2008
DOI: 10.1093/bioinformatics/btn321
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A probe-density-based analysis method for array CGH data: simulation, normalization and centralization

Abstract: Source codes and.gures may be found at http://ntumaps.cgm.ntu.edu.tw/aCGH_supplementary.

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Cited by 22 publications
(9 citation statements)
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“…We considered whether this was due to the normalization protocol and subsequent segmentation analysis. Using technical replicates of LAU-Me275 DNA, we tested three independent normalization schemes, two of which were specifically developed for cancer genome analysis (see Materials and Methods ) and found that the methodology proposed by Chen and colleagues [15] was the most reproducible (Spearman correlation 0.96; see Fig. S2 ).…”
Section: Resultsmentioning
confidence: 99%
“…We considered whether this was due to the normalization protocol and subsequent segmentation analysis. Using technical replicates of LAU-Me275 DNA, we tested three independent normalization schemes, two of which were specifically developed for cancer genome analysis (see Materials and Methods ) and found that the methodology proposed by Chen and colleagues [15] was the most reproducible (Spearman correlation 0.96; see Fig. S2 ).…”
Section: Resultsmentioning
confidence: 99%
“…The log 2 ratio value of each averaged replicate probe was then modified in order to shift the main peak of each hybridization reaction to center around zero. The method, modified from Chen et al (11), was performed to further reduce the effects of hybridization efficiency variation on the data set.…”
Section: Methodsmentioning
confidence: 99%
“…A previous study indicated that the correlation of neighboring genomic intervals should be considered in the structural analysis of aCGH datasets [17], and the neighboring probes correlated with each other [3]. These findings indicate that the significant region would be more reliable for classification of experimental groups, which includes the correlated neighboring probes.…”
Section: Discussionmentioning
confidence: 79%