MicroRNA microarray technology is a powerful high-throughput tool capable of monitoring the expression of thousands of microRNAs at once within tens of samples processed in parallel in a single experiment. While many of the same tools for analyzing mRNA expression arrays can be applied to the analysis of miRNA data, there are distinct differences between the two platforms which necessitate special use of some methods.
A package for the pre-processing and differential expression analysis of Agilent microRNA array data. For the pre-processing of the microRNA signal, AgiMicroRNA incorporates the robust multiarray average algorithm, a method that produces a summary measure of the microRNA expression using a linear model that takes into account the probe affinity effect. To obtain a normalized microRNA signal useful for the statistical analysis, AgiMicroRna offers the possibility of employing either the processed signal estimated by the robust multiarray average algorithm or the processed signal produced by the Agilent image analysis software. It also incorporates different graphical utilities to assess the quality of the data. AgiMicroRna uses the linear model features implemented in the limma package to assess the differential expression between different experimental conditions and provides links to the miRBase for those microRNAs that have been declared as significant in the statistical analysis.
Provides rank-based statistical methods to reveal microRNAs with differential expression in multiple cancer types. RCoS is a method that includes a differential expression score for two classes that take patient matching into account. It detects miRNAs that are up regulated in cancer, such as miR-182 and miR-183. It can also offset possible biases frequently encountered in the experimental data.
A compendium for the analysis of murine palate miRNA two-color expression data. MmPalateMiRNA has been made freely available on Bioconductor. It also includes several functions to produce diagnostic plots for evaluating probe intensity distributions on miRNA microarrays. The MmPalateMiRNA package is very useful as it presents a comprehensive analysis of miRNA data which is completely reproducible.
A user-friendly web interface for the AgiMicroRna R-package. MagiCMicroRna enables researchers to normalize and filter Agilent microarrays by the click of one button. Furthermore, MagiCMicroRna provides flexibility in choosing the filtering method. The new group-specific filtering approach lead to an increased number and additional tissue-specific microRNAs remaining for subsequent analysis compared to the standard procedure.
Provides functionalities for miRNA data analysis. miRNA-Analyzer is a software tool allowing the semi-automatic summarization, annotation and analysis (classification, clustering, and time-series analysis) of Affymetrix binary data. It is based on a plugin-based architecture that allows increasing the functionalities by inserting novel plug-ins. It also comprises a plugin management system that enables the insertion of analysis functionalities provided by another tool.
Assists users in investigating normalized omics large datasets. Qlucore Omics Explorer is a modular platform divided into four main functionalities (i) Visualization includes features for generating various plots types including principal component analysis (PCA) plots and real-time visualization; (ii) Exploration furnishes tools for comparing, browsing and selecting targeted information (iii) Analysis includes statistical methods such as quadratic regression, f-tests, or ANOVA and (iv) Sharing allows users to export results as multiple formats including videos or variable lists.
Provides pathway enrichment techniques for miRNA expression data. Specifically, the set of methods handles the many-to-many relationship between miRNAs and the multiple genes they are predicted to target (and thus affect.) miRNApath also handles the gene-to-pathway relationships separately. Both steps are designed to preserve the additive effects of miRNAs on genes, many miRNAs affecting one gene, one miRNA affecting multiple genes, or many miRNAs affecting many genes.
Assists users with the normalization of Agilent miRNA arrays. LVSmiRNA is an R package that includes several functions: it fits linear model at probe level and return the residual standard deviations and the array effects; it selects the Least Variant Set (LVS) of microRNAs; it provides data from a micro-RNA spike-in experiment; or it plots of residual variance and array effect for instance.
Offers a set of features able to compile microRNA and respective targets. RmiR is an R package composed of four main functions to: (i) plot objects from a selected target; (ii) combine miRNA and gene expression results for a specific database; (iii) compute correlation between the trend of miRNA and their corresponding gene targets and (iv) give access to a set of gene expression and microRNA expression data from the same RNA in a time course experiment.
Provides statistical tools for visualization and analysis of microarrays. GeneSpring GX offers an interactive environment that promotes investigation and enables understanding of Transcriptomics, Genomics, Metabolomics and Proteomics data within a biological context. It can be used for expression arrays, miRNA, exon arrays and genomics copy number data. It also allows to identify targets of interest that are both statistically and biologically meaningful.
Takes the MiChip miRNA microarray .grp scanner output files and parses these out, providing summary and plotting functions to analyse MiChip hybridizations. A set of hybridizations is packaged into an ExpressionSet allowing it to be used by other BioConductor packages.
A package that contains functions for reading raw data in ImaGene TXT format obtained from Exiqon miRCURY LNA arrays, annotating them with appropriate GAL files, and normalizing them using a spike-in probe-based method. Other platforms and data formats are also supported.
Predicts biological targets of miRNAs by searching for the presence of conserved 8mer and 7mer sites that match the seed region of each miRNA. Sites with mismatches in the seed region that are compensated by conserved 3' pairing are also identified. In mammals, predictions are ranked based on the predicted efficacy of targeting as calculated using the context scores of the sites. targetscan.Hs.eg.db provides detailed information about the latest version of the TargetScan miRNA target prediction database. This package is updated biannually.
Allows analysis of Exiqon miRCURY LNA™ microRNA Array data. miRCURY LNA microRNA Array Analysis Software contains ImaGene® 9, Nexus Expression™ 3 from BioDiscovery and settings files for analysis. The two programs help to convert tiff images of the scanned slides into useful information. The software allows to identify differentially expressed microRNAs and analyzes expression patterns across samples.
A tool for the analysis and visualization of high-level microarray data from individual or multiple different platforms. Currently, InCroMAP supports mRNA, microRNA, DNA methylation and protein modification datasets. Several methods are offered that allow for an integrated analysis of data from those platforms. The available features of InCroMAP range from visualization of DNA methylation data over annotation of microRNA targets and integrated gene set enrichment analysis to a joint visualization of data from all platforms in the context of metabolic or signalling pathways.
Analyses large-scale expression datasets. It utilizes curated sets of 3’ UTRs to attach sequences to these genes and then applies the Sylamer algorithm for detection of miRNA or siRNA signatures in those sequences. SylArray allows researchers from a broad area of expertise to perform fast and accurate detection of small RNA signatures in their gene-expression datasets.
Permits normalization of microarray data for removing bias and noise variability. LoessM is a normalization procedure, based on the loess algorithm, that scales expression data on the global median expression rather than on zero, as usually done for whole-genome arrays. Combined with eCADS, a biological replicates dye-swap design, the software is able to maintain the correct structure of expression data.
Normalizes miRNA array data using external information from the qRT-PCT results. Logit is a personalized logistic regression method built based on one-colored array data. This tool is a more feasible and adaptive normalization method for miRNA analysis.
Permits users to normalize microarray data. BeadSme is a measurement error model-based approach to improve beads array intrasample normalization. In comparison with other technics, this tool takes the measurement errors in the measures of the normalizes into consideration.
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