Description Usage Arguments Details Value Author(s) References See Also Examples
Estimation of Absolute Protein Quantities of Unlabeled Samples by Targeted Mass Spectrometry.
1 2 3 4 5 6 7 8 9 10 11 | ## Default S3 method:
ALF(data, report_filename="ALF_report.pdf",
prediction_filename="ALF_prediction.csv", peptide_methods = c("top"),
peptide_topx = c(1,2,3), peptide_strictness = "loose",
peptide_summary = "mean", transition_topx = c(1,2,3),
transition_strictness = "loose", transition_summary = "sum", fasta = NA,
apex_model = NA, combine_precursors = FALSE, combine_peptide_sequences = FALSE,
consensus_proteins = TRUE, consensus_peptides = TRUE, consensus_transitions = TRUE,
scampi_method = "LSE", scampi_iterations = 10, scampi_outliers = FALSE,
scampi_outliers_iterations = 2, scampi_outliers_threshold = 2,
cval_method = "boot", cval_mcx = 1000, ...)
|
data |
a mandatory data frame containing the columns |
report_filename |
the path and filename of the PDF report. |
prediction_filename |
the path and filename of the predictions of the optimal model. |
peptide_methods |
a vecter containing a combination of |
peptide_topx |
( |
peptide_strictness |
( |
peptide_summary |
( |
transition_topx |
a positive integer value of the top x transitions to consider for transition to peptide intensity estimation methods. |
transition_strictness |
whether |
transition_summary |
how to summarize the transition intensities: |
fasta |
( |
apex_model |
( |
combine_precursors |
whether to sum all precursors of the same peptide. |
combine_peptide_sequences |
whether to sum all variants (modifications) of the same peptide sequence. |
consensus_proteins |
if multiple runs are provided, select identical proteins among all runs. |
consensus_peptides |
if multiple runs are provided, select identical peptides among all runs. |
consensus_transitions |
if multiple runs are provided, select identical transitions among all runs. |
scampi_method |
(SCAMPI only:) Describes which method should be used for the parameter estimation. Available: method="LSE", method="MLE". See details of runScampi or iterateScampi. |
scampi_iterations |
(SCAMPI only:) Only used with scampi_method="MLE". See details of runScampi or iterateScampi. |
scampi_outliers |
(SCAMPI only:) Whether runScampi (FALSE) or iterateScampi (TRUE) should be used. See details of runScampi or iterateScampi. |
scampi_outliers_iterations |
(SCAMPI only:) Number of estimation/outlier-removal iterations to be performed. See details of iterateScampi. |
scampi_outliers_threshold |
(SCAMPI only:) Constant to tune the outlier selection process. See details of iterateScampi. |
cval_method |
a method for doing crossvalidation: |
cval_mcx |
a positive integer value of the number of folds for cross-validation. |
... |
future extensions. |
The ALF module enables model selection for TopN transitions and peptides for protein quantification (Ludwig et al., 2012). The workflow is completely automated and a report and prediction (using the best model) is generated.
The reports specified in the function call.
George Rosenberger gr2578@cumc.columbia.edu
Ludwig, C., Claassen, M., Schmidt, A. \& Aebersold, R. Estimation of Absolute Protein Quantities of Unlabeled Samples by Selected Reaction Monitoring Mass Spectrometry. Molecular \& Cellular Proteomics 11, M111.013987-M111.013987 (2012).
import
, ProteinInference
, AbsoluteQuantification
, APEX
, apexFeatures
, proteotypic
1 2 3 4 5 6 7 | ## Not run: data(UPS2MS)
## Not run: ALF(UPS2_SRM)
## Not run: data(LUDWIGMS)
## Not run: ALF(LUDWIG_SRM)
|
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