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

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.

Functions (59)

anova_protti

Perform ANOVA

assign_missingness

Assignment of missingness types

barcode_plot

Barcode plot

calculate_imputation

Sampling of values for imputation

calculate_protein_abundance

Label-free protein quantification

create_queue

Creates a mass spectrometer queue for Xcalibur

create_synthetic_data

Creates a synthetic limited proteolysis proteomics dataset

diff_abundance

Calculate differential abundance between conditions

drc_4p

Dose response curve helper function

extract_metal_binders

Extract metal-bind protein information from UniProt

fetch_chebi

Fetch ChEBI database information

fetch_go

Fetch gene ontology information from geneontology.org

fetch_kegg

Fetch KEGG pathway data from KEGG

fetch_mobidb

Fetch protein disorder information from MobiDB

fetch_uniprot

Fetch protein data from UniProt

fetch_uniprot_proteome

Fetch proteome data from UniProt

filter_cv

Data filtering based on coefficients of variation (CV)

find_all_subs

Find all ChEBI sub IDs of an ID

find_chebis

Find ChEBI IDs for name patterns

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

median_normalisation

Median normalisation

network_analysis

Analyse protein interaction network for significant hits

parallel_fit_drc_4p

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

peptide_type

Assign peptide type

plot_drc_4p

Plotting of four-parameter dose response curves

plot_peptide_profiles

Peptide abundance profile plot

plot_pval_distribution

Plot histogram of p-value distribution

protti_colours

Colour scheme for protti

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_sample_correlation

Correlation based hirachical clustering of samples

qc_sequence_coverage

Protein coverage distribution

randomise_queue

Randomise samples in MS queue

rapamycin_10uM

Rapamycin 10 uM example data

rapamycin_dose_response

Rapamycin dose response example data

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_protti

Volcano plot

woods_plot

Wood's plot

protti

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

v0.1.1

MIT + file LICENSE

Authors

Jan-Philipp Quast [aut, cre], Dina Schuster [aut], ETH Zurich [cph, fnd]

Initial release

protti

Functions (59)

protti

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