1, Batch1, 1025-1-A, RNA_seq
GSM9261710 Covid infection, Symptomatic, V1, Batch1, 1025-2-A, RNA_seq
GSM9261711 Covid infection, Symptomatic, V1, Batch1, 1028-2-A, RNA_seq
GSM9261712 Covid infection, Symptomatic, V1, Batch1, 1017-1-C, RNA_seq
GSM9261713 Covid infection, Asymptomatic, V1, Batch1, 1015-2-C, RNA_seq
GSM9261714 Covid infection, Symptomatic, V1, Batch1, 1029-2-C, RNA_seq
GSM9261715 Covid infection, Symptomatic, V1, Batch1, 1015-1-C, RNA_seq
GSM9261716 Covid infection, Symptomatic, V1, Batch1, 1008-3-A, RNA_seq
GSM9261717 Covid infection, Symptomatic, V1, Batch1, 1007-1-C, RNA_seq
GSM9261718 Covid infection, Asymptomatic, V1, Batch1, 1031-1-C, RNA_seq
GSM9261719 Covid infection, Asymptomatic, V1, Batch1, 1028-1-C, RNA_seq
GSM9261720 Covid infection, Symptomatic, V1, Batch1, 1008-1-C, RNA_seq
GSM9261721 Covid infection, Symptomatic, V1, Batch1, 1016-2-C, RNA_seq
GSM9261722 Covid infection, Symptomatic, V1, Batch1, 1034-1-C, RNA_seq
GSM9261723 Covid infection, Symptomatic, V1, Batch1, 1022-1-A, RNA_seq
GSM9261724 Covid infection, Symptomatic, V1, Batch1, 1016-1-C, RNA_seq
GSM9261725 Covid infection, Symptomatic, V1, Batch1, 1017-3-A, RNA_seq
GSM9261726 Covid infection, Asymptomatic, V1, Batch1, 1030-1-C, RNA_seq
GSM9261727 Covid infection, Symptomatic, V1, Batch1, 1014-3-C, RNA_seq
GSM9261728 Covid infection, Symptomatic, V1, Batch1, 1005-1-C, RNA_seq
GSM9261729 Covid infection, Symptomatic, V1, Batch1, 1032-1-C, RNA_seq
GSM9261730 Covid infection, Symptomatic, V1, Batch1, 1030-3-A, RNA_seq
GSM9261731 Covid infection, Symptomatic, V1, Batch1, 1036-1-C, RNA_seq
GSM9261732 Covid infection, Symptomatic, V1, Batch1, 1036-3-A, RNA_seq
GSM9261733 Covid infection, Symptomatic, V1, Batch1, 1037-1-A, RNA_seq
GSM9261734 Covid infection, Symptomatic, V1, Batch1, 1037-2-C, RNA_seq
GSM9261735 Covid infection, Symptomatic, V1, Batch1, 1038-2-A, RNA_seq
GSM9261736 Covid infection, Symptomatic, V1, Batch1, 1038-3-A, RNA_seq
GSM9261737 Covid infection, Symptomatic, V1, Batch1, 1039-1-A, RNA_seq
GSM9261738 Covid infection, Asymptomatic, V1, Batch1, 1039-2-C, RNA_seq
GSM9261739 Covid infection, Asymptomatic, V1, Batch1, 1002-2-C, RNA_seq
GSM9261740 Covid infection, Symptomatic, V1, Batch1, 1040-1-C, RNA_seq
GSM9261741 Covid infection, Symptomatic, V1, Batch1, 1041-1-A, RNA_seq
GSM9261742 Covid infection, Symptomatic, V1, Batch1, 1041-2-A, RNA_seq
GSM9261743 Covid infection, Asymptomatic, V1, Batch1, 1042-1-A, RNA_seq
GSM9261744 Covid infection, Symptomatic, V1, Batch1, 1042-2-C, RNA_seq
GSM9261745 Covid infection, Symptomatic, V1, Batch1, 1042-3-C, RNA_seq

+ 162 more — browse all 202 samples with per-sample file links →

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GSE213806 Transcriptome-wide mapping of RNA:protein interactions of PRPF8 and SNRNP200 (BRR2) with retinitis pigmentosa (RP) mutations by iCLIP 27 samples shares interactions
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Search all human 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.