1.4.0

• Support for loading new GTEx V7 data
• Support gene expression data:
  • Load, filter, normalise and perform log2-transformation on gene expression data
  • Perform principal component analysis based on gene expression data, survival analysis by gene expression cutoff and pairwise differential gene expression analysis
  • Correlate gene expression of a given gene against PSI values of multiple alternative splicing events
• Data loading:
  • Add step-wise instructions about loading of user-owned files
  • Filter GTEx junction quantification based on tissues of interest (all tissues are loaded by default)
  • Quantify splicing based on a list of genes (splicing events within all genes are quantified by default)
  • Parse sample information from TCGA samples using parseTcgaSampleInfo
  • Generate TCGA sample metadata when loading TCGA junction quantification
  • Present data summary after loading the data
• Data grouping:
  • Redesigned group creation and selection
  • Create groups based on genes and alternative splicing events
  • Assign a customisable colour per data group
  • Export or import patient and sample identifiers of data groups
  • Add new set operations when grouping (such as complement, subtraction and symmetric difference)
  • Suggest attributes of interest when creating groups
  • Allow to retrieve the universe of patient and sample identifiers by performing the complement group without any group selected
  • Statistically analyse group independence (useful to assess the overlap between a PCA cluster and groups derived from clinical and sample attributes, for instance)
• Differential analysis:
  • Label points based on top differentially spliced events or genes, selected alternative splicing events and/or selected genes
  • Create AS event and gene groups based on filtered or selected AS events and genes in the tables
• Dimensionality reduction techniques:
  • Subset data based on groups of AS events and genes before performing dimensionality reduction
  • Create data groups based on the partitioning clustering of PCA scores
  • Perform independent component analysis (ICA) on alternative splicing quantification and gene expression data
• Survival analysis:
  • Add p-value plot to visually infer the significance of survival analyses based on multiple alternative splicing quantification cutoffs
• Gene, transcript and protein information:
  • Information retrieval is now only dependent on a user-defined gene, instead of requiring alternative splicing quantification data to be loaded

Bug fixes and other improvements

• Show progress bar when running in the command-line interface
• Fix inconsistent browser history navigation
• Updated the CLI vignette with information on analysing gene expression data and a quick reference for functions
• Update minimum version required of shiny (1.0.3)
• Avoid replacing selected groups when manipulating new ones
• Differential splicing analysis:
  • Fix data not being rendered in the table when zooming in the plot after data transformation was applied
  • Return p-value of NA instead of 0 when the value of Fligner-Killeen's Test for Homogeneity of Variance is infinite
  • Discard value transformations that may return invalid data for the values chosen for the X and Y axes
  • Fix point that remains highlighted in the plot after deselecting the only selected row of the table
  • Improve readibility of plot's tooltip
  • Improve survival curves based on the optimal alternative splicing quantification cutoff:
    • Include the survival curve previews in 3 new columns within the differential splicing analyses table, instead of below that table; those columns consist of the survival curves, the optimal PSI cutoff and the respective log-rank test's p-value
    • Allow to use survival data when plotting and table sorting
    • Include the optimal PSI cutoff and the respective log-rank test's p-value in exported tables
    • Fix link to survival analyses using the previously calculated PSI cutoff
• Principal component analysis:
  • When clicking on a alternative splicing event in the loadings plot, the appropriate differential splicing analyses will now be automatically rendered with the respective options, as expected
• Survival analysis:
  • Properly set the title of survival curves based on the selected splicing event's quantification
  • Improve readability of Cox PH models
  • When performing survival analyses by alternative splicing cutoff, each patient is assigned the PSI value from the respective sample; for patients with more than one sample, the assigned sample is chosen based on the most frequent sample type across all patients (before, the first matched non-normal or non-control samples were used)
• Multiple other bug fixes and visual improvements