Jamie Hill, Senior Bioinformatics Scientist introduces the latest release.
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.
• 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.
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