Classification (BioFSharp) | BioFSharp

Classification Module

Namespace: BioFSharp.ML
Assembly: BioFSharp.ML.dll
Parent Module: DPPOP

Contains functions to extract the features used in dppop to classify peptides for observability prediction

Functions and values

Function or value	Description
`createDigestionEfficiencyMapFromFasta fa` Full Usage: `createDigestionEfficiencyMapFromFasta fa` Parameters: fa : `FastaItem<BioArray<AminoAcid>> seq` Returns: `Map<(string * AminoAcidSymbol[]), (float * float * float)>`	returns a map mapping from a (proteinIDsequence) touple to the three digestion efficiency scores in the form of a (floatfloatfloat) tuple from the input fasta item collection fa : `FastaItem<BioArray<AminoAcid>> seq` Returns: `Map<(string AminoAcidSymbol[]), (float * float * float)>`
`digestTryptic aminoAcidSeq` Full Usage: `digestTryptic aminoAcidSeq` Parameters: aminoAcidSeq : `BioArray<AminoAcid>` Returns: `AminoAcid[] seq`	Tryptic Digestion2 of an amino acid sequence with the settings used for the dppop web API aminoAcidSeq : `BioArray<AminoAcid>` Returns: `AminoAcid[] seq`
`digestTrypticWith maxMissCleavages minPeptideLength aminoAcidSeq` Full Usage: `digestTrypticWith maxMissCleavages minPeptideLength aminoAcidSeq` Parameters: maxMissCleavages : `int` minPeptideLength : `int` aminoAcidSeq : `BioArray<AminoAcid>` Returns: `AminoAcid[] seq`	Tryptic digestion of an amino acid sequence with the ability to control the maximal amount of misscleavages and filtering of a minimal peptide length maxMissCleavages : `int` minPeptideLength : `int` aminoAcidSeq : `BioArray<AminoAcid>` Returns: `AminoAcid[] seq`
`getDistinctTrypticPeptidesFromFasta fa` Full Usage: `getDistinctTrypticPeptidesFromFasta fa` Parameters: fa : `FastaItem<BioArray<AminoAcid>> seq` Returns: `Set<string>`	Returns a distinct set of peptides that map uniquely to a single protein from the given fasta input fa : `FastaItem<BioArray<AminoAcid>> seq` Returns: `Set<string>`
`getDistinctTrypticPeptidesFromFastaFile filePath` Full Usage: `getDistinctTrypticPeptidesFromFastaFile filePath` Parameters: filePath : `string` Returns: `Set<string>`	Returns a distinct set of peptides that map uniquely to a single protein from the given fasta file input filePath : `string` Returns: `Set<string>`
`getPeptideFeatures digestionEfficiencyMap protId peptide` Full Usage: `getPeptideFeatures digestionEfficiencyMap protId peptide` Parameters: digestionEfficiencyMap : `Map<(string * BioArray<AminoAcidSymbol>), (float * float * float)>` protId : `string` peptide : `AminoAcidSymbol[]` Returns: `PredictionInput option`	Returns a PredictionInput record type for the input peptide containing the calculated feature vector given a digestion efficiency map and the proteinId the peptide maps to digestionEfficiencyMap : `Map<(string * BioArray<AminoAcidSymbol>), (float * float * float)>` protId : `string` peptide : `AminoAcidSymbol[]` Returns: `PredictionInput option`
`getPhysicochemicalProperties peptide` Full Usage: `getPhysicochemicalProperties peptide` Parameters: peptide : `BioArray<AminoAcidSymbol>` Returns: `float[]`	get the physicochemical properties of a peptide: length, MolecularWeight, NetCharge, PositiveCharge, NegativeCharge, piI, Relative frewuencies of polar, hydrophobic, and negatively charge amino acids peptide : `BioArray<AminoAcidSymbol>` Returns: `float[]`
`zNormalizeNonPlantFeatureVector features` Full Usage: `zNormalizeNonPlantFeatureVector features` Parameters: features : `PredictionInput` Returns: `PredictionInput`	returns the z normalized version of the input feature vector by using the normalization vector dppop uses for its non-plant model features : `PredictionInput` Returns: `PredictionInput`
`zNormalizePeptideFeaturesBy norm features` Full Usage: `zNormalizePeptideFeaturesBy norm features` Parameters: norm : `(float * float)[]` features : `PredictionInput` Returns: `PredictionInput`	normalizes feature vector given a normalization vector containing tuples of (stDev,mean) of all features across a dataset norm : `(float * float)[]` features : `PredictionInput` Returns: `PredictionInput`
`zNormalizePlantFeatureVector features` Full Usage: `zNormalizePlantFeatureVector features` Parameters: features : `PredictionInput` Returns: `PredictionInput`	returns the z normalized version of the input feature vector by using the normalization vector dppop uses for its plant model features : `PredictionInput` Returns: `PredictionInput`