Changelog

Better legends on the genes barplot and the correlation heatmap.
Improved vignette layout using the BioConductor style.
Additional version argument for connect_biomart to specify an Ensembl version.

New utility function cut_quantile for cutting a numeric vector into quantiles.
New utility function cat_with_newline for concatenating and printing with newline.
New check function check_proportion which checks for a single proportion.

New function draw_scatterplot to produce scatterplots of two genes or gene signatures.
New function draw_boxplot for boxplots of gene expression values.
New function draw_barplot for barplots of dichotomized gene expression counts into two or three percentile categories.
New helper function wrap_in_mae that wraps a single SummarizedExperiment object into an MAE object.
New method rename that makes renaming columns of rowData and colData as well as assay names in existing SummarizedExperiment objects much easier, as a step before converting to HermesData.
New method lapply that allows user to apply a function on all experiments in a MultiAssayExperiment.
New method isEmpty that checks whether a SummarizedExperiment object is empty.
New gene filtering option n_top in the calc_pca function, which allows filtering genes with greatest variability across samples.
New class GeneSpec for specification of genes or gene signatures, see ?gene_spec for simple construction. Inclusion of gene signature functions colPrinComp1 and colMeanZscores to supplement standard column statistics functions.
New helper function col_data_with_genes which extracts the sample variables saved in colData together with selected gene information as a combined data set.
New helper function inner_join_cdisc which joins genetic with CDISC data sets.

normalize() now also works when the hermes package is not loaded, i.e. you can use it with hermes::normalize().
correlate() now also works when there are factor variables in the sample variables of the HermesData object.
add_quality_flags() does no longer return NA as the technical failure flags for the samples if there is only a single gene contained in the input, but instead a vector of FALSE to ensure correct downstream functionality.

Updated LICENCE and README with new package references.
The multi_assay_experiment now contains HermesData experiments, different patient IDs, one experiment with normalized assays, and multiple samples per patient in one experiment.
The main HermesData example is now saved in the package as hermes_data, and the previous summarized_experiment is still available. Note that patient IDs have been changed in the new version to align with the multi_assay_experiment.
Renaming of required rowData and colData columns to be more consistent with standards and use lowercase snake-case names.
Annotation querying and setting is now more flexible in that it also allows to query more annotations than the required ones.
Instead of gene starts and ends, the total length of gene exons is now used as the annotation column size. Corresponding queries from BioMart are used to return this gene size.
df_char_to_factor has been deprecated (and can still be used with a warning) and replaced with df_cols_to_factor, which also converts logical variables to factor variables.
When providing SummarizedExperiment objects containing DelayedMatrix assays to the HermesData() constructor, these are silently converted to matrix assays to ensure downstream functionality.

First internal release of the hermes package, which contains classes, methods and functions to import, quality-check, filter, normalize, and analyze RNAseq counts data for differential expression.
hermes is a successor of the rnaseqTools R package. The core functionality is built on the BioConductor ecosystem, especially the SummarizedExperiment class. New users should first begin by reading the “Introduction to hermes” vignette to become familiar with the hermes concepts.

hermes 0.99.5.9003