CLC Genomics Workbench 9.5
With the latest release of CLC Genomics Workbench we continue to enhance your data analysis experience
Boost your research by making project-level management of data and metadata easier. The new SRA-download features integrate into NCBI SRA, the largest archive of next-generation sequencing datasets.
- Powerful new search feature under the Download menu. Cast a wide search, e.g. by organism, data type, or disease. Then narrow down your search and filter for dates or other information found in the SRA or abstracts.
- Search or filter by Run-, Experiment-, Study-, or Sample Accession numbers.
- More meaningful data interpretation through metadata. SRA metadata are linked to downloaded reads and are available for statistics and visualizations.
- Maximize data transfer rates through Aspera support.
Enhance accuracy and data interpretation for your RNA-seq analysis
We are releasing improved visualizations and statistics. If you have not yet installed the Advanced RNA-Seq plugin, we suggest you give it a try (the plugin is available for CLC Genomics Workbench free of additional costs).
- More powerful genome browsing with expression data
- New tabular expression browser enables grouping of samples by metadata, or switching between different expression values
- Explore gene expression levels in the genome browser view (track list). Enjoy the new color-coding of expression tracks. Coloring according to a log-scale improves the visual interpretation of expression data. Expression track visualizations also dynamically rescale making best use of your screen real estate
- Statistical Comparison Tracks produced by the Advanced RNA-Seq plugin, can now be used for annotating and filtering other tracksExport expression tracks in BED format. The expression value will be exported as the score.
- Improve the accuracy of isoform and gene quantification with a new option In the RNA-seq tool. The option "Use EM estimation (recommended)" uses an expectation-maximization algorithm to distribute ambiguous reads between isoform/genes in a manner similar to RSEM
- PCA plots help you discover factors underlying expression changes. Visualization now available in 2D and 3D
Expression tracks in genome browser (track list) view