Biomedical subjects

Jeffrey J Delrow

Publications and source records attributed to Jeffrey J Delrow.

4 recordsLinked to original sources

PubMed2005

Denoising array-based comparative genomic hybridization data using wavelets.

Array-based comparative genomic hybridization (array-CGH) provides a high-throughput, high-resolution method to measure relative changes in DNA copy number simultaneously at thousands of genomic loci. Typically, these measurements are reported and displayed linearly on chromosome maps, and gains and losses are detected as deviations from normal diploid cells. We propose that one may consider denoising the data to uncover the true copy number changes before drawing inferences on the patterns of aberrations in the samples. Nonparametric techniques are particularly suitable for data denoising as they do not impose a parametric model in finding structures in the data. In this paper, we employ wavelets to denoise the data as wavelets have sound theoretical properties and a fast computational algorithm, and are particularly well suited for handling the abrupt changes seen in array-CGH data. A simulation study shows that denoising data prior to testing can achieve greater power in detecting the aberrant spot than using the raw data without denoising. Finally, we illustrate the method on two array-CGH data sets.

Breast Neoplasms↗

PubMed2004

Array comparative genomic hybridization analysis of genomic alterations in breast cancer subtypes.

In this study, we performed high-resolution array comparative genomic hybridization with an array of 4153 bacterial artificial chromosome clones to assess copy number changes in 44 archival breast cancers. The tumors were flow sorted to exclude non-tumor DNA and increase our ability to detect gene copy number changes. In these tumors, losses were more frequent than gains, and gains in 1q and loss in 16q were the most frequent alterations. We compared gene copy number changes in the tumors based on histologic subtype and estrogen receptor (ER) status, i.e., ER-negative infiltrating ductal carcinoma, ER-positive infiltrating ductal carcinoma, and ER-positive infiltrating lobular carcinoma. We observed a consistent association between loss in regions of 5q and ER-negative infiltrating ductal carcinoma, as well as more frequent loss in 4p16, 8p23, 8p21, 10q25, and 17p11.2 in ER-negative infiltrating ductal carcinoma compared with ER-positive infiltrating ductal carcinoma (adjusted P values < or = 0.05). We also observed high-level amplifications in ER-negative infiltrating ductal carcinoma in regions of 8q24 and 17q12 encompassing the c-myc and c-erbB-2 genes and apparent homozygous deletions in 3p21, 5q33, 8p23, 8p21, 9q34, 16q24, and 19q13. ER-positive infiltrating ductal carcinoma showed a higher frequency of gain in 16p13 and loss in 16q21 than ER-negative infiltrating ductal carcinoma. Correlation analysis highlighted regions of change commonly seen together in ER-negative infiltrating ductal carcinoma. ER-positive infiltrating lobular carcinoma differed from ER-positive infiltrating ductal carcinoma in the frequency of gain in 1q and loss in 11q and showed high-level amplifications in 1q32, 8p23, 11q13, and 11q14. These results indicate that array comparative genomic hybridization can identify significant differences in the genomic alterations between subtypes of breast cancer.

Adult↗

PubMed2004

Hairy transcriptional repression targets and cofactor recruitment in Drosophila.

Members of the widely conserved Hairy/Enhancer of split family of basic Helix-Loop-Helix repressors are essential for proper Drosophila and vertebrate development and are misregulated in many cancers. While a major step forward in understanding the molecular mechanism(s) surrounding Hairy-mediated repression was made with the identification of Groucho, Drosophila C-terminal binding protein (dCtBP), and Drosophila silent information regulator 2 (dSir2) as Hairy transcriptional cofactors, the identity of Hairy target genes and the rules governing cofactor recruitment are relatively unknown. We have used the chromatin profiling method DamID to perform a global and systematic search for direct transcriptional targets for Drosophila Hairy and the genomic recruitment sites for three of its cofactors: Groucho, dCtBP, and dSir2. Each of the proteins was tethered to Escherichia coli DNA adenine methyltransferase, permitting methylation proximal to in vivo binding sites in both Drosophila Kc cells and early embryos. This approach identified 40 novel genomic targets for Hairy in Kc cells, as well as 155 loci recruiting Groucho, 107 loci recruiting dSir2, and wide genomic binding of dCtBP to 496 loci. We also adapted DamID profiling such that we could use tightly gated collections of embryos (2-6 h) and found 20 Hairy targets related to early embryogenesis. As expected of direct targets, all of the putative Hairy target genes tested show Hairy-dependent expression and have conserved consensus C-box-containing sequences that are directly bound by Hairy in vitro. The distribution of Hairy targets in both the Kc cell and embryo DamID experiments corresponds to Hairy binding sites in vivo on polytene chromosomes. Similarly, the distributions of loci recruiting each of Hairy's cofactors are detected as cofactor binding sites in vivo on polytene chromosomes. We have identified 59 putative transcriptional targets of Hairy. In addition to finding putative targets for Hairy in segmentation, we find groups of targets suggesting roles for Hairy in cell cycle, cell growth, and morphogenesis, processes that must be coordinately regulated with pattern formation. Examining the recruitment of Hairy's three characterized cofactors to their putative target genes revealed that cofactor recruitment is context-dependent. While Groucho is frequently considered to be the primary Hairy cofactor, we find here that it is associated with only a minority of Hairy targets. The majority of Hairy targets are associated with the presence of a combination of dCtBP and dSir2. Thus, the DamID chromatin profiling technique provides a systematic means of identifying transcriptional target genes and of obtaining a global view of cofactor recruitment requirements during development.

Adenine↗

PubMed2002

Improved background correction for spotted DNA microarrays.

Most microarray scanning software for glass spotted arrays provides estimates for the intensity for the "foreground" and "background" of two channels for every spot. The common approach in further analyzing such data is to first subtract the background from the foreground for each channel and to use the ratio of these two results as the estimate of the expression level. The resulting ratios are, after possible averaging over replicates, the usual inputs for further data analysis, such as clustering. If, with this background correction procedure, the foreground intensity was smaller than the background intensity for a channel, that spot (on that array) yields no usable data. In this paper it is argued that this preprocessing leads to estimates of the expression that have a much larger variance than needed when the expression levels are low.

Algorithms↗