README.md

In ncGTW: Alignment of LC-MS Profiles by Neighbor-wise Compound-specific Graphical Time Warping with Misalignment Detection

ncGTW

The purpose of ncGTW is to detect and fix the bad alignments in the LC-MS data. Currently, ncGTW is implemented in a R-package as a plug-in for XCMS. That is, ncGTW can detect the misaligned feature groups from XCMS and realign them. After that, XCMS can use the realigned data from XCMS for more accurate grouping and peak-filling.

Installation

You can install the latest version of ncGTW from GitHub by

devtools::install_github("ChiungTingWu/ncGTW")

or from Bioconductor by

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("ncGTW")

Algorithm overview

ncGTW detects the misaligned features with two criterions. First, ncGTW algorithm estimates the p-value of each feature using higher resolution alignment result, where the p-value is given by the null hypothesis with accurate alignment. Second, we identifies all features with sufficiently small p-values and disjoint sample subsets. Then, ncGTW algorithm matches the neighboring features to the corresponding features produced by lower resolution alignment, and consider realigning these features.

To realign the misaligned features, we proposed a new multiple alignment method, which is reference free and can incorporate the structure information in the dataset. There are two core ideas. First, instead of set a certain reference, ncGTW performs all possible pairwise alignments between each two sample with the structure information in the dataset. Second, with all the pairwise alignment as constraints, ncGTW estimates the warping functions for all sample to a coordinate.

ncGTW documentation built on Nov. 8, 2020, 8:08 p.m.