GEO series

Personal Omics Profiling Reveals Dynamic Molecular Phenotypes and Actionable Medical Risks

GSE32874 Homo sapiens (human) Non-coding RNA profiling 25 samples Submitted 2012/03/16 Platform GPL9052Platform GPL10999

At a glance

Non-coding RNA profiling · human · 25 samples

What it is: Non-coding RNA profilingLevels of RNAs that do not code for proteins, such as miRNA or lncRNA.
Organism: Homo sapiens (human)
Samples: 25 samples
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)

We have determined the whole genome sequence of an individual at high accuracy and performed an integrated analysis of omics profiles over a 1.5 year period that included healthy and two virally infected states. Omics profiling of transcriptomes, proteomes, cytokines, metabolomes and autoantibodyomes from blood components have revealed extensive, dynamic and broad changes in diverse molecular components and biological pathways that occurred during healthy and disease states.

Read the full summary ↓

Many changes were associated with allele- and edit-specific expression at the RNA and protein levels, which may contribute to personalized responses. Importantly, genomic information was also used to predict medical risks, including Type II Diabetes (T2D), whose onset was observed during the course of our study using standard clinical tests and molecular profiles, and whose disease progression was monitored and subsequently partially managed. Our study demonstrates that longitudinal personal omics profiling can relate genomic information to global functional omics activity for physiological and medical interpretation of healthy and disease states.

This dataset

Open GSE32874 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 GSE32874_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 ↗

Also filed as BioProject PRJNA154385 and SRA study SRP008976. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 22424236) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 25 more — browse all 25 samples with per-sample file links →

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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.