R/dataDoc.R
In Vitek-Lab/MSstatsPTM: Statistical Characterization of Post-translational Modifications
#' Example annotation file for a label-free MaxQuant experiment.
#'
#' Must be manually created by the user and input into the
#' MaxQtoMSstatsPTMFormat converter. Requires the correct columns and maps the
#' experimental desing into the MSstats format. Specify unique bioreplicates for
#' group comparison designs, and the same bioreplicate for repeated measure
#' designs. The columns and descriptions are below.
#'
#' \itemize{
#' \item Run : Run name that matches exactly with MaxQuant run. Used to join
#' evidence and metadata in annotation file.
#' \item Condition : Name of condition that was used for each run.
#' \item BioReplicate : Name of biological replicate. Repeating the same name
#' here will tell MSstatsPTM that the experiment is a repeated measure design.
#' \item Raw.file : Run name that matches exactly with MaxQuant run. Used to join
#' evidence and metadata in annotation file.
#' \item IsotopeLabelType: Name of isotope label. May be all `L` or unique
#' depending on experimental design.
#' }
#'
#' @format A data.table with 5 columns.
#' @examples
#' head(maxq_lf_annotation)
"maxq_lf_annotation"
#' Example MaxQuant evidence file from the output of a label free experiment
#'
#' Experiment was performed by the Olsen lab and published on Nat. Commun.
#' (citation below).
#'
#' Bekker-Jensen, D.B., Bernhardt, O.M., Hogrebe, A. et al. Rapid and
#' site-specific deep phosphoproteome profiling by data-independent acquisition
#' without the need for spectral libraries. Nat Commun 11, 787 (2020).
#' https://doi.org/10.1038/s41467-020-14609-1
#'
#' The experiment was processed using MaxQuant by the computational proteomics
#' team at Pfizer (Liang Xue and Pierre Jean).
#'
#' The experiment did not contain a global profiling run, but we show an example
#' of extracting the unmodified peptides and using them in place of the
#' profiling run.
#'
#' @format a data.table with 63 columns and 511 rows, the output of MaxQuant
#' @examples
#' head(maxq_lf_evidence)
"maxq_lf_evidence"
#' Example annotation file for a TMT MaxQuant experiment.
#'
#' Must be manually created by the user and input into the
#' MaxQtoMSstatsPTMFormat converter. Requires the correct columns and maps the
#' experimental desing into the MSstats format. Specify unique bioreplicates for
#' group comparison designs, and the same bioreplicate for repeated measure
#' designs. The columns and descriptions are below.
#'
#' \itemize{
#' \item Run : Run name that matches exactly with MaxQuant run. Used to join
#' evidence and metadata in annotation file.
#' \item Fraction : If multiple fractions were used (i.e. the same mixture
#' split into multiple fractions) enter that here.
#' TechRepMixture : Multiple runs using the same bioreplicate
#' \item Channel : Mixture channel used
#' \item Condition : Name of condition that was used for each run.
#' \item Mixture : The unique mixture (plex) name
#' \item BioReplicate : Name of biological replicate. Repeating the same name
#' here will tell MSstatsPTM that the experiment is a repeated measure design.
#' }
#'
#' @format A data.table with 7 columns.
#' @examples
#' head(maxq_tmt_annotation)
"maxq_tmt_annotation"
#' Example MaxQuant evidence file from the output of a TMT experiment
#'
#' Experiment was performed by the Olsen lab and published on Nat. Commun.
#' (citation below).
#'
#' Hogrebe, A., von Stechow, L., Bekker-Jensen, D.B. et al. Benchmarking common
#' quantification strategies for large-scale phosphoproteomics. Nat Commun 9,
#' 1045 (2018). https://doi.org/10.1038/s41467-018-03309-6
#'
#' The experiment was processed using MaxQuant by the computational proteomics
#' team at Pfizer (Liang Xue and Pierre Jean).
#'
#' The experiment did not contain a global profiling run, but we show an example
#' of extracting the unmodified peptides and using them in place of the
#' profiling run.
#'
#' @format a data.table with 96 columns and 199 rows, the output of MaxQuant
#' @examples
#' head(maxq_tmt_evidence)
"maxq_tmt_evidence"
#' Example annotation file for a label-free Proteome Discoverer experiment.
#'
#' Must be manually created by the user and input into the
#' PDtoMSstatsPTMFormat converter. Requires the correct columns and maps the
#' experimental desing into the MSstats format. Specify unique bioreplicates for
#' group comparison designs, and the same bioreplicate for repeated measure
#' designs. The columns and descriptions are below.
#'
#' \itemize{
#' \item Run : Run name that matches exactly with PD run. Used to join
#' evidence and metadata in annotation file.
#' \item Condition : Name of condition that was used for each run.
#' \item BioReplicate : Name of biological replicate. Repeating the same name
#' here will tell MSstatsPTM that the experiment is a repeated measure design.
#' }
#'
#' @format A data.table with 3 columns.
#' @examples
#' head(pd_annotation)
"pd_annotation"
#' Example Proteome Discoverer evidence file from the output of a label free experiment
#'
#' Experiment was performed by the Olsen lab and published on Nat. Commun.
#' (citation below).
#'
#' Bekker-Jensen, D.B., Bernhardt, O.M., Hogrebe, A. et al. Rapid and
#' site-specific deep phosphoproteome profiling by data-independent acquisition
#' without the need for spectral libraries. Nat Commun 11, 787 (2020).
#' https://doi.org/10.1038/s41467-020-14609-1
#'
#' The experiment was processed using Proteome Discoverer by the computational
#' proteomics team at Pfizer (Liang Xue and Pierre Jean).
#'
#' The experiment did not contain a global profiling run, but we show an example
#' of extracting the unmodified peptides and using them in place of the
#' profiling run.
#'
#' @format a data.table with 60 columns and 1657 rows, the output of PD
#' @examples
#' head(pd_psm_input)
"pd_psm_input"
#' Example output of Proteome Discoverer converter
#'
#' output using example data provided in package
#'
#' The experiment did not contain a global profiling run, but we show an example
#' of extracting the unmodified peptides and using them in place of the
#' profiling run.
#'
#' @format a list with 2 data.frames
#' @examples
#' head(pd_testing_output)
"pd_testing_output"
#' Example annotation file for a label-free Spectronaut experiment.
#'
#' Must be manually created by the user and input into the
#' SpectronauttoMSstatsPTMFormat converter. Requires the correct columns and
#' maps the experimental desing into the MSstats format. Specify unique
#' bioreplicates for group comparison designs, and the same bioreplicate for
#' repeated measure designs. The columns and descriptions are below.
#'
#' \itemize{
#' \item Run : Run name that matches exactly with Spectronaut run. Used to join
#' evidence and metadata in annotation file.
#' \item Condition : Name of condition that was used for each run.
#' \item BioReplicate : Name of biological replicate. Repeating the same name
#' here will tell MSstatsPTM that the experiment is a repeated measure design.
#' \item Raw.file : Run name that matches exactly with Spectronaut run. Used to join
#' evidence and metadata in annotation file.
#' }
#'
#' @format A data.table with 5 columns.
#' @examples
#' head(spectronaut_annotation)
"spectronaut_annotation"
#' Example Spectronaut evidence file from the output of a label free experiment
#'
#' Experiment was performed by the Olsen lab and published on Nat. Commun.
#' (citation below).
#'
#' Bekker-Jensen, D.B., Bernhardt, O.M., Hogrebe, A. et al. Rapid and
#' site-specific deep phosphoproteome profiling by data-independent acquisition
#' without the need for spectral libraries. Nat Commun 11, 787 (2020).
#' https://doi.org/10.1038/s41467-020-14609-1
#'
#' The experiment was processed using Spectronaut by the computational proteomics
#' team at Pfizer (Liang Xue and Pierre Jean).
#'
#' The experiment did not contain a global profiling run, but we show an example
#' of extracting the unmodified peptides and using them in place of the
#' profiling run.
#'
#' @format a data.table with 23 columns and 2683 rows, the output of Spectronaut
#' @examples
#' head(spectronaut_input)
"spectronaut_input"
#' Example annotation file for a TMT FragPipe experiment.
#'
#' Automatically created by FragPipe, manually checked by the user and input
#' into the FragPipetoMSstatsPTMFormat converter. Requires the correct columns
#' and maps the experimental desing into the MSstats format. Specify unique
#' bioreplicates for group comparison designs, and the same bioreplicate for
#' repeated measure designs. The columns and descriptions are below.
#'
#' \itemize{
#' \item Run : Run name that matches exactly with FragPipe run. Used to join
#' evidence and metadata in annotation file.
#' \item Fraction : If multiple fractions were used (i.e. the same mixture
#' split into multiple fractions) enter that here.
#' TechRepMixture : Multiple runs using the same bioreplicate
#' \item Channel : Mixture channel used
#' \item Condition : Name of condition that was used for each run.
#' \item Mixture : The unique mixture (plex) name
#' \item BioReplicate : Name of biological replicate. Repeating the same name
#' here will tell MSstatsPTM that the experiment is a repeated measure design.
#' }
#'
#' @format A data.table with 7 columns.
#' @examples
#' head(fragpipe_annotation)
"fragpipe_annotation"
#' Example annotation file for a global profiling run TMT FragPipe experiment.
#'
#' Automatically created by FragPipe, manually checked by the user and input
#' into the FragPipetoMSstatsPTMFormat converter. Requires the correct columns
#' and maps the experimental desing into the MSstats format. Specify unique
#' bioreplicates for group comparison designs, and the same bioreplicate for
#' repeated measure designs. The columns and descriptions are below.
#'
#' \itemize{
#' \item Run : Run name that matches exactly with FragPipe run. Used to join
#' evidence and metadata in annotation file.
#' \item Fraction : If multiple fractions were used (i.e. the same mixture
#' split into multiple fractions) enter that here.
#' TechRepMixture : Multiple runs using the same bioreplicate
#' \item Channel : Mixture channel used
#' \item Condition : Name of condition that was used for each run.
#' \item Mixture : The unique mixture (plex) name
#' \item BioReplicate : Name of biological replicate. Repeating the same name
#' here will tell MSstatsPTM that the experiment is a repeated measure design.
#' }
#'
#' @format A data.table with 7 columns.
#' @examples
#' head(fragpipe_annotation_protein)
"fragpipe_annotation_protein"
#' Output of FragPipe TMT PTM experiment
#'
#' This dataset was provided by the FragPipe team at the Nesvilab. It was
#' processed using Philosopher and targeted Phosphorylation.
#'
#' @format A data.table with 29 columns and 246 rows.
#' @examples
#' head(fragpipe_input)
"fragpipe_input"
#' Output of FragPipe TMT global profiling experiment
#'
#' This dataset was provided by the FragPipe team at the Nesvilab. It was
#' processed using Philosopher and targeted Phosphorylation.
#'
#' @format A data.table with 27 columns and 47 rows.
#' @examples
#' head(fragpipe_input_protein)
"fragpipe_input_protein"
#' Example of input PTM dataset for TMT experiments.
#'
#' It can be the output of MSstatsPTM converter MaxQtoMSstatsPTMFormat or other
#' MSstatsTMT converter functions (Please see MSstatsPTM_TMT_Workflow vignette).
#' The dataset is formatted as a list with two data.tables named PTM and
#' PROTEIN. In each data.table the variables are as follows:
#'
#' \itemize{
#' \item ProteinName : Name of protein with modification site mapped in with
#' an underscore. ie "Protein_4_Y474"
#' \item PeptideSequence
#' \item Charge
#' \item PSM
#' \item Mixture : Mixture of samples labeled with different TMT reagents,
#' which can be analyzed in
#' a single mass spectrometry experiment. If the channal doesn't have sample,
#' please add `Empty' under Condition.
#' \item TechRepMixture : Technical replicate of one mixture. One mixture may
#' have multiple technical replicates.
#' For example, if `TechRepMixture' = 1, 2 are the two technical replicates of
#' one mixture, then they should match
#' with same `Mixture' value.
#' \item Run : MS run ID.
#' \item Channel : Labeling information (126, ... 131).
#' \item Condition : Condition (ex. Healthy, Cancer, Time0)
#' \item BioReplicate : Unique ID for biological subject. If the channal
#' doesn't have sample, please add `Empty' under BioReplicate.
#' \item Intensity
#' }
#'
#' @format A list of two data.tables named PTM and PROTEIN with 1716 and 29221
#' rows respectively.
#' @examples
#' head(raw.input.tmt$PTM)
#' head(raw.input.tmt$PROTEIN)
#'
"raw.input.tmt"
#' Example of input PTM dataset for LabelFree/DDA/DIA experiments.
#'
#' It can be the output of MSstatsPTM converter ProgenesistoMSstatsPTMFormat or
#' other MSstats converter functions (Please see MSstatsPTM_LabelFree_Workflow
#' vignette). The dataset is formatted as a list with two data.tables named PTM
#' and PROTEIN. In each data.table the variables are as follows:
#'
#' \itemize{
#' #' \item ProteinName : Name of protein with modification site mapped in with
#' an underscore. ie "Protein_4_Y474"
#' \item PeptideSequence
#' \item Condition : Condition (ex. Healthy, Cancer, Time0)
#' \item BioReplicate : Unique ID for biological subject.
#' \item Run : MS run ID.
#' \item Intensity
#' \item PrecursorCharge
#' \item FragmentIon
#' \item ProductCharge
#' \item IsotopeLabelType
#' }
#'
#' @format A list of two data.tables named PTM and PROTEIN with 1745 and 478
#' rows respectively.
#' @examples
#' head(raw.input$PTM)
#' head(raw.input$PROTEIN)
#'
"raw.input"
#' Example of output from dataSummarizationPTM function for non-TMT data
#'
#' It is made from \code{\link{raw.input}}.
#' It is the output of dataSummarizationPTM function from MSstatsPTM.
#' It should include a list with two names \code{PTM} and \code{PROTEIN}. Each
#' of these list values is also a list with two names \code{ProteinLevelData}
#' and \code{FeatureLevelData}, which correspond to two data.tables.The columns
#' in these two data.tables are listed below. The variables are as follows:
#' \itemize{
#' \item FeatureLevelData : \itemize{
#' \item PROTEIN : Protein ID with modification site mapped in. Ex.
#' Protein_1002_S836
#' \item PEPTIDE : Full peptide with charge
#' \item TRANSITION: Charge
#' \item FEATURE : Combination of Protien, Peptide, and Transition Columns
#' \item LABEL :
#' \item GROUP : Condition (ex. Healthy, Cancer, Time0)
#' \item RUN : Unique ID for technical replicate of one TMT
#' mixture.
#' \item SUBJECT : Unique ID for biological subject.
#' \item FRACTION : Unique Fraction ID
#' \item originalRUN : Run name
#' \item censored :
#' \item INTENSITY : Unique ID for TMT mixture.
#' \item ABUNDANCE : Unique ID for TMT mixture.
#' \item newABUNDANCE : Unique ID for TMT mixture.
#' \item predicted : Unique ID for TMT mixture.
#' }
#' \item ProteinLevelData : \itemize{
#' \item RUN : MS run ID
#' \item Protein : Protein ID with modification site mapped in. Ex.
#' Protein_1002_S836
#' \item LogIntensities: Protein-level summarized abundance
#' \item originalRUN : Labeling information (126, ... 131)
#' \item GROUP : Condition (ex. Healthy, Cancer, Time0)
#' \item SUBJECT : Unique ID for biological subject.
#' \item TotalGroupMeasurements : Unique ID for technical replicate of one TMT
#' mixture.
#' \item NumMeasuredFeature : Unique ID for TMT mixture.
#' \item MissingPercentage : Unique ID for TMT mixture.
#' \item more50missing : Unique ID for TMT mixture.
#' \item NumImputedFeature : Unique ID for TMT mixture.
#' }
#'
#' }
#'
#' @format A list of two lists with four data.tables.
#' @examples
#' head(summary.data)
#'
"summary.data"
#' Example of output from dataSummarizationPTM_TMT function for TMT data
#'
#' It is made from \code{\link{raw.input.tmt}}.
#' It is the output of dataSummarizationPTM_TMT function from MSstatsPTM.
#' It should include a list with two names \code{PTM} and \code{PROTEIN}. Each
#' of these list values is also a list with two names \code{ProteinLevelData}
#' and \code{FeatureLevelData}, which correspond to two data.tables.The columns
#' in these two data.tables are listed below. The variables are as follows:
#' \itemize{
#' \item FeatureLevelData : \itemize{
#' \item ProteinName : MS run ID
#' \item PSM : Protein ID with modification site mapped in. Ex.
#' Protein_1002_S836
#' \item censored: Protein-level summarized abundance
#' \item predicted : Labeling information (126, ... 131)
#' \item log2Intensity : Condition (ex. Healthy, Cancer, Time0)
#' \item Run : Unique ID for biological subject.
#' \item Channel : Unique ID for technical replicate of one TMT
#' mixture.
#' \item BioReplicate : Unique ID for TMT mixture.
#' \item Condition : Unique ID for TMT mixture.
#' \item Mixture : Unique ID for TMT mixture.
#' \item TechRepMixture : Unique ID for TMT mixture.
#' \item PeptideSequence : Unique ID for TMT mixture.
#' \item Charge : Unique ID for TMT mixture.
#' }
#' \item ProteinLevelData : \itemize{
#' \item Mixture : MS run ID
#' \item TechRepMixture : Protein ID with modification site mapped in. Ex.
#' Protein_1002_S836
#' \item Run: Protein-level summarized abundance
#' \item Channel : Labeling information (126, ... 131)
#' \item Protein : Condition (ex. Healthy, Cancer, Time0)
#' \item Abundance : Unique ID for biological subject.
#' \item BioReplicate : Unique ID for technical replicate of one TMT
#' mixture.
#' \item Condition : Unique ID for TMT mixture.
#' }
#'
#' }
#'
#' @format A list of two lists with four data.tables.
#' @examples
#' head(summary.data.tmt)
#'
"summary.data.tmt"
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#' Example annotation file for a label-free MaxQuant experiment.
#'
#' Must be manually created by the user and input into the
#' MaxQtoMSstatsPTMFormat converter. Requires the correct columns and maps the
#' experimental desing into the MSstats format. Specify unique bioreplicates for
#' group comparison designs, and the same bioreplicate for repeated measure
#' designs. The columns and descriptions are below.
#'
#' \itemize{
#' \item Run : Run name that matches exactly with MaxQuant run. Used to join
#' evidence and metadata in annotation file.
#' \item Condition : Name of condition that was used for each run.
#' \item BioReplicate : Name of biological replicate. Repeating the same name
#' here will tell MSstatsPTM that the experiment is a repeated measure design.
#' \item Raw.file : Run name that matches exactly with MaxQuant run. Used to join
#' evidence and metadata in annotation file.
#' \item IsotopeLabelType: Name of isotope label. May be all `L` or unique
#' depending on experimental design.
#' }
#'
#' @format A data.table with 5 columns.
#' @examples
#' head(maxq_lf_annotation)
"maxq_lf_annotation"
#' Example MaxQuant evidence file from the output of a label free experiment
#'
#' Experiment was performed by the Olsen lab and published on Nat. Commun.
#' (citation below).
#'
#' Bekker-Jensen, D.B., Bernhardt, O.M., Hogrebe, A. et al. Rapid and
#' site-specific deep phosphoproteome profiling by data-independent acquisition
#' without the need for spectral libraries. Nat Commun 11, 787 (2020).
#' https://doi.org/10.1038/s41467-020-14609-1
#'
#' The experiment was processed using MaxQuant by the computational proteomics
#' team at Pfizer (Liang Xue and Pierre Jean).
#'
#' The experiment did not contain a global profiling run, but we show an example
#' of extracting the unmodified peptides and using them in place of the
#' profiling run.
#'
#' @format a data.table with 63 columns and 511 rows, the output of MaxQuant
#' @examples
#' head(maxq_lf_evidence)
"maxq_lf_evidence"
#' Example annotation file for a TMT MaxQuant experiment.
#'
#' Must be manually created by the user and input into the
#' MaxQtoMSstatsPTMFormat converter. Requires the correct columns and maps the
#' experimental desing into the MSstats format. Specify unique bioreplicates for
#' group comparison designs, and the same bioreplicate for repeated measure
#' designs. The columns and descriptions are below.
#'
#' \itemize{
#' \item Run : Run name that matches exactly with MaxQuant run. Used to join
#' evidence and metadata in annotation file.
#' \item Fraction : If multiple fractions were used (i.e. the same mixture
#' split into multiple fractions) enter that here.
#' TechRepMixture : Multiple runs using the same bioreplicate
#' \item Channel : Mixture channel used
#' \item Condition : Name of condition that was used for each run.
#' \item Mixture : The unique mixture (plex) name
#' \item BioReplicate : Name of biological replicate. Repeating the same name
#' here will tell MSstatsPTM that the experiment is a repeated measure design.
#' }
#'
#' @format A data.table with 7 columns.
#' @examples
#' head(maxq_tmt_annotation)
"maxq_tmt_annotation"
#' Example MaxQuant evidence file from the output of a TMT experiment
#'
#' Experiment was performed by the Olsen lab and published on Nat. Commun.
#' (citation below).
#'
#' Hogrebe, A., von Stechow, L., Bekker-Jensen, D.B. et al. Benchmarking common
#' quantification strategies for large-scale phosphoproteomics. Nat Commun 9,
#' 1045 (2018). https://doi.org/10.1038/s41467-018-03309-6
#'
#' The experiment was processed using MaxQuant by the computational proteomics
#' team at Pfizer (Liang Xue and Pierre Jean).
#'
#' The experiment did not contain a global profiling run, but we show an example
#' of extracting the unmodified peptides and using them in place of the
#' profiling run.
#'
#' @format a data.table with 96 columns and 199 rows, the output of MaxQuant
#' @examples
#' head(maxq_tmt_evidence)
"maxq_tmt_evidence"
#' Example annotation file for a label-free Proteome Discoverer experiment.
#'
#' Must be manually created by the user and input into the
#' PDtoMSstatsPTMFormat converter. Requires the correct columns and maps the
#' experimental desing into the MSstats format. Specify unique bioreplicates for
#' group comparison designs, and the same bioreplicate for repeated measure
#' designs. The columns and descriptions are below.
#'
#' \itemize{
#' \item Run : Run name that matches exactly with PD run. Used to join
#' evidence and metadata in annotation file.
#' \item Condition : Name of condition that was used for each run.
#' \item BioReplicate : Name of biological replicate. Repeating the same name
#' here will tell MSstatsPTM that the experiment is a repeated measure design.
#' }
#'
#' @format A data.table with 3 columns.
#' @examples
#' head(pd_annotation)
"pd_annotation"
#' Example Proteome Discoverer evidence file from the output of a label free experiment
#'
#' Experiment was performed by the Olsen lab and published on Nat. Commun.
#' (citation below).
#'
#' Bekker-Jensen, D.B., Bernhardt, O.M., Hogrebe, A. et al. Rapid and
#' site-specific deep phosphoproteome profiling by data-independent acquisition
#' without the need for spectral libraries. Nat Commun 11, 787 (2020).
#' https://doi.org/10.1038/s41467-020-14609-1
#'
#' The experiment was processed using Proteome Discoverer by the computational
#' proteomics team at Pfizer (Liang Xue and Pierre Jean).
#'
#' The experiment did not contain a global profiling run, but we show an example
#' of extracting the unmodified peptides and using them in place of the
#' profiling run.
#'
#' @format a data.table with 60 columns and 1657 rows, the output of PD
#' @examples
#' head(pd_psm_input)
"pd_psm_input"
#' Example output of Proteome Discoverer converter
#'
#' output using example data provided in package
#'
#' The experiment did not contain a global profiling run, but we show an example
#' of extracting the unmodified peptides and using them in place of the
#' profiling run.
#'
#' @format a list with 2 data.frames
#' @examples
#' head(pd_testing_output)
"pd_testing_output"
#' Example annotation file for a label-free Spectronaut experiment.
#'
#' Must be manually created by the user and input into the
#' SpectronauttoMSstatsPTMFormat converter. Requires the correct columns and
#' maps the experimental desing into the MSstats format. Specify unique
#' bioreplicates for group comparison designs, and the same bioreplicate for
#' repeated measure designs. The columns and descriptions are below.
#'
#' \itemize{
#' \item Run : Run name that matches exactly with Spectronaut run. Used to join
#' evidence and metadata in annotation file.
#' \item Condition : Name of condition that was used for each run.
#' \item BioReplicate : Name of biological replicate. Repeating the same name
#' here will tell MSstatsPTM that the experiment is a repeated measure design.
#' \item Raw.file : Run name that matches exactly with Spectronaut run. Used to join
#' evidence and metadata in annotation file.
#' }
#'
#' @format A data.table with 5 columns.
#' @examples
#' head(spectronaut_annotation)
"spectronaut_annotation"
#' Example Spectronaut evidence file from the output of a label free experiment
#'
#' Experiment was performed by the Olsen lab and published on Nat. Commun.
#' (citation below).
#'
#' Bekker-Jensen, D.B., Bernhardt, O.M., Hogrebe, A. et al. Rapid and
#' site-specific deep phosphoproteome profiling by data-independent acquisition
#' without the need for spectral libraries. Nat Commun 11, 787 (2020).
#' https://doi.org/10.1038/s41467-020-14609-1
#'
#' The experiment was processed using Spectronaut by the computational proteomics
#' team at Pfizer (Liang Xue and Pierre Jean).
#'
#' The experiment did not contain a global profiling run, but we show an example
#' of extracting the unmodified peptides and using them in place of the
#' profiling run.
#'
#' @format a data.table with 23 columns and 2683 rows, the output of Spectronaut
#' @examples
#' head(spectronaut_input)
"spectronaut_input"
#' Example annotation file for a TMT FragPipe experiment.
#'
#' Automatically created by FragPipe, manually checked by the user and input
#' into the FragPipetoMSstatsPTMFormat converter. Requires the correct columns
#' and maps the experimental desing into the MSstats format. Specify unique
#' bioreplicates for group comparison designs, and the same bioreplicate for
#' repeated measure designs. The columns and descriptions are below.
#'
#' \itemize{
#' \item Run : Run name that matches exactly with FragPipe run. Used to join
#' evidence and metadata in annotation file.
#' \item Fraction : If multiple fractions were used (i.e. the same mixture
#' split into multiple fractions) enter that here.
#' TechRepMixture : Multiple runs using the same bioreplicate
#' \item Channel : Mixture channel used
#' \item Condition : Name of condition that was used for each run.
#' \item Mixture : The unique mixture (plex) name
#' \item BioReplicate : Name of biological replicate. Repeating the same name
#' here will tell MSstatsPTM that the experiment is a repeated measure design.
#' }
#'
#' @format A data.table with 7 columns.
#' @examples
#' head(fragpipe_annotation)
"fragpipe_annotation"
#' Example annotation file for a global profiling run TMT FragPipe experiment.
#'
#' Automatically created by FragPipe, manually checked by the user and input
#' into the FragPipetoMSstatsPTMFormat converter. Requires the correct columns
#' and maps the experimental desing into the MSstats format. Specify unique
#' bioreplicates for group comparison designs, and the same bioreplicate for
#' repeated measure designs. The columns and descriptions are below.
#'
#' \itemize{
#' \item Run : Run name that matches exactly with FragPipe run. Used to join
#' evidence and metadata in annotation file.
#' \item Fraction : If multiple fractions were used (i.e. the same mixture
#' split into multiple fractions) enter that here.
#' TechRepMixture : Multiple runs using the same bioreplicate
#' \item Channel : Mixture channel used
#' \item Condition : Name of condition that was used for each run.
#' \item Mixture : The unique mixture (plex) name
#' \item BioReplicate : Name of biological replicate. Repeating the same name
#' here will tell MSstatsPTM that the experiment is a repeated measure design.
#' }
#'
#' @format A data.table with 7 columns.
#' @examples
#' head(fragpipe_annotation_protein)
"fragpipe_annotation_protein"
#' Output of FragPipe TMT PTM experiment
#'
#' This dataset was provided by the FragPipe team at the Nesvilab. It was
#' processed using Philosopher and targeted Phosphorylation.
#'
#' @format A data.table with 29 columns and 246 rows.
#' @examples
#' head(fragpipe_input)
"fragpipe_input"
#' Output of FragPipe TMT global profiling experiment
#'
#' This dataset was provided by the FragPipe team at the Nesvilab. It was
#' processed using Philosopher and targeted Phosphorylation.
#'
#' @format A data.table with 27 columns and 47 rows.
#' @examples
#' head(fragpipe_input_protein)
"fragpipe_input_protein"
#' Example of input PTM dataset for TMT experiments.
#'
#' It can be the output of MSstatsPTM converter MaxQtoMSstatsPTMFormat or other
#' MSstatsTMT converter functions (Please see MSstatsPTM_TMT_Workflow vignette).
#' The dataset is formatted as a list with two data.tables named PTM and
#' PROTEIN. In each data.table the variables are as follows:
#'
#' \itemize{
#' \item ProteinName : Name of protein with modification site mapped in with
#' an underscore. ie "Protein_4_Y474"
#' \item PeptideSequence
#' \item Charge
#' \item PSM
#' \item Mixture : Mixture of samples labeled with different TMT reagents,
#' which can be analyzed in
#' a single mass spectrometry experiment. If the channal doesn't have sample,
#' please add `Empty' under Condition.
#' \item TechRepMixture : Technical replicate of one mixture. One mixture may
#' have multiple technical replicates.
#' For example, if `TechRepMixture' = 1, 2 are the two technical replicates of
#' one mixture, then they should match
#' with same `Mixture' value.
#' \item Run : MS run ID.
#' \item Channel : Labeling information (126, ... 131).
#' \item Condition : Condition (ex. Healthy, Cancer, Time0)
#' \item BioReplicate : Unique ID for biological subject. If the channal
#' doesn't have sample, please add `Empty' under BioReplicate.
#' \item Intensity
#' }
#'
#' @format A list of two data.tables named PTM and PROTEIN with 1716 and 29221
#' rows respectively.
#' @examples
#' head(raw.input.tmt$PTM)
#' head(raw.input.tmt$PROTEIN)
#'
"raw.input.tmt"
#' Example of input PTM dataset for LabelFree/DDA/DIA experiments.
#'
#' It can be the output of MSstatsPTM converter ProgenesistoMSstatsPTMFormat or
#' other MSstats converter functions (Please see MSstatsPTM_LabelFree_Workflow
#' vignette). The dataset is formatted as a list with two data.tables named PTM
#' and PROTEIN. In each data.table the variables are as follows:
#'
#' \itemize{
#' #' \item ProteinName : Name of protein with modification site mapped in with
#' an underscore. ie "Protein_4_Y474"
#' \item PeptideSequence
#' \item Condition : Condition (ex. Healthy, Cancer, Time0)
#' \item BioReplicate : Unique ID for biological subject.
#' \item Run : MS run ID.
#' \item Intensity
#' \item PrecursorCharge
#' \item FragmentIon
#' \item ProductCharge
#' \item IsotopeLabelType
#' }
#'
#' @format A list of two data.tables named PTM and PROTEIN with 1745 and 478
#' rows respectively.
#' @examples
#' head(raw.input$PTM)
#' head(raw.input$PROTEIN)
#'
"raw.input"
#' Example of output from dataSummarizationPTM function for non-TMT data
#'
#' It is made from \code{\link{raw.input}}.
#' It is the output of dataSummarizationPTM function from MSstatsPTM.
#' It should include a list with two names \code{PTM} and \code{PROTEIN}. Each
#' of these list values is also a list with two names \code{ProteinLevelData}
#' and \code{FeatureLevelData}, which correspond to two data.tables.The columns
#' in these two data.tables are listed below. The variables are as follows:
#' \itemize{
#' \item FeatureLevelData : \itemize{
#' \item PROTEIN : Protein ID with modification site mapped in. Ex.
#' Protein_1002_S836
#' \item PEPTIDE : Full peptide with charge
#' \item TRANSITION: Charge
#' \item FEATURE : Combination of Protien, Peptide, and Transition Columns
#' \item LABEL :
#' \item GROUP : Condition (ex. Healthy, Cancer, Time0)
#' \item RUN : Unique ID for technical replicate of one TMT
#' mixture.
#' \item SUBJECT : Unique ID for biological subject.
#' \item FRACTION : Unique Fraction ID
#' \item originalRUN : Run name
#' \item censored :
#' \item INTENSITY : Unique ID for TMT mixture.
#' \item ABUNDANCE : Unique ID for TMT mixture.
#' \item newABUNDANCE : Unique ID for TMT mixture.
#' \item predicted : Unique ID for TMT mixture.
#' }
#' \item ProteinLevelData : \itemize{
#' \item RUN : MS run ID
#' \item Protein : Protein ID with modification site mapped in. Ex.
#' Protein_1002_S836
#' \item LogIntensities: Protein-level summarized abundance
#' \item originalRUN : Labeling information (126, ... 131)
#' \item GROUP : Condition (ex. Healthy, Cancer, Time0)
#' \item SUBJECT : Unique ID for biological subject.
#' \item TotalGroupMeasurements : Unique ID for technical replicate of one TMT
#' mixture.
#' \item NumMeasuredFeature : Unique ID for TMT mixture.
#' \item MissingPercentage : Unique ID for TMT mixture.
#' \item more50missing : Unique ID for TMT mixture.
#' \item NumImputedFeature : Unique ID for TMT mixture.
#' }
#'
#' }
#'
#' @format A list of two lists with four data.tables.
#' @examples
#' head(summary.data)
#'
"summary.data"
#' Example of output from dataSummarizationPTM_TMT function for TMT data
#'
#' It is made from \code{\link{raw.input.tmt}}.
#' It is the output of dataSummarizationPTM_TMT function from MSstatsPTM.
#' It should include a list with two names \code{PTM} and \code{PROTEIN}. Each
#' of these list values is also a list with two names \code{ProteinLevelData}
#' and \code{FeatureLevelData}, which correspond to two data.tables.The columns
#' in these two data.tables are listed below. The variables are as follows:
#' \itemize{
#' \item FeatureLevelData : \itemize{
#' \item ProteinName : MS run ID
#' \item PSM : Protein ID with modification site mapped in. Ex.
#' Protein_1002_S836
#' \item censored: Protein-level summarized abundance
#' \item predicted : Labeling information (126, ... 131)
#' \item log2Intensity : Condition (ex. Healthy, Cancer, Time0)
#' \item Run : Unique ID for biological subject.
#' \item Channel : Unique ID for technical replicate of one TMT
#' mixture.
#' \item BioReplicate : Unique ID for TMT mixture.
#' \item Condition : Unique ID for TMT mixture.
#' \item Mixture : Unique ID for TMT mixture.
#' \item TechRepMixture : Unique ID for TMT mixture.
#' \item PeptideSequence : Unique ID for TMT mixture.
#' \item Charge : Unique ID for TMT mixture.
#' }
#' \item ProteinLevelData : \itemize{
#' \item Mixture : MS run ID
#' \item TechRepMixture : Protein ID with modification site mapped in. Ex.
#' Protein_1002_S836
#' \item Run: Protein-level summarized abundance
#' \item Channel : Labeling information (126, ... 131)
#' \item Protein : Condition (ex. Healthy, Cancer, Time0)
#' \item Abundance : Unique ID for biological subject.
#' \item BioReplicate : Unique ID for technical replicate of one TMT
#' mixture.
#' \item Condition : Unique ID for TMT mixture.
#' }
#'
#' }
#'
#' @format A list of two lists with four data.tables.
#' @examples
#' head(summary.data.tmt)
#'
"summary.data.tmt"
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