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simple utility for parsing and working with NMR peak tables, including ROC analysis

Project description

nmrtoolbox

Introduction

This is a simple utility that provides modules for working with NMRPipe peak tables and performing a receiver operator characteristic (ROC) analysis to quantify the quality of the "recovered" peaks relative to a control set of "synthetic" peaks. The modules in this package are as follows:

  • nmrtoolbox.peak: classes for reading in peak tables (currently supports both synthetically generated and recovered peak tables from NMRPipe)
  • nmrtoolbox.roc: perform receiver operator characteristic (ROC) analysis of a recovered peak table relative to a synthetic peak table
  • nmrtoolbox.mask: define regions of a spectrum that contain signal or are empty
  • nmrtoolbox.util: various supporting utilities used by other modules
  • nmrtoolbox.strip_plot: generate color coded strip plots that correspond to the true positive and false positive peaks classified by an ROC analysis

Applications

Example #1 - Formal Workflow

The tools in this package are utilized by the NUScon software package. You can access NUScon on the NMRbox platform (free for academic, government, and non-profit users). Running nuscon -h will provide instructions on how to run the NUScon evaluation workflow, which directly utilizes the tools presented here in the nmrtoolbox package.

Example #2 - Kick the Tires

from nmrtoolbox.roc import roc
from nmrtoolbox.strip_plot import strip_plot

# perform ROC analysis and specify filtering criteria
my_roc = roc(
    recPeaks=<file-recovered.tab>,
    synPeaks=<file-synthetic.tab>,
    cluster_type=1,
    chi2prob=.75,
    vol_height_mismatch=True,
    maxLW_percent_SW=0.25,
)

# show and plot results
my_roc.print_stats()
my_roc.plot_roc()

# generate strip plots
strip_plot(
    recSpectrum=<file-recovered-spectrum.ft3>,
    sumSpectrum=<file-sum-spectrum.ft3>,
    empSpectrum=<file-empirical-spectrum.ft3>,
    empPeaks=<file-empirical.tab>,
    roc_obj=my_roc,
)

The roc function supports the following filter criteria:

  • number
  • height
  • abs_height
  • roi_list
  • index
  • cluster_type
  • mask_file
  • chi2prob
  • outlier
  • vol_height_mismatch
  • maxLW_percent_SW

Note: Filtering by mask requires the external use of NMRPipe to generate a mask file indicating where the spectrum is empty. This binary data is converted by Connjur Spectrum Translator into a "tabular" format file (i.e. plain text) which is then read in by nmrtoolbox.mask.

The strip plot function shown above will make pairwise comparisons among the following 3 types of input spectra (all of which are fundamental to the NUScon workflow):

  • empSpectrum: empirical spectrum, this reference is typically obtained by FT processing of a uniformly collected experiment
  • sumSpectrum: sum spectrum, this control is typically obtained by FT processing the uniformly sampled time domain data of the empirical data augmented with synthetic peaks
  • recSpectrum: recovered spectrum, typically obtained by processing a nonuniformly sampled version of the empirical time data augmented with the synthetic time data

In addition, the corresponding peak tables are also accepted as inputs:

  • empPeaks: empirical peaks, peak table from the empirical spectrum
  • synPeaks: synthetic peaks, peak table of just the synthetic peaks used to build the sum spectrum
  • recPeaks: recovered peaks, peak table from the NUS reconstruction of the synthetic and empirical data

Example data from NUScon archive is available on NMRbox at '/NUScon/archive'

Changelog

v11

  • major upgrades to strip_plot module
  • PeakTable and Spectrum classes use enumerated types to define valid input formats
  • PeakTable and Spectrum classes offer .read() methods to handle multiple input types
  • rename roc input parameters to be consistent with PeakTable and Spectrum classes
  • universal change to variable naming: "injected" is no longer used. "synthetic" refers to only the synthetic peaks/spectra and "sum" refers to "empirical" + "synthetic" peaks/spectra

v10

  • major change: ROC now sorts peaks by absolute value of intensity (previously used intensity from largest positive down to largest negative)
  • new module added for generating strip plots
  • add more options for peak table filtering

v9

  • change in internal data model for storing metadata in Peak, PeakTable, Mask, ROC, and ROI classes
  • allow roc class to accept Mask object (not just mask file)
  • approximate maximum LW for injected peaks from X1/X3, etc. parameters in the injected peak table
  • function to write NMRPipe peak table to file

v8

  • change to MIT license
  • box_radius for mask filtering is multidimensional
  • improved input options for setting carrier frequency
  • axis labels used to verify compatibility of Peak, Mask, ROI, and ROC objects

v7

  • addition of roc module
  • addition of mask module

v6

  • rename package as nmrtoolbox
  • use subclasses to handle NMRPipe peak tables coming from genSimTab or from the peak picker

v5

  • new Axis class for containing metadata from peak table header

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