The MSnID is a convenience class for manipulating the MS/MS search results.
● Data Source:
BioConductor
● Keywords: classes
● Alias: MSnID, MSnID-class, class:MSnID
●
0 images
|
|
Extracts MS/MS ID data from mzIdentML (leveraging mzID package) or text files. After collating the search results from multiple datasets it assesses their identification quality and optimize filtering criteria to achieve the maximal identifications at a user specified false discovery rate. Additional utilities include:
● Data Source:
BioConductor
● Keywords: package
● Alias: MSnID-package
●
0 images
|
The MSnIDFilter is a convenience class for manipulating the MS/MS filter for MS/MS results.
● Data Source:
BioConductor
● Keywords: classes
● Alias: MSnIDFilter, MSnIDFilter-class, class:MSnIDFilter
●
0 images
|
accessions
(Package: MSnID) :
Non-redundant list of accession (protein) identifiers
Returns the non-redundant list of accession (protein) identifiers from the MSnID object. Most of the times accessions and proteins have the same meaning. However, there are cases, for example use of 6-frame stop-to-stop translation as FASTA file, where the entries are called with general term accessions rather then proteins. Currently, accessions and proteins have the same meaning in MSnID.
● Data Source:
BioConductor
● Keywords:
● Alias: accessions, proteins
●
0 images
|
apply_filter
(Package: MSnID) :
Filters the MS/MS identifications
Filter out peptide-to-spectrum MS/MS identifications.
● Data Source:
BioConductor
● Keywords:
● Alias: apply_filter, apply_filter,MSnID,MSnIDFilter-method, apply_filter,MSnID,character-method
●
0 images
|
assess_missed_cleavages
(Package: MSnID) :
Counts the missing cleavage sites within the peptides sequence
Bottom-up proteomics approaches utilize endoproteases or chemical agents to digest proteins into smaller fragments called peptides. The enzymes recognize short amino acid motifs and cleave along the peptide bonds. Chemical agents such as CNBr also possess amino acid cleavage specificity. In real-world not every cleavage site get cleaved during the sample processing. Therefore settings of MS/MS search engines quite often explictly allow up to a certain number missed clevage sites per peptide sequence.
● Data Source:
BioConductor
● Keywords:
● Alias: assess_missed_cleavages
●
0 images
|
assess_termini
(Package: MSnID) :
Checks if the peptide termini conforms with cleavage specificity
Bottom-up proteomics approaches utilize endoproteases or chemical agents to digest proteins into smaller fragments called peptides. The enzymes recognize short amino acid motifs and cleave along the peptide bonds. Chemical agents such as CNBr also possesses amino acid cleavage specificity.
● Data Source:
BioConductor
● Keywords:
● Alias: assess_termini
●
0 images
|
correct_peak_selection
(Package: MSnID) :
Corrects wrong selection of monoisotopic peak
In a typical setting instruments select ions for fragmentation primarily based on ion intensity. For low molecular weight peptides the most intense peak usually corresponds to monoisotopic peak (that is only C12 carbon isotopes). With increase of molecular weight, instensity of monoisotopic peak becomes smaller relatively to heavier peptide isotopes (that is containing one or a few C13 isotopes).
● Data Source:
BioConductor
● Keywords:
● Alias: correct_peak_selection
●
2 images
|
evaluate_filter
(Package: MSnID) :
Filters the MS/MS identifications
Filter out peptide-to-spectrum MS/MS identifications.
● Data Source:
BioConductor
● Keywords:
● Alias: evaluate_filter
●
0 images
|
id_quality
(Package: MSnID) :
Identification quality
Reports quality for a given level of identification (spectra, peptide or protein).
● Data Source:
BioConductor
● Keywords:
● Alias: id_quality
●
0 images
|
providing 
.