Package index • DIANNmv

All functions

add_contaminants(): Adds a Potential.contaminant column to pg_matrix based on MaxQuant contaminants.txt

add_iBAQ(): Add iBAQ intensities to report.pg_matrix file.

add_maxLFQ_iBAQ(): Adds iBAQ values based on LFQ values to SummarizedExperiment

add_median_peptide_intensity(): Adds median peptide intensities to summerizedExperiment object

add_peptide_numbers(): Add the peptide number information to pg_matrix

add_standardTheme(): Adds standard changes to ggplot theme

calculate_iBAQ(): Calculate iBAQ values from raw intensities

contaminants_maxquant: Data frame with potential contaminants from MaxQuant.

create_imputation_mask(): Returns boolean masks specifying MAR/MNAR imputation

expDesign: Experimental design for example data

get_DEPresults(): Perform differential protein expression analysis

get_detection_limit(): Find the cutoff for MAR/MNAR classification

get_genesets(): Extract a collection of gene sets from the MSigDB object

get_ibaq_peptides(): Perform in silico tryptic digest on uniprot fasta file

get_intensities_prMatrix(): Calculate protein intensities from peptide information

get_median_intensities_prMatrix(): Calculates the median peptide intensity per proteinGroup per sample.

get_nPep_prMatrix(): Get the numer of razor/unique peptides per proteinGroup per sample

get_peptide_position_in_protein(): Find the amino acid locations of peptides within a protein sequence

get_ranked_genes(): Rank proteins/genes based on fold change

ibaq_peptides: List with calculated theoretical tryptic peptides for mouse and human for iBAQ Peptides are calculated using 'cleaver' package with 'trypsin' set as enzyme, zero miscleavages, and peptide length 7-30.

load_msigdb(): Downloads MSigDB

mixed_imputation(): Perform mixed imputation on summarizedExperiment object

mixed_imputation_matrix(): Perform mixed imputation on a data matrix

perform_GSEA(): Perform GSEA based on DEP results

perform_mixed_imputation(): Perform mixed imputation over a matrix containing data of a single condition.

plotVolcano(): create volcano plots for all comparisons present in the results file

plot_DEP_barplot(): Make bar plot showing number of differential proteins between conditions.

plot_MA(): Makes MA plots for each comparison in the results data frame

plot_gsea_barplot(): Plots GSEA results as bar plot.

plot_gsea_bubbleplot(): Plots GSEA data as bubble plot. Mainly useful to compare multiple gsea comparisons.

plot_gsea_dotplot(): Plots GSEA data as a faceted dot plot showing NES, padj, and set size.

plot_gsea_volcano(): Plots GSEA data as volcano plot

plot_protein_coverage(): Plots the coverage of proteins.

plot_upset(): Plots upset plot showsing overlapping significant proteins between comparisons

plot_venn_diagram(): Plots a Venn diagram showing overlapping significant proteins

prepare_MA_data(): Prepare the data for making MA plots

prepare_barplot_data(): Prepare data for plot_DEP_barplot function.

prepare_diann_data(): Tidies sample names and parses an experimental design.

prepare_gsea_data(): Prepares data for the different GSEA visualization options

prepare_peptide_data(): Prepares the data for protein coverage plots.

prepare_se(): Prepare summarizedExperiment object from diann report.pg_matrix file

prepare_volcano_data(): Prepare data for volcano plots

recode_sig_col(): Relabel the significance column in the DEP results data frame

report.pg_matrix: Output file of DIANN with raw proteinGroup intensities on protein level.

report.pr_matrix: Output file of DIANN with raw intensities on peptide level.

summarize_peptide_intensities(): Combine different peptide variants into a single intensity

use_dep(): Prepares summarizedExperiment object to work with functions from DEP package.