Ingenuity supports many sequencing data types from DNA to RNA sequencing across a wide range of NGS platforms, including but not limited to these popular choices.
Ingenuity Variant Analysis is a web application that helps researchers studying human disease to identify causal variants from human DNA-seq data in just minutes. Ingenuity Variant Analysis combines analytical tools and integrated content to help you rapidly identify and prioritize variants by drilling down to a small, targeted subset of compelling variants based both upon published biological evidence and your own knowledge of disease biology. With Variant Analysis, you can interrogate your variants from multiple biological perspectives, explore different biological hypotheses, and identify the most promising variants for follow-up.
Ingenuity® iReport™ for Isoform-level Human RNA-Seq Data eliminates the obstacles between data and biological insight by providing an easy, accurate biological interpretation tool for RNA-Seq data. iReport delivers a unique combination of interactive visual tools that help you quickly identify compelling genes, molecular interactions, pathways, diseases, and processes relevant to your experiment, resulting in a deeper biological understanding of your samples and a more efficient way to rapidly translate an experimental dataset into actionable biological insights.
Next-generation sequencing (NGS) technologies generate millions of reads and hundreds of datasets, and the need for a better way to accurately interpret and distill such large amounts of data has never been more acute. IPA helps you put this data into a biological context and quickly focus in on the most relevant genes to better understand the biological implications of your experiment. RNA-Sequencing (RNA-Seq) capabilities in IPA enable you to upload, analyze and visualize your processed RNA-Seq datasets for enhanced biological insights, helping to standardize RNA-Seq data analysis and interpretation results.
Upload processed RNA-Seq datasets directly into IPA to analyze and understand RNA-Seq data in the context of known biology to get a comprehensive view of your experimental system.
- Seamlessly move from data processing tools to biological interpretation by directly uploading RefSeq, Ensembl, or UCSC IDs into IPA.
- Quickly move beyond statistical analysis of high-throughput RNA-Seq data to understand the biological implications of your data, so you can accurately identify novel disease mechanisms, prioritize drug targets, generate hypotheses, and more.
- Identify significantly regulated isoforms in your experiment and determine their potential impact using information about functional protein domains and isoform-specific literature