• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.205-213
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• 2007

In this paper, the normal mixture model subjected to general linear restriction for component-means based on linear regression is proposed, and its fitting method by EM algorithm and Lagrange multiplier is provided. This model is applied to gene clustering of microarray expression data, which demonstrates it has very good performances for real data set. This model also allows to obtain the clusters that an analyst wants to find out in the fashion that the hypothesis for component-means is represented by the design matrices and the linear restriction matrices.

• Communications for Statistical Applications and Methods
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• 제14권3호
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• pp.687-698
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• 2007

A normal mixture model with which dependence between classes is incorporated is proposed in order to detect differentially expressed genes. Gene clustering approaches suffer from the high dimensional column of microarray expression data matrix which leads to the over-fit problem. Various methods are proposed to solve the problem. In this paper, use of simple averaging data within each class is proposed to overcome the various problems due to high dimensionality when the normal mixture model is fitted. Some experiments through simulated data set and real data set show its availability in actuality.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2004년도 The 3rd Annual Conference for The Korean Society for Bioinformatics Association of Asian Societies for Bioinformatics 2004 Symposium
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• pp.272-278
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• 2004

Recently, Pepe et al. (2003) employed the receiver operating characteristic (ROC) approach to rank candidate genes from a microarray experiment that can be used for the biomarker development with the ultimate purpose of the population screening of a cancer, In the cancer microarray experiment based on n patients the researcher often wants to compare the tumor tissue with the normal tissue within the same individual using a common reference RNA. This design is referred to as a reference design or an indirect design. Ideally, this experiment produces n pairs of microarray data, where each pair consists of two sets of microarray data resulting from reference versus normal tissue and reference versus tumor tissue hybridizations. However, for certain individuals either normal tissue or tumor tissue is not large enough for the experimenter to extract enough RNA for conducting the microarray experiment, hence there are missing values either in the normal or tumor tissue data. Practically, we have $n_1$ pairs of complete observations, $n_2$ 'normal only' and $n_3$ 'tumor only' data for the microarray experiment with n patients, where n=$n_1$+$n_2$+$n_3$. We refer to this data set as a mixed data set, as it contains a mix of fully observed and partially observed pair data. This mixed data set was actually observed in the microarray experiment based on human tissues, where human tissues were obtained during the surgical operations of cancer patients. Pepe et al. (2003) provide the rationale of using ROC approach based on two independent samples for ranking candidate gene instead of using t or Mann -Whitney statistics. We first modify ROC approach of ranking genes to a paired data set and further extend it to a mixed data set by taking a weighted average of two ROC values obtained by the paired data set and two independent data sets.

• Journal of Genetic Medicine
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• 제15권2호
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• pp.49-54
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• 2018

Nuchal translucency is an important indicator of an aneuploid fetus in prenatal diagnostics. Previously, only the presence of aneuploid could be confirmed by conventional karyotyping of fetuses with thick nuchal translucency. With the development of genetic diagnostic techniques, however, it has been reported that subtle variations not detectable by conventional karyo-typing might occur in cases of pathologic clinical syndrome in euploid fetuses. One of the newer, high-resolution genetic methods in the prenatal setting is chromosomal microarray. The possible association between nuchal translucency thickness with normal karyotype and submicroscopic chromosomal abnormalities detectable by microarray has been studied. How and when to apply microarray in clinical practice, however, is still debated. This article reviews the current studies on the clinical application of microarray in cases of increased nuchal translucency with normal karyotype for prenatal diagnosis.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.169-182
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• 2007

Receive operating characteristic (ROC) approach can be employed to rank candidate genes from a microarray experiment, in particular, for the biomarker development with the purpose of population screening of a cancer. In the cancer microarray experiment based on n patients the researcher often wants to compare the tumor tissue with the normal tissue within the same individual using a common reference RNA. Ideally, this experiment produces n pairs of microarray data. However, it is often the case that there are missing values either in the normal or tumor tissue data. Practically, we have $n_1$ pairs of complete observations, $n_2$ "normal only" and $n_3$ "tumor only" data for the microarray. We refer to this data set as a mixed data set. We develop a ROC approach on the mixed data set to rank candidate genes for the biomarker development for the colorectal cancer screening. It turns out that the correlation between two ranks in terms of ROC and t statistics based on the top 50 genes of ROC rank is less than 0.6. This result indicates that employing a right approach of ranking candidate genes for the biomarker development is important for the allocation of resources.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2006년도 Principles and Practice of Microarray for Biomedical Researchers
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• pp.98-107
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• 2006

Chromosomal copy number changes (aneuploidies) are common in human populations. The extra chromosome can affect gene expression by whole-genome level. By gene expression microarray analysis, we want to find aberrant gene expression due to aneuploidies in Klinefelter (+X) and Down syndrome (+21). We have analyzed the inactivation status of X-linked genes in Klinefelter Syndrome (KS) by using X-linked cDNA microarray and cSNP analysis. We analyzed the expression of 190 X-linked genes by cDNA microarray from the lymphocytes of five KS patients and five females (XX) with normal males (XY) controls. cDNA microarray experiments and cSNP analysis showed the differentially expressed genes were similar between KS and XX cases. To analyze the differential gene expressions in Down Syndrome (DS), Amniotic Fluid (AF)cells were collected from 12 pregnancies at $16{\sim}18$ weeks of gestation in DS (n=6) and normal (n=6) subjects. We also analysis AF cells for a DNA microarray system and compared the chip data with two dimensional protein gel analysis of amniotic fluid. Our data may provide the basis for a more systematic identification of biological markers of fetal DS, thus leading to an improved understanding of pathogenesis for fetal DS.

• Genomics & Informatics
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• 제2권1호
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• pp.30-35
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• 2004

To investigate the XIST gene expression and its effect in a Klinefelter's patient, we used Klinefelter's syndrome (XXY) patient with azoospermia and also used a normal male (XY) and a normal female (XX) as the control, We were performed cytogenetic analysis, Y chromosomal microdeletion assay (Yq), semi-quantitative RT-PCR, and the Northern blot for Klinefelter's syndrome (KS) patient, a female and a male control, We extracted total RNA from the KS patient, and from the normal cells of the female and male control subjects using the RNA prep kit (Qiagen), cDNA microarray contained 218 human X chromosome-specific genes was fabricated. Each total RNA was reverse transcribed to the first strand cDNA and was labeled with Cy-3 and Cy-5 fluorescein, The microarray was scanned by ScanArray 4000XL system. XIST transcripts were detected from the Klinefelters patient and the female by RT-PCR and Northern blot analysis, but not from the normal male, In the cDNA microarray experiment, we found 24 genes and 14 genes are highly expressed in KS more than the normal male and females, respectively. We concluded that highly expressed genes in KS may be a resulted of the abnormal X inactivation mechanism.

• Journal of the Korean Data and Information Science Society
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• 제22권5호
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• pp.967-976
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• 2011

The Box-Cox transformation is a well known family of power transformations that brings a set of data into agreement with the normality assumption of the residuals and hence the response variable of a postulated model in regression analysis. Normalization (studentization) of the regressors is a common practice in analyzing microarray data. Here, we implement Box-Cox transformation in normalizing regressors in microarray data. Pridictabilty of the model can be improved using data transformation compared to studentization.

• Molecules and Cells
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• 제39권4호
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• pp.337-344
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• 2016

Intravenous administration of mesenchymal stem cells (IV-MSC) protects the ischemic rat brain in a stroke model, but the molecular mechanism underlying its therapeutic effect is unclear. We compared genomic profiles using the mRNA microarray technique in a rodent stroke model. Rats were treated with $1{\times}10^6$ IV-MSC or saline (sham group) 2 h after transient middle cerebral artery occlusion (MCAo). mRNA microarray was conducted 72 h after MCAo using brain tissue from normal rats (normal group) and the sham and MSC groups. Predicted pathway analysis was performed in differentially expressed genes (DEGs), and functional tests and immunohistochemistry for inflammation-related proteins were performed. We identified 857 DEGs between the sham and normal groups, with the majority of them (88.7%) upregulated in sham group. Predicted pathway analysis revealed that cerebral ischemia activated 10 signaling pathways mainly related to inflammation and cell cycle. IV-MSC attenuated the numbers of dysregulated genes in cerebral ischemia (118 DEGs between the MSC and normal groups). In addition, a total of 218 transcripts were differentially expressed between the MSC and sham groups, and most of them (175/218 DEGs, 80.2%) were downregulated in the MSC group. IV-MSC reduced the number of Iba-$1^+$ cells in the peri-infarct area, reduced the overall infarct size, and improved functional deficits in MCAo rats. In conclusion, transcriptome analysis revealed that IV-MSC attenuated postischemic genomic alterations in the ischemic brain. Amelioration of dysregulated inflammation- and cell cycle-related gene expression in the host brain is one of the molecular mechanisms of IV-MSC therapy for cerebral ischemia.

• Journal of Genetic Medicine
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• 제17권1호
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• pp.21-26
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• 2020

Purpose: To evaluate the additive value of prenatal chromosomal microarray analysis (CMA) in assessing increased nuchal translucency (NT) (≥3.5 mm) with normal karyotype and the possibility of detecting clinically significant genomic imbalance, based on specific indications. Materials and Methods: Invasive samples from 494 pregnancies with NT ≥3.5 mm, obtained from the Research Center of Fertility & Genetics of Hamchoon Women's Clinic between January 2019 and February 2020, were included in this study and CMA was performed in addition to a standard karyotype. Results: In total, 494 cases were subjected to both karyotype and CMA analyses. Among these, 199 cases of aneuploidy were excluded. CMA was performed on the remaining 295 cases (59.7%), which showed normal (231/295, 78.3%) or non-significant copy number variation (CNV), such as benign CNV or variants of uncertain clinical significance likely benign (53/295, 18.0%). Clinically significant CNVs were detected in 11 cases (11/295, 3.7%). Conclusion: Prenatal CMA resulted in a 3% to 4% higher CNV diagnosis rate in fetuses exhibiting increased NT (≥3.5 mm) without other ultrasound detected anomalies and normal karyotype. Therefore, we suggest using high resolution, non- targeting CMA to provide valuable additional information for prenatal diagnosis. Further, we recommend that a genetics specialist should be consulted to interpret the information appropriately and provide counseling and follow-up services after prenatal CMA.