Figure 4.

xMSanalyzer improves the sensitivity of feature detection without compromising data quality. a) Histograms showing number of peaks with ranges of percent intensity differences (PID) for LC/MS profile alignments using apLCMS (left) and xMSanalyzer (right). The results show that the xMSanalyzer routine allows detection of more quantitatively reproducible features; b) Histograms showing the average log2 intensity levels in features with median PID less than 30% detected using apLCMS (left) and xMSanalyzer (right) in Sample Set 2, Column A. xMSanalyzer not only improves the overall quantitative reproducibility of features, but also allows detection of reliable low abundance features.

Uppal et al. BMC Bioinformatics 2013 14:15   doi:10.1186/1471-2105-14-15
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