IPA limited concurrence license

ipa limited concurrence license:
The software must provide a comprehensive user-friendly, graphics user interface that allows scientists with a limited bioinformatics background to execute complex data analysis and management tasks.
The software must have the capabilities of displaying and analyzing DNA and RNA data.
The software must include an interactive genome browser that allows overlay and analysis of different types of genomic information, such as genome annotations, variants, gene expression, epigenetic information, visuals comparison, filtering, and analysis of data from multiple samples.
The software must be able to perform primary data analysis, which includes quality control, trimming for low quality regions and adapters, demultiplexing of barcoded data.
The software must be able to complete de novo assembly and scaffolding of genomes of any size, hybrid read mapping of next generation sequencing data, color space mapping, genome wide variant detection using advanced quality-based or ploidy aware algorithms and detection of structural variation, advanced filtering and annotation of variants based on information from public and commercial variant databases, trio analysis, and a workflow editor to build and share complex, and automated analysis workflows.
The software must be capable of RNA-seq analysis including support for paired data and transcript-level expression, small RNA analysis, expression profiling by tags, expressed sequence tag library sequence support, experimental design and statistical analysis of differential gene expression from RNA-Seq and Microarray data.
The software must allow for a large selection of standard formats for data import and export for easy transition between applications.
The software must be capable of analyzing, integrating, and interpreting of a combination of data derived from 'omics experiments, such as RNAseq, small RNAseq, microarrays including miRNA and SNP, metabolomics, and proteomics. Information can be used for small scale simulation experiments that generate gene and chemical lists.
The software must be able to combined experimental database to identified key regulators and activity to explain expression patterns; predicting downstream effects on biological and disease processes; providing targeted data on genes, proteins, chemicals, and drugs.