Mohutný rozvoj molekulárně biologických metod v posledních deseti letech je charakterizován produkcí velkého množství dat. Nejinak je tomu i v případě technologie DNA mikročipů, která umožňuje v jednom experimentu sledovat expresi desítek tisíc genů najednou. Kvantum získaných experimentálních dat je však pro relevantní medicínské závěry nutné vhodně analyzovat a interpretovat. Tento článek je věnován statistickým metodám, které lze pro hodnocení dat získaných z DNA mikročipů použít. Tyto metody lze rozdělit do tří velkých skupin: shlukovací metody, metody pro identifikaci rozdílně exprimovaných genů a klasifikační metody. Shlukovací metody slouží k nalezení homogenních skupin pacientů s podobným expresním profilem nebo skupin genů s podobným chováním, metody pro identifikaci rozdílně exprimovan ých genů hledají geny specifické svojí aktivitou pro určitou biologickou tkáň, zatímco klasifikační metody slouží k nalezení diskriminačního pravidla pro přesnou diagnostiku nových pacientů do jedné z definovaných skupin.
Last decade led to massive progress in the molecular biology methods which was accompanied by the production of large amount of data. This is also the case of the gene expression microarray technology that makes it feasible to study thousands of genes simultaneously. However, for relevant medical inference there is the need for appropriate evaluation and interpretation of this large quantity of experimental data. This paper is dedicated to statistical methods that can be used for the evaluation of gene expression data. These methods can be split into three main categories: clustering methods, methods for identification of differentially expressed genes and classification techniques. Clustering methods can be used for finding of homogenous groups of patients or genes with similar expression profile, methods for identification of differentially expressed genes find genes specific for activity of certain biological tissue while classification techniques are used for setting up a discrimination rule for precise diagnostics of newly diagnosed patients to one of the previously defined classes.
- MeSH
- Discriminant Analysis MeSH
- Gene Expression genetics MeSH
- Financing, Organized MeSH
- Humans MeSH
- Oligonucleotide Array Sequence Analysis methods statistics & numerical data utilization MeSH
- Cluster Analysis MeSH
- Models, Statistical MeSH
- Statistics as Topic MeSH
- Models, Theoretical MeSH
- Check Tag
- Humans MeSH
- Publication type
- Review MeSH
Background: Microarray technologies are used to measure the simultaneous expression of a certain set of thousands of genes based on ribonucleic acid (RNA) obtained from a biological sample. We are interested in several statistical analyses such as 1) finding differentially expressed genes between or among several experimental groups, 2) finding a small number of genes allowing for the correct classification of a sample in a certain group, and 3) finding relations among genes. Objectives: Gene expression data are high dimensional, and this fact complicates their analysis because we are able to perform only a few samples (e.g. the peripheral blood from a limited number of patients) for a certain set of thousands of genes. The main purpose of this paper is to present the shrinkage estimator and show its application in different statistical analyses. Methods: The shrinkage approach relates to the shift of a certain value of a classic estimator towards a certain value of a specified target estimator. More precisely, the shrinkage estimator is the weighted average of the classic estimator and the target estimator. Results: The benefit of the shrinkage estimator is that it improves the mean squared error (MSE) as compared to a classic estimator. The MSE combines the measure of an estimator’s bias away from its true unknown value and the measure of the estimator’s variability. The shrinkage estimator is a biased estimator but has a lower variability. Conclusions: The shrinkage estimator can be considered as a promising estimator for analyzing high dimensional gene expression data.
- MeSH
- Gene Expression * genetics MeSH
- Humans MeSH
- Microarray Analysis * methods statistics & numerical data MeSH
- RNA * genetics MeSH
- Models, Statistical MeSH
- Check Tag
- Humans MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
Understanding the control of gene expression is critical for our understanding of the relationship between genotype and phenotype. The need for reliable assessment of transcript abundance in biological samples has driven scientists to develop novel technologies such as DNA microarray and RNA-Seq to meet this demand. This review focuses on comparing the two most useful methods for whole transcriptome gene expression profiling. Microarrays are reliable and more cost effective than RNA-Seq for gene expression profiling in model organisms. RNA-Seq will eventually be used more routinely than microarray, but right now the techniques can be complementary to each other. Microarrays will not become obsolete but might be relegated to only a few uses. RNA-Seq clearly has a bright future in bioinformatic data collection.
Wiley series in probability and statistics
1st ed. xx, 320 s.
- MeSH
- Early Diagnosis MeSH
- Molecular Diagnostic Techniques MeSH
- Gene Expression MeSH
- Genome, Human MeSH
- Humans MeSH
- RNA, Messenger analysis MeSH
- MicroRNAs analysis MeSH
- Polymerase Chain Reaction MeSH
- Oligonucleotide Array Sequence Analysis MeSH
- Gene Expression Profiling MeSH
- Check Tag
- Humans MeSH
- Publication type
- Book Review MeSH
... VOLUME 123 | SUPPLEMENT 5 | OCTOBER 2013 | www.laryngoscope.com -- ORIGINAL REPORT -- DIFFERENTIAL GENE ... ... EXPRESSION IN CHOLESTEATOMA BY DNA CHIP -- ANALYSIS -- S1 INTRODUCTION -- S2 MATERIALS AND METHODS - ... ... - Tissue Samples and Study Design -- RNA Isolation -- 3D-Gene Human Oligo Chip 25k Assay -- Statistical ... ... Analysis and Gene Ontology Analysis -- Real Time qRT-PCR -- IHC -- S4 RESULTS -- . 3D-Gene DNA Chip ...
The laryngoscope, ISSN 0023-852X Volume 123, supplementum 5 , October 2013
21 stran : ilustrace, tabulky ; 28 cm
- MeSH
- Genome-Wide Association Study MeSH
- Cholesteatoma, Middle Ear MeSH
- Gene Expression MeSH
- Prospective Studies MeSH
- Oligonucleotide Array Sequence Analysis MeSH
- Conspectus
- Patologie. Klinická medicína
- NML Fields
- otorinolaryngologie
- genetika, lékařská genetika
- NML Publication type
- studie
BACKGROUND: The full maturational capability of mammalian oocytes is accompanied by nuclear and cytoplasmic modifications, which are associated with proliferation and differentiation of surrounding cumulus cells. These events are regulated on molecular level by the expression of target genes involved in signal transduction pathways crucial for folliculogenesis and oogenesis. Transforming growth factor beta signaling includes several molecules that are involved in the regulation of oogenesis and embryo growth, including bone morphogenetic protein (BMP). However, the BMP-related gene expression profile in oocytes at different maturational stages requires further investigation. METHODS: Oocytes were isolated from pubertal crossbred Landrace gilts follicles, selected with a use of BCB staining test and analyzed before and after in vitro maturation. Gene expression profiles were examined using an Affymetrix microarray approach and validated by RT-qPCR. Database for Annotation, Visualization, and Integrated Discovery (DAVID) software was used for the extraction of the genes belonging to a BMP-signaling pathway ontology group. RESULTS: The assay revealed 12,258 different transcripts in porcine oocytes, among which 379 genes were down-regulated and 40 were up-regulated. The DAVID database indicated a "BMP signaling pathway" ontology group, which was significantly regulated in both groups of oocytes. We discovered five up-regulated genes in oocytes before versus after in vitro maturation (IVM): chordin-like 1 (CHRDL1), follistatin (FST), transforming growth factor-beta receptor-type III (TGFβR3), decapentaplegic homolog 4 (SMAD4), and inhibitor of DNA binding 1 (ID1). CONCLUSIONS: Increased expression of CHRDL1, FST, TGFβR3, SMAD4, and ID1 transcripts before IVM suggested a subordinate role of the BMP signaling pathway in porcine oocyte maturational competence. Conversely, it is postulated that these genes are involved in early stages of folliculogenesis and oogenesis regulation in pigs, since in oocytes before IVM increased expression was observed.
- MeSH
- In Vitro Oocyte Maturation Techniques * MeSH
- Bone Morphogenetic Proteins genetics metabolism MeSH
- Cumulus Cells cytology metabolism physiology MeSH
- Microarray Analysis MeSH
- Oocytes cytology metabolism physiology MeSH
- Oogenesis genetics MeSH
- Swine genetics metabolism MeSH
- Signal Transduction genetics MeSH
- Gene Expression Profiling MeSH
- Transcriptome MeSH
- Gene Expression Regulation, Developmental MeSH
- Animals MeSH
- Check Tag
- Female MeSH
- Animals MeSH
- Publication type
- Journal Article MeSH
[1st ed.] 2 sv. : il.
- MeSH
- Gene Expression MeSH
- Reference Books, Medical MeSH
- Publication type
- Handbook MeSH
- Conspectus
- Obecná genetika. Obecná cytogenetika. Evoluce
- NML Fields
- genetika, lékařská genetika
- MeSH
- Child MeSH
- Adult MeSH
- Gene Expression MeSH
- Research Support as Topic MeSH
- Bone Marrow MeSH
- Blood MeSH
- Leukemia diagnosis genetics MeSH
- Middle Aged MeSH
- Humans MeSH
- Cordocentesis MeSH
- Oligonucleotide Array Sequence Analysis methods MeSH
- Check Tag
- Child MeSH
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Review MeSH
- Comparative Study MeSH
