Microarray analysis techniques
Encyclopedia
Microarray
A microarray is a multiplex lab-on-a-chip. It is a 2D array on a solid substrate that assays large amounts of biological material using high-throughput screening methods.Types of microarrays include:...
s, which allow researchers to investigate the expression state of a large number of genes - in many cases, an organism's entire genome
Genome
In modern molecular biology and genetics, the genome is the entirety of an organism's hereditary information. It is encoded either in DNA or, for many types of virus, in RNA. The genome includes both the genes and the non-coding sequences of the DNA/RNA....
- in a single experiment. Such experiments generate a very large volume of genetic data that can be difficult to analyze, especially in the absence of good gene annotation.
Introduction
Microarray data analysis involves several distinct steps, as outlined below. Changing any one of the steps has the potential to change the outcome of the analysis, so the MAQC Project was created to identify a set of standard strategies. Companies exist that use the MAQC protocols to perform a complete analysis.Creating raw data
Most microarray manufacturers, such as AffymetrixAffymetrix
Affymetrix is a company that manufactures DNA microarrays; it is based in Santa Clara, California, United States. The company was founded by Dr. Stephen Fodor in 1992. It began as a unit in Affymax N.V...
and Agilent, provide commercial data analysis software with microarray equipment such as plate readers.
Background correction
Depending on the type of array, signal related to nonspecific binding of the fluorophore can be subtracted to achieve better results. One approach involves subtracting the averagesignal intensity of the area between spots. A variety of tools for background correction and further analysis are available from TIGR, Agilent (GeneSpring), and Ocimum Biosolutions (Genowiz).
Quality control
Entire arrays may have obvious flaws detectable by visual inspection, pairwise comparisons to arrays in the same experimental group, or by analysis of RNA degradation. Results may improve by removing these arrays from the analysis entirely.Spot filtering
Visual identification of local artifacts, such as printing or washing defects, may likewise suggest the removal of individual spots. This can take a substantial amount of time depending on the quality of array manufacture. In addition, some procedures call for the elimination of all spots with an expression value below a certain intensity threshold.Aggregation and normalization
Comparing two different arrays, or two different samples hybridized to the same array generally involves making adjustments for systematic errors introduced by differences in procedures and dye intensity effects. Dye normalization for two color arrays is often achieved by local regressionLocal regression
LOESS, or LOWESS , is one of many "modern" modeling methods that build on "classical" methods, such as linear and nonlinear least squares regression. Modern regression methods are designed to address situations in which the classical procedures do not perform well or cannot be effectively applied...
. LIMMA provides a set of tools for background correction and scaling, as well an option to average on-slide duplicate spots.. A common method for evaluating how well normalized an array is, is to plot an MA plot
MA plot
DNA microarrays consist of an arrayed series of thousands of microscopic spots of DNA which allow comparisons between two samples of RNA or DNA , which can provide data on relative gene expression levels or gene copy number . The data obtained from two-color DNA microarrays come in the form of...
of the data.
Raw Affy data contains about twenty probes for the same RNA target. Half of these are "mismatch spots", which do not precisely match the target sequence. These can theoretically measure the amount of nonspecific binding for a given target. Robust Multichip Average (RMA) is a normalization approach that does not take advantage of these mismatch spots, but still must summarize the perfect matches through median polish
Median polish
The median polish is an exploratory data analysis procedure proposed by the statistician John Tukey. It finds an additively-fit model for data in a two-way layout table of the form row effect + column effect + overall median.-References:* Frederick Mosteller and John Tukey . "Data Analysis and...
. The median polish algorithm, although robust, behaves differently depending on the number of samples analyzed. Quantile normalization, also part of RMA, is one sensible approach to normalize a batch of arrays in order to make further comparisons meaningful.
The current Affymetrix MAS5 algorithm, which uses both perfect match and mismatch probes, continues to enjoy popularity and do well in head to head tests.
Factor Analysis for Robust Microarray Summarization (FARMS) is a model-based technique for summarizing array data at perfect match probe level. It is based on a factor analysis model for which a Bayesian maximum a posteriori method optimizes the model parameters under the assumption of Gaussian measurement noise. According to the Affycomp benchmark FARMS outperformed all other summarizations methods with respect to sensitivity and specificity.
Identification of significant differential expression
Many strategies exist to identify which array probes show an unusual level of over expression or under expression. The simplest one is to call "significant" any probe that differs by an average of at least twofold between treatment groups. More sophisticated approaches are often related to t-tests or other mechanisms that take both effect size and variability into account. Curiously, the p-values associated with particular genes do not reproduce well between replicate experiments, and lists generated by straight fold change perform much better. This represents an extremely important observation, since the point of performing experiments has to do with predicting general behavior. The MAQC group recommends using a fold change assessment plus a non-stringent p-value cutoff, further pointing out that changes in the background correction and scaling process have only a minimal impact on the rank order of fold change differences, but a substantial impact on p-values.Pattern recognition
Commercial systems for gene network analysis such as Ingenuity and Pathway studio create visual representations of differentially expressed genes based on current scientific literature. Non-commercial tools such as GenMAPPGenMAPP
GenMAPP is a free, open-source bioinformatics software tool designed to visualize and analyze genomic data in the context of pathways , connecting gene-level datasets to biological processes and disease. First created in 2000, GenMAPP is developed by an open-source team based in an academic...
also aid in organizing and visualizing gene network data procured from one or several microarray experiments. A wide variety of microarray analysis tools are available through Bioconductor
Bioconductor
Bioconductor is a free, open source and open development software project for the analysis and comprehension of genomic data generated by wet lab experiments in molecular biology....
written in the R programming language. The frequently cited SAM Excel module and other microarray tools are available through Stanford University. Another set is available from Harvard and MIT.
Specialized software tools for statistical analysis to determine the extent of over- or under-expression of a gene in a microarray experiment relative to a reference state have also been developed to aid in identifying genes or gene sets associated with particular phenotype
Phenotype
A phenotype is an organism's observable characteristics or traits: such as its morphology, development, biochemical or physiological properties, behavior, and products of behavior...
s. One such method of analysis, known as Gene Set Enrichment Analysis (GSEA), uses a Kolmogorov-Smirnov-style statistic to identify groups of genes that are regulated together. This third-party statistics package offers the user information on the genes or gene sets of interest, including links to entries in databases such as NCBI's GenBank
GenBank
The GenBank sequence database is an open access, annotated collection of all publicly available nucleotide sequences and their protein translations. This database is produced and maintained by the National Center for Biotechnology Information as part of the International Nucleotide Sequence...
and curated databases such as Biocarta and Gene Ontology
Gene Ontology
The Gene Ontology, or GO, is a major bioinformatics initiative to unify the representation of gene and gene product attributes across all species...
. Related system, PAINT and SCOPE performs a statistical analysis on gene promoter regions, identifying over and under representation of previously identified transcription factor
Transcription factor
In molecular biology and genetics, a transcription factor is a protein that binds to specific DNA sequences, thereby controlling the flow of genetic information from DNA to mRNA...
response elements. Another statistical analysis tool is Rank Sum Statistics for Gene Set Collections (RssGsc), which uses rank sum probability distribution functions to find gene sets that explain experimental data. A further approach is contextual meta-analysis, i.e. finding out how a gene cluster responds to a variety of experimental contexts. Genevestigator
Genevestigator
Genevestigator is a web-based application developed for biologists and medical researchers to rapidly find out in which tissues, at which stages of development, and to what stimuli, drug treatments, diseases, or genetic modifications genes of given organisms are activated...
is a public tool to perform contextual meta-analysis across contexts such as anatomical parts, stages of development, and response to diseases, chemicals, stresses, and neoplasms.