GEO series

Removing System Noise from Comparative Genomic Hybridization Data by Self-Self Analysis

GSE23682 Homo sapiens (human) Genome variation profiling by genome tiling array 3852 samples Submitted 2011/06/09 Platform GPL10815

At a glance

human · 3852 samples

Organism: Homo sapiens (human)
Samples: 3852 samples
Data you can get: A processed table (series matrix) and supplementary files from NCBI.

Summary (written by the submitters)

To minimize the distortion of genetic signal by system noise, we have explored the latter in an archive of hybridizations in which no genetic signal is expected. This archive is obtained by comparative genomic hybridization (CGH) of a reference sample in one channel to the same sample in the other channel, which we have termed ‘self-self’ data.

Read the full summary ↓

We show that these self-self hybridizations trap a variety of system noise inherent in sample-reference (test) data. Through singular value decomposition (SVD) of self-self data, we are able to determine the principal components of system noise. Assuming simple linear models of noise generation, we present evidence that the linear correction of test data with self-self data—which we call system normalization—reduces local and long-range correlations as well as improves signal-to-noise metrics, yet does not introduce detectable spurious signal.

This dataset

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Direct links to NCBI, 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.

All supplementary files ↗

3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE23682_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

Also filed as BioProject PRJNA130799. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 21658583) ↗

Samples in this study

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