Data integration software tools | DNA methylation microarray data analysis
Cancer development and progression is driven by a complex pattern of genomic and epigenomic perturbations. Both types of perturbations can affect gene expression levels and disease outcome. Integrative analysis of cancer genomics data may therefore improve detection of perturbed genes and prediction of disease state.
A combined database and R package that allows you to investigate the methylation state of regions of interest across the genome. Marmal-aid is the largest publicly available Illumina HumanMethylation450 methylation database combining Illumina HumanMethylation450 data from a number of sources into a single location with a single common annotation format. This allows for automated extraction using the R package and inclusion into existing analysis pipelines. Marmal-aid also provides a easy to use GUI to visualise methylation data in user defined genomic regions for various reference tissues.
Provides analysis and integration of genomics data. SCANN is a method that extracts the stemness signature of several tissues by training a multiclass single-layer linear artificial neural network. Data were integrated by generalization of the hematopoietic stem cell hierarchy and by homology between different adult and embryonic tissues (liver, blood, bone, prostate and stomach in Homo sapiens and Mus musculus).
Provides tools for analysing single-nucleotide resolution methylation data. COHCAP is a pipeline that covers most user needs for differential methylation and integration with gene expression data. The software includes quality control metrics, defining differentially methylated CpG sites, defining differentially methylated CpG islands and visualization of methylation data. It contains two different methods of CpG island analysis. COHCAP has been shown scalable for high-quality integrative analysis of cell line data as well as large heterogeneous patient 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.
Enables analysis and visualization of the information content of genomic signals. MSR is a method, adapted from an image segmentation algorithm and inspired by multiscale approaches for classifying image texture patterns. The software enables global analysis of genomic data in an unbiased manner with respect to the spatial scales on which biological information is encoded. It was used to analyze measurements of transcription factor binding, covalent histone modifications and DNA methylation, as well as genomic annotations and sequence-derived data.
Encapsulates multiple data sets. MultiDataSet is an R package designed to manage data from different omics experiment in the same individuals. The software contains methods to perform typical operations, such as sub-setting or selecting common samples, making integrative analysis more accessible to users with a low expertise in bioinformatics. Base classes for MEAL and rexposome packages are included.
Enables researchers to predict the origin site of tumor samples of their interests. MMCOP is a web-server that consists of classifiers based on Illumina 450k DNA methylation (DNAm) profiles and microRNA (miRNA) expression. 14 tissues for miRNA expression profiles are supported by the software, as well as the same number for DNA methylation profiles. The software was tested using seven DNAm datasets in GEO.