protti0.9.1 package

Bottom-Up Proteomics and LiP-MS Quality Control and Data Analysis Tools

analyse_functional_network

Analyse protein interaction network for significant hits

anova_protti

Perform ANOVA

assign_missingness

Assignment of missingness types

assign_peptide_type

Assign peptide type

barcode_plot

Barcode plot

calculate_aa_scores

Calculate scores for each amino acid position in a protein sequence

calculate_diff_abundance

Calculate differential abundance between conditions

calculate_go_enrichment

Perform gene ontology enrichment analysis

calculate_imputation

Sampling of values for imputation

calculate_kegg_enrichment

Perform KEGG pathway enrichment analysis

calculate_protein_abundance

Label-free protein quantification

calculate_sequence_coverage

Protein sequence coverage

calculate_treatment_enrichment

Check treatment enrichment

correct_lip_for_abundance

Protein abundance correction for LiP-data

create_queue

Creates a mass spectrometer queue for Xcalibur

create_structure_contact_map

Creates a contact map of all atoms from a structure file

create_synthetic_data

Creates a synthetic limited proteolysis proteomics dataset

diff_abundance

Calculate differential abundance between conditions

drc_4p_plot

Plotting of four-parameter dose response curves

drc_4p

Dose response curve helper function

extract_metal_binders

Extract metal-binding protein information from UniProt

fetch_alphafold_aligned_error

Fetch AlphaFold aligned error

fetch_alphafold_prediction

Fetch AlphaFold prediction

fetch_chebi

Fetch ChEBI database information

fetch_eco

Fetch evidence & conclusion ontology

fetch_go

Fetch gene ontology information from geneontology.org

fetch_kegg

Fetch KEGG pathway data from KEGG

fetch_metal_pdb

Fetch structural information about protein-metal binding from MetalPDB

fetch_mobidb

Fetch protein disorder and mobility information from MobiDB

fetch_pdb_structure

Fetch PDB structure atom data from RCSB

fetch_pdb

Fetch structure information from RCSB

fetch_quickgo

Fetch information from the QuickGO API

fetch_uniprot_proteome

Fetch proteome data from UniProt

fetch_uniprot

Fetch protein data from UniProt

filter_cv

Data filtering based on coefficients of variation (CV)

find_all_subs

Find all sub IDs of an ID in a network

find_chebis

Find ChEBI IDs for name patterns

find_peptide_in_structure

Finds peptide positions in a PDB structure based on positional matchin...

find_peptide

Find peptide location

fit_drc_4p

Fitting four-parameter dose response curves

go_enrichment

Perform gene ontology enrichment analysis

impute

Imputation of missing values

kegg_enrichment

Perform KEGG pathway enrichment analysis

map_peptides_on_structure

Maps peptides onto a PDB structure or AlphaFold prediction

median_normalisation

Intensity normalisation

network_analysis

Analyse protein interaction network for significant hits

normalise

Intensity normalisation

parallel_create_structure_contact_map

Creates a contact map of all atoms from a structure file (using parall...

parallel_fit_drc_4p

Fitting four-parameter dose response curves (using parallel processing...

peptide_profile_plot

Peptide abundance profile plot

peptide_type

Assign peptide type

plot_drc_4p

Perform gene ontology enrichment analysis

plot_peptide_profiles

Peptide abundance profile plot

plot_pval_distribution

Plot histogram of p-value distribution

predict_alphafold_domain

Predict protein domains of AlphaFold predictions

pval_distribution_plot

Plot histogram of p-value distribution

qc_charge_states

Check charge state distribution

qc_contaminants

Percentage of contaminants per sample

qc_cvs

Check CV distribution

qc_data_completeness

Data completeness

qc_ids

Check number of precursor, peptide or protein IDs

qc_intensity_distribution

Check intensity distribution per sample and overall

qc_median_intensities

Median run intensities

qc_missed_cleavages

Check missed cleavages

qc_pca

Plot principal component analysis

qc_peak_width

Peak width over retention time

qc_peptide_type

Check peptide type percentage share

qc_proteome_coverage

Proteome coverage per sample and total

qc_ranked_intensities

Check ranked intensities

qc_sample_correlation

Correlation based hirachical clustering of samples

qc_sequence_coverage

Protein coverage distribution

randomise_queue

Randomise samples in MS queue

read_protti

Read, clean and convert

replace_identified_by_x

Replace identified positions in protein sequence by "x"

scale_protti

Scaling a vector

sequence_coverage

Protein sequence coverage

split_metal_name

Convert metal names to search pattern

treatment_enrichment

Check treatment enrichment

try_query

Query from URL

ttest_protti

Perform Welch's t-test

volcano_plot

Volcano plot

volcano_protti

Volcano plot

woods_plot

Woods' plot

Useful functions and workflows for proteomics quality control and data analysis of both limited proteolysis-coupled mass spectrometry (LiP-MS) (Feng et. al. (2014) <doi:10.1038/nbt.2999>) and regular bottom-up proteomics experiments. Data generated with search tools such as 'Spectronaut', 'MaxQuant' and 'Proteome Discover' can be easily used due to flexibility of functions.

  • Maintainer: Jan-Philipp Quast
  • License: MIT + file LICENSE
  • Last published: 2024-10-21