支持系统
OS X 10.11
价格
68
下载次数
190
官方网站
Orca is a gene expression analysis software that is native to macOS, and does not require additional plugins or run-time environments, such as Java™. With Orca, there's no more copy & paste errors and tedious tasks to analyse and generate reports on gene expression data. The application allows for seamless analysis of differential gene expression on various types of gene expression data sets, such as RNAseq, MicroArray and NanoString®. Orca is a one time purchase which gives you *lifetime* access to the app. All updates to the app are made available to you for free and our team is constantly developing new and exciting features. This is unlike many analysis packages available to biomedical scientists that require monthly or annual subscriptions which can become cost prohibitive over time. **Features** - Orca comes with gene annotation data for 27 different species. - Access information from NCBI Gene for more detailed information on your gene of interest (internet access required). - Create journal quality figures straight from the app. - Intuitive copy & paste feature for copying tabulated data from Orca to other applications, such as Microsoft Excel and Graph Pad Prism. - Intuitively copy graphs to other applications, such as Microsoft PowerPoint and Adobe Illustrator. - Export graphs as high quality PNG or PDF (vector image). - Export tabulated data as tab-delimited (.txt) or comma separated value (.csv) files. - Orca comes packed with different data transformation and normalization features that can be applied with a simple click. - Intuitively build comparison ratios between your control and samples. - Create heatmaps to quickly identify highly differential genes. - Import gene expression data from tab-delimited or comma separated value files, which can be created with minimal effort with any spreadsheet software. **More new features to come with updates, such as gene ontology and enrichment analysis! So get your lifetime access to Orca now for a more intuitive and streamlined experience for gene expression analysis.