Package index • tidybulk

All functions
`X_cibersort`	Cibersort reference
`adjust_abundance()`	Adjust transcript abundance for unwanted variation
`aggregate_duplicates()`	Aggregates multiple counts from the same samples (e.g., from isoforms), concatenates other character columns, and averages other numeric columns
`arrange`	Arrange rows by column values
`as_SummarizedExperiment()`	as_SummarizedExperiment
`as_matrix()`	Get matrix from tibble
`bind_rows`	Efficiently bind multiple data frames by row and column
`breast_tcga_mini_SE`	Needed for vignette breast_tcga_mini_SE
`cluster_elements()`	Get clusters of elements (e.g., samples or transcripts)
`counts_ensembl`	Counts with ensembl annotation
`deconvolve_cellularity()`	Get cell type proportions from samples
`describe_transcript()` `.describe_transcript_SE()`	Get DESCRIPTION from gene SYMBOL for Human and Mouse
`distinct`	distinct
`bind_cols` `left_join`	Left join datasets
`ensembl_symbol_mapping`	Data set
`ensembl_to_symbol()`	Add transcript symbol column from ensembl id for human and mouse data
`fill_missing_abundance()`	Fill transcript abundance if missing from sample-transcript pairs
`filter`	Subset rows using column values
`flybaseIDs`	flybaseIDs
`get_bibliography()`	Produces the bibliography list of your workflow
`group_by`	Group by one or more variables
`identify_abundant()`	find abundant transcripts
`impute_missing_abundance()`	impute transcript abundance if missing from sample-transcript pairs
`inner_join` `right_join` `full_join`	Inner join datasets
`keep_abundant()`	Keep abundant transcripts
`keep_variable()`	Keep variable transcripts
`log10_reverse_trans()`	log10_reverse_trans
`logit_trans()`	logit scale
`mutate`	Create, modify, and delete columns
`unnest` `nest`	unnest
`pivot_sample()`	Extract sample-wise information
`pivot_transcript()`	Extract transcript-wise information
`quantile_normalise_abundance()`	Normalise by quantiles the counts of transcripts/genes
`reduce_dimensions()`	Dimension reduction of the transcript abundance data
`remove_redundancy()`	Drop redundant elements (e.g., samples) for which feature (e.g., transcript/gene) abundances are correlated
`rename`	Rename columns
`resolve_complete_confounders_of_non_interest()`	Resolve Complete Confounders of Non-Interest
`rotate_dimensions()`	Rotate two dimensions (e.g., principal components) of an arbitrary angle
`rowwise`	Group input by rows
`scale_abundance()`	Scale the counts of transcripts/genes
`se`	SummarizedExperiment
`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()`	Perform differential transcription testing using edgeR quasi-likelihood (QLT), edgeR likelihood-ratio (LR), limma-voom, limma-voom-with-quality-weights or DESeq2
`test_differential_cellularity()`	Add differential tissue composition information to a tbl
`test_gene_enrichment()`	analyse gene enrichment with EGSEA
`test_gene_overrepresentation()`	analyse gene over-representation with GSEA
`test_gene_rank()`	analyse gene rank with GSEA
`test_stratification_cellularity()`	Test of stratification of biological replicates based on tissue composition, one cell-type at the time, using Kaplan-meier curves.
`tidybulk()`	Creates an annotated `tidybulk` tibble from a `tbl` or `SummarizedExperiment` object
`tidybulk_SAM_BAM()`	Creates a `tt` object from a list of file names of BAM/SAM
`tximeta_summarizeToGene_object`	Needed for tests tximeta_summarizeToGene_object, It is SummarizedExperiment from tximeta
`vignette_manuscript_signature_boxplot`	Needed for vignette vignette_manuscript_signature_boxplot
`vignette_manuscript_signature_tsne`	Needed for vignette vignette_manuscript_signature_tsne
`vignette_manuscript_signature_tsne2`	Needed for vignette vignette_manuscript_signature_tsne2

Reference

All functions