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A B C D E F G I K L M N P R S T U X
| add_attr | Add attribute to abject |
| add_class | Add class to abject |
| add_scaled_counts_bulk.calcNormFactor | Calculate the norm factor with calcNormFactor from limma |
| add_scaled_counts_bulk.get_low_expressed | Drop lowly tanscribed genes for TMM normalization |
| adjust_abundance | Adjust transcript abundance for unwanted variation |
| adjust_abundance-method | adjust_abundance |
| adjust_abundance-method | adjust_abundance |
| adjust_abundance-method | adjust_abundance |
| adjust_abundance-method | adjust_abundance |
| adjust_abundance-method | adjust_abundance |
| aggregate_duplicated_transcripts_bulk | Aggregates multiple counts from the same samples (e.g., from isoforms) This function aggregates counts over samples, concatenates other character columns, and averages other numeric columns |
| aggregate_duplicates | Aggregates multiple counts from the same samples (e.g., from isoforms), concatenates other character columns, and averages other numeric columns |
| aggregate_duplicates-method | aggregate_duplicates |
| aggregate_duplicates-method | aggregate_duplicates |
| aggregate_duplicates-method | aggregate_duplicates |
| aggregate_duplicates-method | aggregate_duplicates |
| aggregate_duplicates-method | aggregate_duplicates |
| arrange | Arrange rows by column values |
| arrange.default | Arrange rows by column values |
| as_matrix | Get matrix from tibble |
| bind | Efficiently bind multiple data frames by row and column |
| bind_cols | Efficiently bind multiple data frames by row and column |
| bind_rows | Efficiently bind multiple data frames by row and column |
| breast_tcga_mini | Data set |
| check_if_counts_is_na | Check whether there are NA counts |
| check_if_duplicated_genes | Check whether there are duplicated genes/transcripts |
| check_if_wrong_input | Check whether there are NA counts |
| cluster_elements | Get clusters of elements (e.g., samples or transcripts) |
| cluster_elements-method | cluster_elements |
| cluster_elements-method | cluster_elements |
| cluster_elements-method | cluster_elements |
| cluster_elements-method | cluster_elements |
| cluster_elements-method | cluster_elements |
| counts | Example data set |
| counts_ensembl | Counts with ensembl annotation |
| counts_mini | Example data set reduced |
| create_tt_from_bam_sam_bulk | Convert bam/sam files to a tidy gene transcript counts data frame |
| create_tt_from_tibble_bulk | Create tt object from tibble |
| deconvolve_cellularity | Get cell type proportions from samples |
| deconvolve_cellularity-method | deconvolve_cellularity |
| deconvolve_cellularity-method | deconvolve_cellularity |
| deconvolve_cellularity-method | deconvolve_cellularity |
| deconvolve_cellularity-method | deconvolve_cellularity |
| deconvolve_cellularity-method | deconvolve_cellularity |
| distinct | distinct |
| drop_attr | Drop attribute to abject |
| drop_class | Remove class to abject |
| ensembl_symbol_mapping | Data set |
| ensembl_to_symbol | Add transcript symbol column from ensembl id for human and mouse data |
| ensembl_to_symbol-method | ensembl_to_symbol |
| ensembl_to_symbol-method | ensembl_to_symbol |
| ensembl_to_symbol-method | ensembl_to_symbol |
| error_if_counts_is_na | Check whether there are NA counts |
| error_if_duplicated_genes | Check whether there are duplicated genes/transcripts |
| error_if_log_transformed | Check whether a numeric vector has been log transformed |
| error_if_wrong_input | Check whether there are NA counts |
| fill_NA_using_formula | This function is needed for DE in case the matrix is not rectangular, but includes NA |
| fill_NA_with_row_median | This function is needed for DE in case the matrix is not rectangular, but includes NA |
| filter | Subset rows using column values |
| flybaseIDs | flybaseIDs |
| full_join | Full join datasets |
| get_abundance_norm_if_exists | Get column names either from user or from attributes |
| get_adjusted_counts_for_unwanted_variation_bulk | Get adjusted count for some batch effect |
| get_cell_type_proportions | Get cell type proportions from cibersort |
| get_clusters_kmeans_bulk | Get K-mean clusters to a tibble |
| get_clusters_SNN_bulk | Get SNN shared nearest neighbour clusters to a tibble |
| get_differential_transcript_abundance_bulk | Get differential transcription information to a tibble using edgeR. |
| get_elements | Get column names either from user or from attributes |
| get_elements_features | Get column names either from user or from attributes |
| get_elements_features_abundance | Get column names either from user or from attributes |
| get_reduced_dimensions_MDS_bulk | Get dimensionality information to a tibble using MDS |
| get_reduced_dimensions_PCA_bulk | Get principal component information to a tibble using PCA |
| get_reduced_dimensions_TSNE_bulk | Get principal component information to a tibble using tSNE |
| get_rotated_dimensions | Get rotated dimensions of two principal components or MDS dimension of choice, of an angle |
| get_sample | Get column names either from user or from attributes |
| get_sample_counts | Get column names either from user or from attributes |
| get_sample_transcript | Get column names either from user or from attributes |
| get_sample_transcript_counts | Get column names either from user or from attributes |
| get_scaled_counts_bulk | Get a tibble with scaled counts using TMM |
| get_symbol_from_ensembl | after wget, this function merges hg37 and hg38 mapping data bases - Do not execute! |
| get_transcript | Get column names either from user or from attributes |
| get_x_y_annotation_columns | get_x_y_annotation_columns |
| group_by | Group by one or more variables |
| ifelse2_pipe | This is a generalisation of ifelse that acceots an object and return an objects |
| ifelse_pipe | This is a generalisation of ifelse that acceots an object and return an objects |
| impute_abundance | Impute transcript abundance if missing from sample-transcript pairs |
| impute_abundance-method | impute_abundance |
| impute_abundance-method | impute_abundance |
| impute_abundance-method | impute_abundance |
| impute_abundance-method | impute_abundance |
| impute_abundance-method | impute_abundance |
| inner_join | Inner join datasets |
| keep_abundant | Filter abundant transcripts |
| keep_abundant-method | keep_abundant |
| keep_abundant-method | keep_abundant |
| keep_abundant-method | keep_abundant |
| keep_abundant-method | keep_abundant |
| keep_abundant-method | keep_abundant |
| keep_variable | Filter variable transcripts |
| keep_variable-method | keep_variable |
| keep_variable-method | keep_variable |
| keep_variable-method | keep_variable |
| keep_variable-method | keep_variable |
| keep_variable-method | keep_variable |
| keep_variable_transcripts | Identify variable genes for dimensionality reduction |
| left_join | Left join datasets |
| mutate | Create, modify, and delete columns |
| nest | nest |
| parse_formula | .formula parser |
| pivot_sample | Extract sampe-wise information |
| pivot_sample-method | pivot_sample |
| pivot_sample-method | pivot_sample |
| pivot_sample-method | pivot_sample |
| pivot_transcript | Extract transcript-wise information |
| pivot_transcript-method | pivot_transcript |
| pivot_transcript-method | pivot_transcript |
| pivot_transcript-method | pivot_transcript |
| prepend | From rlang deprecated |
| reduce_dimensions | Dimension reduction of the transcript abundance data |
| reduce_dimensions-method | reduce_dimensions |
| reduce_dimensions-method | reduce_dimensions |
| reduce_dimensions-method | reduce_dimensions |
| reduce_dimensions-method | reduce_dimensions |
| reduce_dimensions-method | reduce_dimensions |
| remove_redundancy | Drop redundant elements (e.g., samples) for which feature (e.g., transcript/gene) aboundances are correlated |
| remove_redundancy-method | remove_redundancy |
| remove_redundancy-method | remove_redundancy |
| remove_redundancy-method | remove_redundancy |
| remove_redundancy-method | remove_redundancy |
| remove_redundancy-method | remove_redundancy |
| remove_redundancy_elements_though_reduced_dimensions | Identifies the closest pairs in a MDS contaxt and return one of them |
| remove_redundancy_elements_through_correlation | Drop redundant elements (e.g., samples) for which feature (e.g., genes) aboundances are correlated |
| rename | Rename columns |
| right_join | Right join datasets |
| rotate_dimensions | Rotate two dimensions (e.g., principal components) of an arbitrary angle |
| rotate_dimensions-method | rotate_dimensions |
| rotate_dimensions-method | rotate_dimensions |
| rotate_dimensions-method | rotate_dimensions |
| rotate_dimensions-method | rotate_dimensions |
| rotate_dimensions-method | rotate_dimensions |
| rowwise | Group input by rows |
| run_llsr | Perform linear equation system analysis through llsr |
| scale_abundance | Scale the counts of transcripts/genes |
| scale_abundance-method | scale_abundance |
| scale_abundance-method | scale_abundance |
| scale_abundance-method | scale_abundance |
| scale_abundance-method | scale_abundance |
| scale_abundance-method | scale_abundance |
| scale_design | Scale design matrix |
| se | SummarizedExperiment |
| select_closest_pairs | Sub function of remove_redundancy_elements_though_reduced_dimensions |
| se_mini | SummarizedExperiment mini for vignette |
| summarise | Summarise each group to fewer rows |
| symbol_to_entrez | Get ENTREZ id from gene SYMBOL |
| test_differential_abundance | Add differential transcription information to a tbl using edgeR. |
| test_differential_abundance-method | test_differential_abundance |
| test_differential_abundance-method | test_differential_abundance |
| test_differential_abundance-method | test_differential_abundance |
| test_differential_abundance-method | test_differential_abundance |
| test_differential_abundance-method | test_differential_abundance |
| test_gene_enrichment | analyse gene enrichment with EGSEA |
| test_gene_enrichment-method | test_gene_enrichment |
| test_gene_enrichment-method | test_gene_enrichment |
| test_gene_enrichment-method | test_gene_enrichment |
| test_gene_enrichment_bulk_EGSEA | Get gene enrichment analyses using EGSEA |
| tidybulk | Creates a 'tt' object from a 'tbl" |
| tidybulk-method | tidybulk |
| tidybulk-method | tidybulk |
| tidybulk-method | tidybulk |
| tidybulk-method | tidybulk |
| tidybulk_SAM_BAM | Creates a 'tt' object from a list of file names of BAM/SAM |
| tidybulk_SAM_BAM-method | tidybulk_SAM_BAM |
| tidybulk_to_SummarizedExperiment | tidybulk_to_SummarizedExperiment |
| ungroup | Group by one or more variables |
| X_cibersort | Cibersort reference |