CLC Genomics Workbench 10 和 Biomedical Genomics Workbench 4 版本发布 重磅

Improved RNA-seq analysis and more statistical tools

• The RNA-Seq Analysis tool now runs faster and delivers even more accurate results than before.

• You can now validate RNA-seq experiments using RNA spike-ins, such as ERCC and SIRV. You can also import custom spike-ins sets via the new Import Spike-ins tool.

• The RNA-seq analysis report has been greatly improved and now includes:

– the distribution of the biotypes that the reads mapped to

– the strand specificity of the reads

– any coverage bias

– potential adapter read-through

– the result of the spike-in experiment




• Pink highlights in the report help you identify potential problems in your RNA-seq analysis. The report also includes customized troubleshooting propositions when needed.



• The Create Combined RNA-Seq Report tool joins multiple RNA-seq analysis reports into one, hereby facilitating the comparison of several RNA-seq analysis runs. The combined report also flags data of sub-optimal quality or parameters that were not set appropriately.




• All statistical tools from the Advanced RNA-Seq plugin are now an integral part of the Toolbox in a new folder called RNA-Seq Analysis. These tools automatically account for differences due to sequencing depth, removing the need to normalize input data. They work with existing RNA-seq TE and GE tracks and allow you to generate 2D and 3D PCA plots, heat maps, volcano plots and Venn diagrams.




• A new tool called Gene Set Test uses a hypergeometric test to find overrepresented gene sets using input such as Gene Ontology terms. Gene Ontology annotations are now automatically propagated to parent Gene Ontology terms.





Importing improved

• You can now easily import:

– PacBio data

– RefSeq genomes

– More types of COSMIC reads than previously


• RNA tracks imported from GFF3 format files are now colored according to their biotype.




• When searching reads from SRA, you can now narrow your search only to those the ones associated with a PubMed abstract or full-text article.





Enhanced read mapper

• Our read mapper, which is used in tools such as Map Reads to References, Map Reads to Contigs and RNA-Seq Analysis, has been improved:

– It is faster

– It is more accurate for hard-to-map reads, especially those involving insertions or deletions

– It maps longer reads better

– It is optimized to deal with PacBio reads

– And it uses less memory


• Draft assemblies or transcriptomes with many shorter sequences will run faster in tools, and tables associated to the tracks will open more quickly.

• Filtering tables is easier: right-click on a table cell and filter table rows based on the value of that cell.




• The speed of searches from within a Metadata Table has been greatly improved.