iOMICS is a cloud-based high performance software for analyzing genomic data. It offers researchers in academia, pharmaceuticals and biotechs a powerful computational resource to get exhaustive, reproducible results at unprecedented speed and accuracy. Built for collaboration and large scale genomics research, iOMICS helps researchers store and manage large data volumes securely.
iOMICS has 20+ pre-built workflows and 500+ gold standard, peer-reviewed software tools for sequence data analysis, microarray data analysis, meta-analysis, functional genomics, biomarker discovery, drug target discovery and patient stratification.
Identification of variants in the exonic region of the human genome. This app comes with advanced features to classify, annotate and perform population based statistics on the variants
Detection of single nucleotide polymorphisms and structural variants with high precision at the whole genome level
Identification of transcripts and genes from RNA-Seq data, along with expression patterns for multiple samples and case-control studies
Identification and annotation of miRNAs from NGS data to study their expression level changes and functional implications
Identification and annotation of DNA protein interaction sites or peaks from ChIP-seq experiments
High-precision NGS based HLA typing software for identifying all known HLA alleles and common alleles across samples
Identification of microbial communities and their distribution in metagenomic samples
Identification of DNA interaction sites which show direct change in the transcriptome
Identification of DNA variations which show direct change in the transcriptome
Identification of miRNA target genes
Microarray based detection of genome wide DNA interaction sites along with functional annotations
Identification of gene products expressed for a specific condition along with functional analysis
Identification of miRNA’s expressed for specific conditions along with target identification
Identification of Gene Ontology, Pathways and Diseases for significant genes
Identify novel, high quality drug target candidates
Identify biomarkers and clinical markers which distinguish responders from non-responders to specific drug/treatment using powerful statistical tools such as Bayesian modeling, Cox regression and LASSO etc
Annotation of reported genetic variations
Annotation of functional and protein prediction effects of Genetic Variations
Annotation of allele frequency from large-scale exome sequencing project of various population such as African, American, East Asian, Finish, South Asian and others
Annotation of clinical significance of variants with associated phenotypes and its supporting evidences
Annotation of allele frequency of various population such as African, European, American, Asian and Global
Gene Expression patterns under different biological conditions for different tissue types
Annotation of tissue base line expression for healthy individuals for different tissue types
Used for obtaining the genes associated with specific phenotypes
Ontology or controlled vocabulary for phenotypic abnormalities encountered in human disease
Used for genome scale metabolic reconstruction network for human to identify potential drug target for specific phenotype
Annotation of enriched, peer reviewed pathways for human
Annotation of signaling pathways for humans
Protein-protein interaction for humans from published literatures
Annotation of signaling pathways for humans
Annotation of Biological Process, Molecular Function and Cellular Component for given set of genes
High quality controlled-access raw and processed genetic data sets across a board range of disease indication such as Neurology, Pediatric, Oncology and Metabolic diseases with over 600+ patient genetic and respective clinical data from Asian population. Explore a large set of curated data from published literature containing variations and clinical information for functional annotation.
Integrates multi scale Multi-Omics data, along with Omnia data, to understand the disease etiology, right from the genomic to the phenotype scale. It can be used to perform advanced disease analytics such as phenotype modeling, drug target identification and validation, and biomarker identification for disease prediction, prognosis, and Pharmacogenomics. It aids in reducing cost, improving turn around time, and a better success rate of drug discovery.
It is easy to analyze terabytes of genomics datasets without the need for in-house high performance computing hardware systems. Cloud implementation enables improved accessibility, automatic software updates, convenient pay-per use model, easy data sharing and remote accessibility.
Individual datasets from different technologies such as targeted gene seq, Whole EXOME-Seq, DNA-Seq, RNA-Seq, ChIP-Seq and Microarrays can be analyzed. It also supports the integration of Multi-Omics datasets to discover the genetic flow of information associated with the phenotypes.
Drug Target Discovery identify potential drug targets using gene expression data (RNA/Microarray) through genome scale metabolic reconstruction and in silico knock out modelling. Identified targets are annotated for pathways and gene ontologies. Also, the human protein-protein interaction network properties are identified for the potential drug targets.
Suitable for independent researchers and enterprises looking for quick access to genomics data analysis infrastructure that is usually available to large labs and enterprises.
The iOMICS Cloud suite brings unlimited access to High Performance Computing software and systems coupled with highly efficient and user friendly Next Generation Sequencing data analysis apps through a simple web browser, straight from your laptop or a tablet. With iOMICS Cloud suite there is no need to invest in developing large compute infrastructure and no need to build and maintain complex genomics data analysis and visualization pipelines. All that is required to translate your raw genomics data into actionable insights is a simple iOMICS user account at http://iomics.interpretomics.co/