Release notes - June 6, 2022

Data Cruncher and Interactive Analysis become Data Studio and Interactive Browsers

Data Studio, previously Data Cruncher, is an interactive analysis tool which allows you to explore and visualize data using environments like JupyterLab and RStudio. Previously located under the Interactive Analysis tab, it has now been given a more prominent location in the project navigation by having its own tab located next to Tasks. With the removal of Data Studio from the Interactive Analysis tab, the tab's name has been changed to Interactive Browsers in order to better reflect its contents.

Recently published apps

We have just published an updated version (4.2.5.0) of Mutect2 workflows:

  • GATK Somatic SNVs and INDELs (Mutect2) 4.2.5.0, a workflow used for somatic short variant calling. It runs on a single tumor-normal pair or on a single tumor sample, and performs additional filtering and functional annotation tasks, and
  • GATK Create Mutect2 Panel of Normals 4.2.5.0 that creates a panel of normals for use in other GATK workflows. The workflow takes multiple normal sample callsets and passes them to GATK Somatic SNVs and INDELs (Mutect2) 4.2.5.0 with tumor-only mode (although it is called tumor-only, normal samples are given as the input) and additionally collates sites present in two or more samples into a sites-only VCF.
  • Three apps from the MetaXcan toolkit:
    • S-PrediXcan for computing associations between omic features and a complex trait starting from GWAS summary statistics.
    • S-MultiXcan for computing association from predicted gene expression to a trait, using multiple studies for each gene.
    • MetaMany for serially performing multiple MetaXcan runs on a GWAS study from summary statistics using multiple tissues.
  • The MetaXcan Workflow for computing associations between omic features and complex traits across multiple tissues. The workflow includes two tools from MetaXcan framework - MetaMany and S-MultiXcan and it uses summary statistics from a GWAS study and multiple models that predict the expression or splicing quantification.
  • MaxQuant (v2.0.3.0, CWL1.2), a quantitative proteomics tool designed for analysing large mass-spectrometric data. It uses a target-decoy search strategy to estimate and control the extent of false positives. Within the target-decoy strategy, MaxQuant applies the concept of posterior error probability (PEP) to integrate multiple peptide properties (e.g. length, charge, number of modifications) together with Andromeda score into a single quantity, reflecting the quality of a peptide spectrum match (PSM).
  • Manta (v1.6.0, CWL1.2), a tool used for calling structural variants (germline or somatic) from paired-end data. It can process WGS or WES data and supports germline SV calling on one or more samples (<=10) and somatic SV calling for matched tumor-normal pairs or tumor-only data.