ArrayQue: The comprehensive transcriptome data analysis tool

백동엽,유진호,이영복,조윤주,신지영,정호상,안준익,김양석 한국바이오칩학회 2012 BioChip Journal Vol.6 No.4

We have developed microarray analysis pipeline software for covering the entire process of transcriptome data analysis. This software, part of the Korea Toxicogenomics Integrated System (KOTIS), is freely distributed to users who upload their microarray data to the KOTIS database, which is operated under the server system of the National Institute of Toxicological Research (NITR). The uploaded microarray data can be downloaded by users through a web search interface within KOTIS and are used as input data of the analysis software. The software, which consists of four major analysis modules and one meta-analysis module, is connected to a gene-related annotation database through the web. Major analysis modules consist of (1) data import and preprocessing, (2) differentially expressed gene finding, (3) clustering analysis, and (4) classification analysis. A gene-related annotation database provides the biological meanings of the analysis results. A highly standardized analysis flow, from data import to differentially expressed gene finding, can be easily implemented using the interface series of a run wizard. The KOTIS system and analysis software are accessible at ttp://kotis.nitr.go.kr.

Robust gene selection methods using weighting schemes for microarray data analysis

Kang, Suyeon,Song, Jongwoo BioMed Central 2017 BMC bioinformatics Vol.18 No.1

<P><B>Background</B></P><P>A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates.</P><P><B>Results</B></P><P>We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays.</P><P><B>Conclusions</B></P><P>The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.</P><P><B>Electronic supplementary material</B></P><P>The online version of this article (10.1186/s12859-017-1810-x) contains supplementary material, which is available to authorized users.</P>

Gene Discovery Analysis from Mouse Embryonic Stem Cells Based on Time Course Microarray Data

서영주,조선아,심정희,육연주,유경현,김정희,박은영,노지연,이성호,양문희,정효석,박종훈 한국분자세포생물학회 2008 Molecules and cells Vol.26 No.4

An embryonic stem cell is a powerful tool for investigation of early development in vitro. The study of embryonic stem cell mediated neuronal differentiation allows for improved understanding of the mechanisms involved in embryonic neuronal development. We investigated expression profile changes using time course cDNA microarray to identify clues for the signaling network of neuronal differentiation. For the short time course microarray data, pattern analysis based on the quadratic regression method is an effective approach for identification and classification of a variety of expressed genes that have biological relevance. We studied the expression patterns, at each of 5 stages, after neuronal induction at the mRNA level of embryonic stem cells using the quadratic regression method for pattern analysis. As a result, a total of 316 genes (3.1%) including 166 (1.7%) informative genes in 8 possible expression patterns were identified by pattern analysis. Among the selected genes associated with neurological system, all three genes showing linearly increasing pattern over time, and one gene showing decreasing pattern over time, were verified by RT-PCR. Therefore, an increase in gene expression over time, in a linear pattern, may be associated with embryonic development. The genes: Tcfap2c, Ttr, Wnt3a, Btg2 and Foxk1 detected by pattern analysis, and verified by RT-PCR simultaneously, may be candidate markers associated with the development of the nervous system. Our study shows that pattern analysis, using the quadratic regression method, is very useful for investigation of time course cDNA microarray data. The pattern analysis used in this study has biological significance for the study of embryonic stem cells.

Functional Profiling of Human MeCP2 by Automated Data Comparison Analysis and Computerized Expression Pathway Modeling

김인주,이신해,정진우,박준형,유미애,김철민 대한의료정보학회 2016 Healthcare Informatics Research Vol.22 No.2

Objectives: Methyl-CpG binding protein 2 (MeCP2) is a ubiquitous epigenetic factor that represses gene expression by modifying chromatin. Mutations in the MeCP2 gene cause Rett syndrome, a progressive neurodevelopmental disorder. Recent studies also have shown that MeCP2 plays a role in carcinogenesis. Specifically, functional ablation of MeCP2 suppresses cell growth and leads to the proliferation of cancer cells. However, MeCP2’s function in adult tissues remains poorly understood. We utilized a weight matrix-based comparison software to identify transcription factor binding site (TFBS) of MeCP2-regulated genes, which were recognized by cDNA microarray analysis. Methods: MeCP2 expression was silenced using annealed siRNA in HEK293 cells, and then a cDNA microarray analysis was performed. Functional analysis was carried out, and transcriptional levels in target genes regulated by MeCP2 were investigated. TFBS analysis was done within genes selected by the cDNA microarray analysis, using a weight matrix-based program and the TRANSFAC 6.0 database. Results: Among the differentially expressed genes with a change in expression greater than two-fold, 189 genes were up-regulated and 91 genes were down-regulated. Genes related to apoptosis and cell proliferation (JUN, FOSL2, CYR61, SKIL, ATF3, BMABI, BMPR2, RERE, and FALZ) were highly up-regulated. Genes with anti-apoptotic and anti-proliferative functions (HNRPA0, HIS1, and FOXC1) were down-regulated. Using TFBS analysis within putative promoters of novel candidate target genes of MeCP2, disease-related transcription factors were identified. Conclusions: The present results provide insights into the new target genes regulated by MeCP2 under epigenetic control. This information will be valuable for further studies aimed at clarifying the pathogenesis of Rett syndrome and neoplastic diseases.

Laser Capture Microdissection을 이용한 유전자 발현 연구 (III) -생쥐 착상 부위 자궁 내강상피 조직에서 배아 병치 기간 동안 일어나는 유전자 발현에 관한 Microarray 분석-

윤세진,전은현,박창은,고정재,최동희,차광열,김세년,이경아,Yoon, Se-Jin,Jeon, Eun-Hyun,Park, Chang-Eun,Ko, Jung-Jae,Choi, Dong-Hee,Cha, Kwang-Yul,Kim, Se-Nyun,Lee, Kyung-Ah 대한생식의학회 2002 Clinical and Experimental Reproductive Medicine Vol.29 No.4

Object: The present study was accomplished to obtain a gene expression profile of the luminal epithelium during embryo apposition in comparison of implantation (1M) and interimplantation (INTER) sites. Material and Method: The mouse uterine luminal epithelium from IM and INTER sites were sampled on day 4.5 (Day of vaginal plug = day 0.5) by Laser Captured Microdissection (LCM). RNA was extracted from LCM captured epithelium, amplified, labeled and hybridized to microarrays. Results from microarray hybridization were analyzed by Significance Analysis of Microarrays (SAM) method. Differential expression of some genes was confirmed by LCM followed by RT-PCR. Results: Comparison of IM and INTER sites by SAM identified 73 genes most highly ranked at IM, while 13 genes at the INTER sites, within the estimated false discovery rate (FDR) of 0.163. Among 73 genes at IM, 20 were EST/unknown function, and the remain 53 were categorized to the structural, cell cycle, gene/protein expression, immune reaction, invasion, metabolism, oxidative stress, and signal transduction. Of the 24 structural genes, 14 were related especially to extracellular matrix and tissue remodeling. Meanwhile, among 13 genes up-regulated at INTER, 8 genes were EST/unknown function, and the rest 5 were related to metabolism, signal transduction, and gene/protein expression. Among these 58 (53+5) genes with known functions, 13 genes (22.4%) were related with $Ca^{2+}$ for their function. Conclusions: Results of the present study suggest that 1) active tissue remodeling is occurring at the IM sites during embryo apposition, 2) the INTER sites are relatively quiescent than IM sites, and 3) the $Ca^{2+}$ may be a crucial for apposition. Search for human homologue of those genes expressed in the mouse luminal epithelium during apposition will help to understand the implantation process and/or implantation failure in humans.

Analysis of Key Genes and Pathways Associated with Colorectal Cancer with Microarray Technology

Liu, Yan-Jun,Zhang, Shu,Hou, Kang,Li, Yun-Tao,Liu, Zhan,Ren, Hai-Liang,Luo, Dan,Li, Shi-Hong Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.3

Objective: Microarray data were analyzed to explore key genes and their functions in progression of colorectal cancer (CRC). Methods: Two microarray data sets were downloaded from Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were identified using corresponding packages of R. Functional enrichment analysis was performed with DAVID tools to uncover their biological functions. Results: 631 and 590 DEGs were obtained from the two data sets, respectively. A total of 32 common DEGs were then screened out with the rank product method. The significantly enriched GO terms included inflammatory response, response to wounding and response to drugs. Two interleukin-related domains were revealed in the domain analysis. KEGG pathway enrichment analysis showed that the PPAR signaling pathway and the renin-angiotensin system were enriched in the DEGs. Conclusions: Our study to systemically characterize gene expression changes in CRC with microarray technology revealed changes in a range of key genes, pathways and function modules. Their utility in diagnosis and treatment now require exploration.

Bayesian Survival Analysis of High-Dimensional Microarray Data for Mantle Cell Lymphoma Patients

Moslemi, Azam,Mahjub, Hossein,Saidijam, Massoud,Poorolajal, Jalal,Soltanian, Ali Reza Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.1

Background: Survival time of lymphoma patients can be estimated with the help of microarray technology. In this study, with the use of iterative Bayesian Model Averaging (BMA) method, survival time of Mantle Cell Lymphoma patients (MCL) was estimated and in reference to the findings, patients were divided into two high-risk and low-risk groups. Materials and Methods: In this study, gene expression data of MCL patients were used in order to select a subset of genes for survival analysis with microarray data, using the iterative BMA method. To evaluate the performance of the method, patients were divided into high-risk and low-risk based on their scores. Performance prediction was investigated using the log-rank test. The bioconductor package "iterativeBMAsurv" was applied with R statistical software for classification and survival analysis. Results: In this study, 25 genes associated with survival for MCL patients were identified across 132 selected models. The maximum likelihood estimate coefficients of the selected genes and the posterior probabilities of the selected models were obtained from training data. Using this method, patients could be separated into high-risk and low-risk groups with high significance (p<0.001). Conclusions: The iterative BMA algorithm has high precision and ability for survival analysis. This method is capable of identifying a few predictive variables associated with survival, among many variables in a set of microarray data. Therefore, it can be used as a low-cost diagnostic tool in clinical research.

Transcriptomic analysis of the heat stress response for a commercial baker’s yeast Saccharomyces cerevisiae

Duygu Varol,Vilda Purutçuoğlu,Remziye Yılmaz 한국유전학회 2018 Genes & Genomics Vol.40 No.2

The aim of this study is to explore the effects of heat stresses on global gene expression profiles and to identify the candidate genes for the heat stress response in commercial baker’s yeast (Saccharomyces cerevisiae) by using microarray technology and comparative statistical data analyses. The data from all hybridizations and array normalization were analyzed using the GeneSpringGX 12.1 (Agilent) and the R 2.15.2 program language. In the analysis, all required statistical methods were performed comparatively. For the normalization step, among alternatives, the RMA (Robust Microarray Analysis) results were used. To determine differentially expressed genes under heat stress treatments, the fold-change and the hypothesis testing approaches were executed under various cut-off values via different multiple testing procedures then the up/down regulated probes were functionally categorized via the PAMSAM clustering. The results of the analysis concluded that the transcriptome changes under the heat shock. Moreover, the temperature-shift stress treatments show that the number of differentially up-regulated genes among the heat shock proteins and transcription factors changed significantly. Finally, the change in temperature is one of the important environmental conditions affecting propagation and industrial application of baker’s yeast. This study statistically analyzes this affect via one-channel microarray data.

Identification of Egr1 Direct Target Genes in the Uterus by In Silico Analyses with Expression Profiles from mRNA Microarray Data

Seo, Bong-Jong,Son, Ji Won,Kim, Hye-Ryun,Hong, Seok-Ho,Song, Haengseok The Korean Society of Developmental Biology 2014 발생과 생식 Vol.18 No.1

Early growth response 1 (Egr1) is a zinc-finger transcription factor to direct second-wave gene expression leading to cell growth, differentiation and/or apoptosis. While it is well-known that Egr1 controls transcription of an array of targets in various cell types, downstream target gene(s) whose transcription is regulated by Egr1 in the uterus has not been identified yet. Thus, we have tried to identify a list of potential target genes of Egr1 in the uterus by performing multi-step in silico promoter analyses. Analyses of mRNA microarray data provided a cohort of genes (102 genes) which were differentially expressed (DEGs) in the uterus between Egr1(+/+) and Egr1(-/-) mice. In mice, the frequency of putative EGR1 binding sites (EBS) in the promoter of DEGs is significantly higher than that of randomly selected non-DEGs, although it is not correlated with expression levels of DEGs. Furthermore, EBS are considerably enriched within -500 bp of DEG's promoters. Comparative analyses for EBS of DEGs with the promoters of other species provided power to distinguish DEGs with higher probability as EGR1 direct target genes. Eleven EBS in the promoters of 9 genes among analyzed DEGs are conserved between various species including human. In conclusion, this study provides evidence that analyses of mRNA expression profiles followed by two-step in silico analyses could provide a list of putative Egr1 direct target genes in the uterus where any known direct target genes are yet reported for further functional studies.

Identification of Egr1 Direct Target Genes in the Uterus by In Silico Analyses with Expression Profiles from mRNA Microarray Data

Bong-jong Seo,Ji Won Son,Hye-Ryun Kim,Seok-Ho Hong,Haengseok Song 한국발생생물학회 2014 발생과 생식 Vol.18 No.1

Early growth response 1 (Egr1) is a zinc-finger transcription factor to direct second-wave gene expression leading to cell growth, differentiation and/or apoptosis. While it is well-known that Egr1 controls transcription of an array of targets in various cell types, downstream target gene(s) whose transcription is regulated by Egr1 in the uterus has not been identified yet. Thus, we have tried to identify a list of potential target genes of Egr1 in the uterus by performing multi-step in silico promoter analyses. Analyses of mRNA microarray data provided a cohort of genes (102 genes) which were differentially expressed (DEGs) in the uterus between Egr1(+/+) and Egr1(-/-) mice. In mice, the frequency of putative EGR1 binding sites (EBS) in the promoter of DEGs is significantly higher than that of randomly selected non-DEGs, although it is not correlated with expression levels of DEGs. Furthermore, EBS are considerably enriched within -500 bp of DEG’s promoters. Comparative analyses for EBS of DEGs with the promoters of other species provided power to distinguish DEGs with higher probability as EGR1 direct target genes. Eleven EBS in the promoters of 9 genes among analyzed DEGs are conserved between various species including human. In conclusion, this study provides evidence that analyses of mRNA expression profiles followed by two-step in silico analyses could provide a list of putative Egr1 direct target genes in the uterus where any known direct target genes are yet reported for further functional studies.