- Changed maintainer email address.
- New plotting function
draw_heatmapto produce heatmaps of (normalized) counts.
- The utility function
df_cols_to_factornow also converts existing factors to having explicit missing levels. - Version bump on
forcatsdependency. - Removed
ggplot2deprecation warning..count...
- Additional
versionargument forconnect_biomartto specify anEnsemblversion.
- First public release of the
hermespackage. - Submission to
BioConductor.
- Better legends on the genes barplot and the correlation heatmap.
- Improved vignette layout using the
BioConductorstyle.
- New utility function
cut_quantilefor cutting a numeric vector into quantiles. - New utility function
cat_with_newlinefor concatenating and printing with newline. - New check function
check_proportionwhich checks for a single proportion.
- New function
draw_scatterplotto produce scatterplots of two genes or gene signatures. - New function
draw_boxplotfor boxplots of gene expression values. - New function
draw_barplotfor barplots of dichotomized gene expression counts into two or three percentile categories. - New helper function
wrap_in_maethat wraps a singleSummarizedExperimentobject into an MAE object. - New method
renamethat makes renaming columns ofrowDataandcolDataas well as assay names in existingSummarizedExperimentobjects much easier, as a step before converting toHermesData. - New method
lapplythat allows user to apply a function on all experiments in aMultiAssayExperiment. - New method
isEmptythat checks whether aSummarizedExperimentobject is empty. - New gene filtering option
n_topin thecalc_pcafunction, which allows filtering genes with greatest variability across samples. - New class
GeneSpecfor specification of genes or gene signatures, see?gene_specfor simple construction. Inclusion of gene signature functionscolPrinComp1andcolMeanZscoresto supplement standard column statistics functions. - New helper function
col_data_with_geneswhich extracts the sample variables saved incolDatatogether with selected gene information as a combined data set. - New helper function
inner_join_cdiscwhich joins genetic with CDISC data sets.
normalize()now also works when thehermespackage is not loaded, i.e. you can use it withhermes::normalize().correlate()now also works when there are factor variables in the sample variables of theHermesDataobject.add_quality_flags()does no longer returnNAas the technical failure flags for the samples if there is only a single gene contained in the input, but instead a vector ofFALSEto ensure correct downstream functionality.
- Updated
LICENCEandREADMEwith new package references. - The
multi_assay_experimentnow containsHermesDataexperiments, different patient IDs, one experiment with normalized assays, and multiple samples per patient in one experiment. - The main
HermesDataexample is now saved in the package ashermes_data, and the previoussummarized_experimentis still available. Note that patient IDs have been changed in the new version to align with themulti_assay_experiment. - Renaming of required
rowDataandcolDatacolumns 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 fromBioMartare used to return this gene size. df_char_to_factorhas been deprecated (and can still be used with a warning) and replaced withdf_cols_to_factor, which also converts logical variables to factor variables.- When providing
SummarizedExperimentobjects containingDelayedMatrixassays to theHermesData()constructor, these are silently converted tomatrixassays to ensure downstream functionality.
- First internal release of the
hermespackage, which contains classes, methods and functions to import, quality-check, filter, normalize, and analyzeRNAseqcounts data for differential expression. hermesis a successor of thernaseqToolsR package. The core functionality is built on theBioConductorecosystem, especially theSummarizedExperimentclass. New users should first begin by reading the "Introduction tohermes" vignette to become familiar with thehermesconcepts.
- Import
RNAseqcount data into thehermesready format. - Annotate gene information from the
Ensembldatabase viabiomaRt. - Add quality control (QC) flags to genes and samples.
- Filter and subset the data set.
- Normalize the counts.
- Produce descriptive plots.
- Perform principal components analysis.
- Produce a templated QC
Rmdreport. - Perform differential expression analysis.