A method for detecting and correcting feature misidentification on expression microarrays (2004)
Tu, I-Ping, Schaner, Marci, Diehn, Maximilian, Sikic, Branimir I, Brown, Patrick O, Botstein, David, ...
Abstract Background Much of the microarray data published at Stanford is based on mouse and human arrays produced under controlled and monitored conditions at the Brown and Botstein laboratories and...
The maximum of a function of a Markov chain and application to linkage analysis (1999)
One method of linkage analysis in humans is based on identity-by-descent of pairs of relatives who share a phenotype of interest (for example, a particular disease). We replace the convenient...
Leung, Suet Y., Chen, Xin, Chu, Kent M., Yuen, Siu T., Mathy, Jonathan, Ji, Jiafu, ...
We analyzed gene expression patterns in human gastric cancers by using cDNA microarrays representing ≈30,300 genes. Expression of PLA2G2A, a gene previously implicated as a modifier of the ApcMin/+...
Gene Expression Patterns in Ovarian Carcinomas
Schaner, Marci E., Ross, Douglas T., Ciaravino, Giuseppe, Sørlie, Therese, Troyanskaya, Olga, Diehn, Maximilian, ...
We used DNA microarrays to characterize the global gene expression patterns in surface epithelial cancers of the ovary. We identified groups of genes that distinguished the clear cell subtype from...
A method for detecting and correcting feature misidentification on expression microarrays
Tu, I-Ping, Schaner, Marci, Diehn, Maximilian, Sikic, Branimir I, Brown, Patrick O, Botstein, David, ...
Detection of Disease Genes by Use of Family Data. I. Likelihood-Based Theory
Whittemore, Alice S., Tu, I-Ping
We present a class of likelihood-based score statistics that accommodate genotypes of both unrelated individuals and families, thereby combining the advantages of case-control and family-based...
Detection of Disease Genes by Use of Family Data. II. Application to Nuclear Families
Tu, I-Ping, Balise, Raymond R., Whittemore, Alice S.
Two likelihood-based score statistics are used to detect association between a disease and a single diallelic polymorphism, on the basis of data from arbitrary types of nuclear families. The first...
Leung, Suet Y., Chen, Xin, Chu, Kent M., Yuen, Siu T., Mathy, Jonathan, Ji, Jiafu, ...
We analyzed gene expression patterns in human gastric cancers by using cDNA microarrays representing ≈30,300 genes. Expression of PLA2G2A, a gene previously implicated as a modifier of the ApcMin/+...
Gene Expression Patterns in Ovarian Carcinomas
Schaner, Marci E., Ross, Douglas T., Ciaravino, Giuseppe, Sørlie, Therese, Troyanskaya, Olga, Diehn, Maximilian, ...
We used DNA microarrays to characterize the global gene expression patterns in surface epithelial cancers of the ovary. We identified groups of genes that distinguished the clear cell subtype from...
A method for detecting and correcting feature misidentification on expression microarrays
Tu, I-Ping, Schaner, Marci, Diehn, Maximilian, Sikic, Branimir I, Brown, Patrick O, Botstein, David, ...
Detection of Disease Genes by Use of Family Data. I. Likelihood-Based Theory
Whittemore, Alice S., Tu, I-Ping
We present a class of likelihood-based score statistics that accommodate genotypes of both unrelated individuals and families, thereby combining the advantages of case-control and family-based...
Detection of Disease Genes by Use of Family Data. II. Application to Nuclear Families
Tu, I-Ping, Balise, Raymond R., Whittemore, Alice S.
Two likelihood-based score statistics are used to detect association between a disease and a single diallelic polymorphism, on the basis of data from arbitrary types of nuclear families. The first...