Package index • prolfquapp

All functions

AnnotationProcessor: AnnotationProcessor
DEAReportGenerator: DEAReportGenerator
DEAnalyse: will replace make_DEA_report
ExternalReader: external reader R6 class for handling external data sources
FragPipe: Methods for reading Fragpipe outputs
MaxQuant: Methods for reading MaxQuant outputs
ProcessingOptions: processing options R6 class
ProjectSpec: project specification R6 class
ProjectStructure: keep track of folder paths and create them if needed
ProlfquAppConfig: R6 class representing ProlfquApp configuration
ProteinAnnotation: Decorates LFQData with a row annotation and some protein specific functions.
QC_generator: QC_generator
add_RevCon(): add REV and zz entries - used for testing
add_contrasts_vec(): add vector of contrasts to annotation data frame
aggregate_data(): dataset transform data
anndata_from_LFQData(): convert lfqdata to anndata
bfabric_url_builder(): build bfabric urls
build_protein_annot(): build Dataset protein annot, defaults are compatible with DIANN
capture_output(): capture output of function to send it to log
column_to_rownames(): convert tibble to data.frame with rownames
compute_IBAQ_values(): compute IBAQ values
copy_DEA_Files(): copy Markdown and runscripts for DEA
copy_DEA_Metabolomics_Files(): copy Markdown and runscripts for DEA
copy_docker_script(): copy dockerfile to run the DEA app
copy_shell_script(): copy shellscript to run the DEA app
dataset_extract_contrasts(): extect contrasts from dataset
dataset_get_functions(): get functions for creating datasets
dataset_protein_annot(): Dataset protein annot
dataset_template_BGS(): create templte dataset for BGS data
dataset_template_FP_TMT(): get dataset annotation template
dataset_template_MAXQUANT(): create template dataset for MAXQUANT data
dataset_template_MSSTATS(): create dataset template from MSStats data.
dataset_template_diann(): create dataset template from DIANN outputs
diann_output_to_peptide(): Create peptide level (stripped sequences) report by aggregating Precursor abundances.
diann_read_output(): read DiaNN diann-output.tsv file
diann_read_output_deprec(): read DiaNN diann-output.tsv file
exp2(): transform lfq data with x^2 - apply if non log data is needed
extract_GN(): extract gene names from uniprot 1sp fasta.headers
extract_contrasts(): extract contrast from annotation file
feature_annotation_collapse_to_single_row(): get best feature annotation.
feature_annotation_get_best_score(): get best feature annotation.
generate_DEA_reports(): Generate differential expression analysis reports
generate_DEA_reports2(): will replace generate_DEA_reports
get_BGS_files(): get BGS and fasta file location in folder
get_DIANN_files(): get report.tsv and fasta file location in folder
get_FP_PSM_files(): get psm.tsv and fasta file location in folder
get_FP_multiSite_files(): get report.tsv and fasta file location in folder
get_MQ_peptide_files(): get petpide.txt and fasta file location in folder
get_MSstats_files(): get petpide.txt and fasta file location in folder
get_annot_from_fasta(): get_annot_from_fasta
get_config(): get configuration from yaml file or create default configuration
get_dummy_files(): get_dummy_files
get_formula(): will generates formula
get_mzMine_files(): get mzmine fliles
get_procfuncs(): Get all processing functions from all packages
list_to_R6_app_config(): read minimal yaml and convert to R6 object
make_DEA_config(): create GRP2 configuration. Use this function if there is no Yaml Input.
make_DEA_config_R6(): create GRP2 configuration for differential expression analysis Use this function if there is no Yaml Input.
make_DEA_report() render_DEA(): Create DEA report in html and write data to xlsx table
make_DEA_report2(): make DEA
make_SummarizedExperiment(): Convert prolfqua differential expression analysis results to SummarizedExperiment
make_annotated_experiment(): make lfqdata with row annotation
make_feature_annotation(): get feature annotation.
massage_CD(): massage CD output compound table.
normalize_path(): Function to normalize paths for both Windows and Linux
nr_tryptic_peptides(): Compute number of tryptic peptides
plot_abundance_vs_percent(): Plot relative protein abundance as a function of rank by abundance
preprocess_BGS(): preprocess DIANN ouput, filter by q_value and nr_peptides
preprocess_CD(): load compound discoverer (CD) files
preprocess_DIANN(): preprocess DIANN ouput, filter by q_value and nr_peptides
preprocess_FP_PSM(): preprocess FP psm, filter by purity_threshold and PeptideProphetProb
preprocess_MQ_peptide(): preprocess MQ peptide
preprocess_MSstats(): preprocess MSstats file coming from FragPipe
preprocess_MSstats_FPDIA(): preprocess MSstats fragpipe
preprocess_dummy(): preprocess_dummy
preprocess_mzMine(): preprocess mzMine input
preprocess_software(): collects preprocess methods for various software
prolfqua_preprocess_functions: Mapping of software to string representations of functions and arguments Preprocess Functions Mapping
read_BF_yamlR6(): read yaml file and convert to R6 configuration object
read_BGS(): get BGS and fasta file location in folder
read_annotation(): read annotation files
read_msstats(): read MSstats.csv files and rollup to ProteinSequence level.
read_table_data(): read dataset file in csv, tsv or xlsx format
read_yaml_deprec(): read yaml file
sanitize_grouping_var(): Sanitize grouping variable in annotation file
set_lib_path(): set library path with logging
set_list_to_R6(): set arguments in list config to r6obj
sim_data_protAnnot(): simulate peptdata and fitting protein annotation for testing
sync_opt_config(): Synchronize opt and config
tidy_FragPipe_psm(): read psm.tsv produced by FragPipe and convert into long format
tidy_FragPipe_psm_V2(): read psm.tsv produced by FragPipe and convert into long format
tidy_mzMineFeatures(): convert mzmine features to tidy table
transform_lfqdata(): transform lfq data using robscale, vsn or log2, Assumes that data is not transformed (still needs log2 transformation)
writeLinesPaired(): nice plot for paired analysis
write_DEA(): Write differential expression analysis results
write_DEA_all(): Generate differential expression analysis reports
write_annotation_file(): Write dataset to file in csv, tsv, or xlsx format
write_index_html(): write index.html file with links to all relevant files:
zipdir_name(): Generate zip directory name based on project information and date