isolNAneighb

(matrix or data.frame) main data (may contain <code>NA</code>)

(character or factor) grouping of columns of 'mat', replicate association

(integer) maximum count of NAs to consider separately (higher ones will be counted/pooled as maxHi)

maxHi

(logical) check at beginning if executing this function is useful (presence any <code>NA</code>)

iniCheck

silent

(character) allow easier tracking of message(s) produced

callFrom

This functions extracts all replicate-values where at least one of the replicates is <code>NA</code>. 
Then, the non-<code>NA</code> values are sorted by the number of <code>NA</code>s which occored in this group of replicates.
A list with all <code>NA</code>-neighbours organized by the number of <code>NA</code>s gets returned.

Data analysis of proteomics experiments by mass spectrometry is supported by this collection of functions mostly dedicated to the analysis of (bottom-up) quantitative (XIC) data.
Fasta-formatted proteomes (eg from UniProt Consortium <doi:10.1093/nar/gky1049>) can be read with automatic parsing and multiple annotation types (like species origin, abbreviated gene names, etc) extracted.
Quantitative proteomics measurements frequently contain multiple NA values, due to physical absence of given peptides in some samples, limitations in sensitivity or other reasons.
The functions provided here help to inspect graphically the data to investigate the nature of NA-values via their respective replicate measurements and to help/confirm the choice of NA-replacement by low random values.
Dedicated filtering and statistical testing using the framework of package 'limma' <doi:10.18129/B9.bioc.limma> can be run, enhanced by multiple rounds of NA-replacements to provide robustness towards rare stochastic events.
Multi-species samples, as frequently used in benchmark-tests (eg Navarro et al 2016 <doi:10.1038/nbt.3685>, Ramus et al 2016 <doi:10.1016/j.jprot.2015.11.011>), can be run with special options separating
the data into sub-groups during normalization and testing.
As example the data-set from Ramus et al 2016 <doi:10.1016/j.jprot.2015.11.011>) is provided quantified by MaxQuant (Tyanova et al 2016 <doi:10.1038/nprot.2016.136>), ProteomeDiscoverer,
OpenMS (<doi:10.1038/nmeth.3959>) and Proline (Bouyssie et al 2020 <doi:10.1093/bioinformatics/btaa118>). Meta-data provided in sdrf format can be integrated to the analysis.
Subsequently, ROC curves (Hand and Till 2001 <doi:10.1023/A:1010920819831>) can be constructed to compare multiple analysis approaches.

isolNAneighb: Isolate NA-neighbours

Description

Usage

Arguments

Value

See Also

Examples