average-linkage pearson correlation hierarchical clustering  (Unigene)

Journal: BMC Bioinformatics

Article Title: Redefinition of Affymetrix probe sets by sequence overlap with cDNA microarray probes reduces cross-platform inconsistencies in cancer-associated gene expression measurements

doi: 10.1186/1471-2105-6-107

Figure Lengend Snippet: Sequence-overlapping probes give greater cross-platform concordance for the NCI-60 panel. ( A ) Pearson correlation coefficient was calculated for each gene between its expression values measured on the Affymetrix Hu6800 platforms and its expression values measured on the Stanford cDNA microarray across sixty cell lines of the NCI-60 panel. The figure shows the cumulative distribution of the Pearson correlation coefficients for all genes analyzed. The five different curves reflect the level of cross-platform consistency of probe sets with various levels of overlap between the two microarray platforms. Matched gene measurements across the two platforms showed higher correlation when greater numbers of probes in the Affymetrix probe sets overlapped the insert region of the cDNA clone. The highest correlation was attained when only those Affymetrix probes overlapping the insert-sequence of a given cDNA clone were retained. Measurements for which the probes targeted the same transcript as the cDNA clone, but did not overlap the clone sequence, showed the lowest correlation. ( B ), Pearson correlation coefficient was calculated across all genes for each matched sample pair profiled by the Affymetrix Hu6800 platform and by the Stanford cDNA microarray. The figure shows the cumulative distribution of the Pearson correlation coefficients for the sixty cell lines of the NCI-60 panel. Matched cell-line measurements showed identical stratification of correlation levels by feature-matching criteria.

Article Snippet: We also computed the average-linkage Pearson correlation hierarchical clustering of the combined datasets using both the Unigene and sequence-overlap mappings.

Techniques: Sequencing, Expressing, Microarray

Journal: BMC Bioinformatics

Article Title: Redefinition of Affymetrix probe sets by sequence overlap with cDNA microarray probes reduces cross-platform inconsistencies in cancer-associated gene expression measurements

doi: 10.1186/1471-2105-6-107

Figure Lengend Snippet: Conserved clustering pattern of the NCI-60 cell lines profiled using cDNA microarray and Affymetrix gene chips. Data was normalized as described (methods). Average linkage Pearson correlation hierarchical clustering was computed for each dataset. Cell line names are colored according to cancer type.

Article Snippet: We also computed the average-linkage Pearson correlation hierarchical clustering of the combined datasets using both the Unigene and sequence-overlap mappings.

Techniques: Microarray

Journal: BMC Bioinformatics

Article Title: Redefinition of Affymetrix probe sets by sequence overlap with cDNA microarray probes reduces cross-platform inconsistencies in cancer-associated gene expression measurements

doi: 10.1186/1471-2105-6-107

Figure Lengend Snippet: Increased efficiency of breast cancer subtype classification transfer from cDNA microarray to Affymetrix HuFL gene-chip tumor-profiles by sequence-overlapping probe measurements. Tumor samples profiled on the Affymetrix platform were classified according to their correlation with the set of subtype median-centroids derived from cDNA microarray measurements (see methods). The classified samples were then hierarchically clustered using Pearson correlation and average-linkage agglomeration. Affymetrix measurements matched to cDNA centroids by sequence-overlap of probe features produced more coherent classifications than those obtained in the original transfer (Sørlie), specifically, more coherent Luminal A and ERBB2+ subtype clusters.

Article Snippet: We also computed the average-linkage Pearson correlation hierarchical clustering of the combined datasets using both the Unigene and sequence-overlap mappings.

Techniques: Microarray, Sequencing, Derivative Assay, Produced

Journal: BMC Bioinformatics

Article Title: Redefinition of Affymetrix probe sets by sequence overlap with cDNA microarray probes reduces cross-platform inconsistencies in cancer-associated gene expression measurements

doi: 10.1186/1471-2105-6-107

Figure Lengend Snippet: Increased efficiency of breast cancer subtype classification transfer from cDNA microarray to Affymetrix HG-U95Av2 gene-chip tumor-profiles by sequence-overlapping probe measurements. Tumor samples profiled on the Affymetrix platform were classified according to their correlation with the set of subtype median-centroids derived from cDNA microarray measurements (see methods). The classified samples were then hierarchically clustered using Pearson correlation and average-linkage agglomeration. ( A ), Affymetrix measurements matched to the cDNA centroids by Unigene identifier. ( B ), Affymetrix measurements matched to cDNA centroids by sequence-overlap of probe features produced more coherent classifications. In particular, the large ERbB2+ subtype cluster (upper left) is mostly absent from the unigene-based classification. The significance of this cluster is supported by the observation that all tumors in this cluster for which Her-2 amplification was assessed by immunohistochemistry were designated positive.

Article Snippet: We also computed the average-linkage Pearson correlation hierarchical clustering of the combined datasets using both the Unigene and sequence-overlap mappings.

Techniques: Microarray, Sequencing, Derivative Assay, Produced, Amplification, Immunohistochemistry