Brings transcriptomics to the tidyverse

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Documentation for package ‘tidybulk’ version 1.99.4

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

.describe_transcript_SE	Get DESCRIPTION from gene SYMBOL for Human and Mouse
adjust_abundance	Adjust transcript abundance for unwanted variation
adjust_abundance-method	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
aggregate_duplicates-method	Aggregates multiple counts from the same samples (e.g., from isoforms), concatenates other character columns, and averages other numeric columns
as_matrix	Get matrix from tibble
as_SummarizedExperiment	as_SummarizedExperiment
as_SummarizedExperiment-method	as_SummarizedExperiment
cluster_elements	Get clusters of elements (e.g., samples or transcripts)
cluster_elements-method	Get clusters of elements (e.g., samples or transcripts)
deconvolve_cellularity	Get cell type proportions from samples
deconvolve_cellularity-method	Get cell type proportions from samples
describe_transcript	Get DESCRIPTION from gene SYMBOL for Human and Mouse
describe_transcript-method	Get DESCRIPTION from gene SYMBOL for Human and Mouse
fill_missing_abundance	Fill transcript abundance if missing from sample-transcript pairs
get_bibliography	Produces the bibliography list of your workflow
get_bibliography-method	Produces the bibliography list of your workflow
get_X_cibersort	Get Cibersort reference data
identify_abundant	Identify abundant transcripts/genes
identify_abundant-method	Identify abundant transcripts/genes
impute_missing_abundance	impute transcript abundance if missing from sample-transcript pairs
impute_missing_abundance-method	impute transcript abundance if missing from sample-transcript pairs
keep_abundant	Filter to keep only abundant transcripts/genes
keep_abundant-method	keep_abundant
keep_abundant-method	keep_abundant
keep_variable	Keep variable transcripts
keep_variable-method	Keep variable transcripts
log10_reverse_trans	Log10 reverse transformation for ggplot2
logit_trans	logit scale
pivot_sample	Extract sample-wise information
pivot_sample-method	Extract sample-wise information
pivot_transcript	Extract transcript-wise information
pivot_transcript-method	Extract transcript-wise information
quantile_normalise_abundance	Normalise by quantiles the counts of transcripts/genes
quantile_normalise_abundance-method	Normalise by quantiles the counts of transcripts/genes
reduce_dimensions	Dimension reduction of the transcript abundance data
reduce_dimensions-method	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
remove_redundancy-method	Drop redundant elements (e.g., samples) for which feature (e.g., transcript/gene) abundances are correlated
resolve_complete_confounders_of_non_interest	Resolve Complete Confounders of Non-Interest
resolve_complete_confounders_of_non_interest-method	resolve_complete_confounders_of_non_interest
rotate_dimensions	Rotate two dimensions (e.g., principal components) of an arbitrary angle
rotate_dimensions-method	Rotate two dimensions (e.g., principal components) of an arbitrary angle
scale_abundance	Scale the counts of transcripts/genes
scale_abundance-method	Scale the counts of transcripts/genes
scale_x_log10_reverse	scale_x_log10_reverse
scale_y_log10_reverse	scale_y_log10_reverse
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_abundance-method	Perform differential transcription testing using edgeR quasi-likelihood (QLT), edgeR likelihood-ratio (LR), limma-voom, limma-voom-with-quality-weights or DESeq2
test_differential_expression	Perform differential expression testing using edgeR quasi-likelihood (QLT), edgeR likelihood-ratio (LR), limma-voom, limma-voom-with-quality-weights or DESeq2
test_differential_expression-method	Perform differential expression testing using edgeR quasi-likelihood (QLT), edgeR likelihood-ratio (LR), limma-voom, limma-voom-with-quality-weights or DESeq2
test_gene_enrichment	analyse gene enrichment with EGSEA
test_gene_enrichment-method	analyse gene enrichment with EGSEA
test_gene_overrepresentation	analyse gene over-representation with GSEA
test_gene_overrepresentation-method	analyse gene over-representation with GSEA
test_gene_rank	analyse gene rank with GSEA
test_gene_rank-method	analyse gene rank with GSEA
test_stratification_cellularity-method	test_stratification_cellularity
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
X_cibersort	Cibersort reference