There are several charts displayed via the "--showcharts" option during matching that will help you
to understand how well the AMT matching algorithm performed. Here are some example charts from a
successful AMT matching run
- T->H Map: the datapoints used for the modal regression to develop the nonlinear map from RT to
NRT. The mapping itself is indicated as a line on this chart.
- Before Calibration: describes the mass calibration of the LC-MS features, prior to
recalibration. LC-MS features are calibrated using the initial match to the AMT database, in order
ensure a normal distribution of mass error. A line indicates the regression result used for
calibration
- After Calibration: describes the mass calibration of the LC-MS features after recalibration
- Loose match error data: shows all AMT matches within a wide tolerance window
- Decoy data: shows all AMT matches to a decoy AMT database created by adding a fixed value
to AMT feature masses
- EM dist analysis: plots describing how well the estimated distribution fits the data,
one for each dimension. In the charts on the left, the estimated distributions in each dimension are
overlaid with the actual data density; ideally there should be little difference. The quantile-quantile
plots on the right are derived from the same data and should ideally be a 1:1 line.
- Distribution: 3D perspective plot of the raw match data density (gray) with the estimated
distribution superimposed in a red mesh. Ideally the two distributions should lie very closely atop
one another. This plot requires R version >= 2.5.1
- EM Parameters: shows the convergence of all the parameters estimated by the EM algorithm
- All probabilities: shows the same datapoints from the "Loose match error data" plot,
color-coded by the probability assigned with the EM model. High-probability points are blue.
Time to NRT Map
LC-MS Feature Mass Calibration, pre-recalibration
LC-MS Feature Mass Calibration, after recalibration
Loose match error data
Loose decoy match error data
Estimated Distributions Compared with Real Data, with QQ plot
Estimated 2D Distribution Compared with Real Data
EM Parameter Convergence
All Probabilities Assigned
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