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2 protocols using agilent cgh analytics version 6

1

Genome-wide Copy Number Variation Analysis

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Array-based CGH was performed using an Agilent Human Whole Genome CGH 8 × 60 K microarray (Agilent Technologies). Labeling and hybridization were performed using protocols provided by the manufacturer (Cancer Sci. 2013; 104; 631-638). Briefly, 0.5 μg of test or reference DNA was digested with Alu I and Rsa I (Promega, Madison, WI) and purified with the QIAprep Spin Miniprep kit (QIAGEN). Test and reference DNA samples were labeled by random priming with either Cy3-dUTP or Cy5-dUTP using the Agilent Genomic DNA Labeling Kit PLUS (Agilent Technologies). Following the labeling reaction, individually labeled test and reference samples were combined and concentrated using Amicon Ultra-0.5 centrifugal filters (Millipore, Billerica, MA). After denaturing the probe and preannealing it to human Cot-1 DNA, samples were hybridized at 65°C and 20 rpm rotation for 24 hours in a DNA Microarray Hybridization Oven (Agilent Technologies). Samples were washed in wash buffer 1 at room temperature for 5 minutes and wash buffer 2 at 37°C for 1 minute using Agilent Oligo CGH washes. All slides were scanned on an Agilent DNA microarray scanner. Data were obtained using Agilent Feature Extraction Software 9 and analyzed with Agilent CGH Analytics Version 6.5 software using the ADM-2 statistical algorithms with 6.0 sensitivity thresholds.
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2

Genome-wide Copy Number Analysis

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aCGH was performed using SurePrint G3 Human CGH 4 × 180 K Microarrays (Agilent Technologies, Inc., Santa Clara, CA, USA). Labeling and hybridization were performed according to the manufacturer's instructions. The dual-colored fluorescence signals were scanned using the Agilent Microarray Scanner and translated to log10 ratios using Feature Extraction software (Ver-11.0.1.1, Agilent). Purified DNA was labeled with Cy5-dUTP following the Agilent Oligonucleotide Array-Based CGH for Genomic DNA Analysis protocol (Ver-7.3, Agilent). Data were obtained using Agilent Feature Extraction software 9 and analyzed with Agilent CGH Analytics Version 6.5 software, using the ADM-2 statistical algorithms with 6.0 sensitivity thresholds. Based on the aCGH data, the extracted signals were normalized to log2 ratios using the limma package [57 (link)]. We classified the segmented results into copy losses when the log2 ratios were lower than −0.25 and into copy gains when these were greater than 0.25.
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