Gene-expression profiling with reduced numbers of transcript measurements
A technology of genome-wide expression and transcripts, which is applied in the direction of analysis materials, measurement devices, biological tests, etc.
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Embodiment I
[0177] Example I: Identification of Cluster Centroid Landmark Transcripts and Building a Correlation Matrix
[0178] This example describes a method for identifying cluster centroid landmark transcripts with inferred relationships.
[0179] The 35,867 transcriptome-wide gene expression profiles generated with the Affymetrix U133 family of oligonucleotide microarrays were downloaded as .cel files from NCBI’s Gene Expression Omnibus (GEO) repository. For each probe set, the .cel files were preprocessed using MAS5 (Affymetrix) to generate mean difference values (ie expression levels). The expression level of each expression profile was then increased or decreased relative to the expression levels of 350 previously determined invariant probes whose expression levels collectively spanned the range of expression levels observed. The smallest common feature space in the dataset was determined to be 22,268 probe sets.
[0180] The quality of each profile was evaluated by referri...
Embodiment II
[0187] Example II: Determining an Appropriate Number of Cluster Centroid Landmark Transcripts
[0188] This example describes a method for selecting the number of cluster centroid landmark transcripts required to build a useful transcriptome-wide gene expression profile. The method uses a large collection of transcriptome-wide gene expression profiles generated from Affymetrix oligonucleotide microarrays from cultured human cells treated with small molecule disruptors, provided in the public connectivity map resource build02 (broadinstitute.org / cmap) . One use of connectivity graphs is to identify similarities between the biological effects of small molecule interferents. This can be done by examining the similarity of gene expression profiles produced by treatment of cells with these disruptors (Lamb et al., "The Connectivity Map: using gene-expression signatures to connect small molecules, genes and disease (Connectivity Map: Using gene-expression signatures to connect s...
Embodiment III
[0192] Example III: Platform-specific selection of cluster centroid landmark transcripts
[0193] This example describes a method for validating the performance of cluster centroid landmark transcripts on selected moderately multiplexed assay platforms. This example relates in particular to the measurement of expression levels of cluster centroid landmark transcripts derived from gene expression profiles established with Affymetrix microarrays using the LMF method of Peck et al., "A method for high-throughput gene expression signature analysis (using method for high-throughput gene expression marker analysis)” Genome Biology 7: R61 (2006). see image 3 .
[0194] Probe pairs were designed for the 1,000 cluster centroid landmark transcripts selected according to Example 1 (above) as described by Peck et al. The expression levels of these transcripts were measured by LMF in a collection of 384 biological samples including unperturbed cell lines, cell lines treated with b...
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