
Package index
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hermeshermes-package -
hermesPackage
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HermesData()HermesDataFromMatrix() -
HermesDataandRangedHermesData
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correlate(<AnyHermesData>)autoplot(<HermesDataCor>) - Correlation between Sample Counts of
AnyHermesData
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calc_pca() - Principal Components Analysis Calculation
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top_genes()autoplot(<HermesDataTopGenes>) - Derivation of Top Genes
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summary()show(<HermesDataSummary>) - Summary Method for
AnyHermesDataObjects
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correlate(<HermesDataPca>)autoplot(<HermesDataPcaCor>) - Correlation of Principal Components with Sample Variables
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diff_expression()autoplot(<HermesDataDiffExpr>) - Differential Expression Analysis
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connect_biomart() - Connection to
BioMart
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GeneSpec - R6 Class Representing a Gene (Signature) Specification
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HermesData()HermesDataFromMatrix() -
HermesDataandRangedHermesData
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gene_spec() -
GeneSpecConstructor
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all_na() - Checks Whether All Missing
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cat_with_newline() - Concatenate and Print with Newline
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validate_counts()validate_cols()validate_row_data()validate_col_data()validate_names()validate_prefix() - Internal Helper Functions for Validation of
AnyHermesDataObjects
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h_map_pos() - Helper Function For Matching Map Values to Names
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normalize(<AnyHermesData>)h_cpm()h_rpkm()h_tpm()h_voom()h_vst()h_rlog() - Normalization of
AnyHermesDataObjects
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add_quality_flags()h_low_expression_flag()h_low_depth_flag()h_tech_failure_flag()get_tech_failure()get_low_depth()get_low_expression() - Add Quality Flags
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h_diff_expr_voom() -
limma/voom Differential Expression Analysis
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h_diff_expr_deseq2() -
DESeq2Differential Expression Analysis
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h_pca_var_rsquared() - Calculation of R2 between Sample Variable and Principal Components
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h_pca_df_r2_matrix() - Calculation of R2 Matrix between Sample Variables and Principal Components
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h_get_annotation_biomart() - Get Annotations from
BioMart
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h_get_granges_by_id() - Conversion of
BioMartCoordinates intoGRanges
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h_get_size_biomart() - Total Length of All Exons for Genes
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h_ensembl_to_entrez_ids() - Translation of
EnsembltoEntrezGene IDs
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h_strip_prefix() - Stripping Prefix from Gene IDs
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h_has_req_annotations() - Predicate for Required Annotations
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h_short_list() - Make a Short List of a Character Vector
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h_parens() - Parenthesize a Character Vector
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h_all_duplicated() - Finding All Duplicates in Vector
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h_unique_labels() - Creation of Unique Labels
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h_df_factors_with_explicit_na() - Conversion to Factors with Explicit Missing Level in a
data.frame
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draw_boxplot()h_draw_boxplot_df() - Boxplot for Gene Expression Values
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expression_set - Example
ExpressionSetData
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hermes_data - Example
HermesDataData
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summarized_experiment - Example
SummarizedExperimentData
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multi_assay_experiment - Example
MultiAssayExperimentData
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annotation(<AnyHermesData>).row_data_annotation_cols`annotation<-`(<AnyHermesData>,<DataFrame>) - Annotation Accessor and Setter
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cbind - Column Binding of
AnyHermesDataObjects
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correlate() - Generic Function for Correlation Calculations
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counts(<AnyHermesData>)`counts<-`(<AnyHermesData>,<matrix>) - Counts Accessor and Setter
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extraColDataNames()extraRowDataNames() - Extra Variable Names Accessor Methods
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filter() - Filter
AnyHermesDataon Subset Passing Default QC Flags
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genes() - Gene IDs Accessor
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isEmpty(<SummarizedExperiment>) - Checking for Empty
SummarizedExperiment
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lapply(<MultiAssayExperiment>) -
lapplymethod forMultiAssayExperiment
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metadata - Metadata Accessor and Setter
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normalize(<AnyHermesData>)h_cpm()h_rpkm()h_tpm()h_voom()h_vst()h_rlog() - Normalization of
AnyHermesDataObjects
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prefix() - Prefix Accessor
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query() - Query Gene Annotations from a Connection
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rbind - Row Binding of
AnyHermesDataObjects
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rename(<SummarizedExperiment>)rename(<data.frame>) - Renaming Contents of
SummarizedExperimentObjects
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samples(<AnyHermesData>) - Sample IDs Accessor
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show(<HermesData>)show(<RangedHermesData>) - Show Method for
AnyHermesDataObjects
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subset - Subsetting
AnyHermesDataObjects
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summary()show(<HermesDataSummary>) - Summary Method for
AnyHermesDataObjects
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add_quality_flags()h_low_expression_flag()h_low_depth_flag()h_tech_failure_flag()get_tech_failure()get_low_depth()get_low_expression() - Add Quality Flags
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calc_pca() - Principal Components Analysis Calculation
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diff_expression()autoplot(<HermesDataDiffExpr>) - Differential Expression Analysis
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set_tech_failure() - Set Technical Failure Flags
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top_genes()autoplot(<HermesDataTopGenes>) - Derivation of Top Genes
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connect_biomart() - Connection to
BioMart
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df_cols_to_factor() - Conversion of Eligible Columns to Factor Variables in a
DataFrame
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colPrinComp1() - First Principal Component (PC1) Gene Signature
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colMeanZscores() - Mean Z-score Gene Signature
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wrap_in_mae() - Wrap in MAE
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col_data_with_genes() - Sample Variables with Selected Gene Information
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inner_join_cdisc() - Inner Joining a Genes with a CDISC Data Set
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cut_quantile() - Cutting a Numeric Vector into a Factor of Quantile Bins
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draw_libsize_hist() - Histogram of Library Sizes
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draw_libsize_qq() - Q-Q Plot of Library Sizes
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draw_libsize_densities() - Density Plot of (Log) Counts Distributions
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draw_nonzero_boxplot() - Boxplot of Non-Zero Genes
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draw_genes_barplot() - Stacked Barplot of Low Expression Genes by Chromosome
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draw_heatmap() - Heatmap for Gene Expression Counts
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draw_scatterplot() - Scatterplot for Gene Expression Values
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draw_barplot() - Barplot for Gene Expression Percentiles
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draw_boxplot()h_draw_boxplot_df() - Boxplot for Gene Expression Values
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autoplot(<AnyHermesData>) - All Standard Plots in Default Setting
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control_normalize() - Control Settings for Counts Normalization
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control_quality() - Control for Specified Quality Flags
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assertion_arguments - Standard Assertion Arguments
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check_proportion()assert_proportion()test_proportion()expect_proportion() - Check for proportion
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is_class()is_hermes_data()is_counts_vector()is_list_with()one_provided()is_constant() - Additional Assertions for
assert_that
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annotation(<AnyHermesData>).row_data_annotation_cols`annotation<-`(<AnyHermesData>,<DataFrame>) - Annotation Accessor and Setter