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pmid:26258045

Microarray-based optimization to detect genomic deletion mutations.

Eric J Belfield · Carly Brown · Xiangchao Gan · Caifu Jiang · Dilair Baban · Aziz Mithani · Richard Mott · Jiannis Ragoussis · Nicholas P Harberd

Genomics data · 2014 doi:10.1016/j.gdata.2014.04.005

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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title
Microarray-based optimization to detect genomic deletion mutations.
doi
10.1016/j.gdata.2014.04.005
pmid
26258045
authors array · 9 items
[0]
Eric J Belfield
[1]
Carly Brown
[2]
Xiangchao Gan
[3]
Caifu Jiang
[4]
Dilair Baban
[5]
Aziz Mithani
[6]
Richard Mott
[7]
Jiannis Ragoussis
[8]
Nicholas P Harberd
journal
Genomics data
year
2014
abstract
We performed array comparative genome hybridization (aCGH) analyses of five Arabidopsis thaliana mutants with genomic deletions ranging in size from 4 bp to > 5 kb. We used the Roche NimbleGen Arabidopsis CGH 3 × 720 K whole genome custom tiling array to optimize deletion detection. Details of the microarray design and hybridization data have been deposited at the NCBI GEO repository with accession number GSE55327.
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Microarray-based ultra-high resolution discovery of genomic deletion mutations
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The first step (performed by NimbleGen) uses a locally weighted polynomial regression (LOESS, see: http://www.obgyn.cam.ac.uk/genearray/loess-normalisation.htm) and is applied practically to all two-color arrays to adjust the signal intensity of each feature based on the X and Y coordinates of the probes on the array.
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