Abstract Details
Activity Number:
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46
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Type:
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Contributed
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Date/Time:
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Sunday, August 4, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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Abstract - #309287 |
Title:
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Quality Assessment of Label-Free Multiple Reaction Monitoring Experiment
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Author(s):
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Lisa Chung*+ and Christopher Colangelo and Hongyu Zhao
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Companies:
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and Yale University and Yale University
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Keywords:
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Multiple Reaction Monitoring ;
Quality assessment ;
Outlier detection
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Abstract:
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Targeted proteomics assays simultaneously quantify expression abundance of hundreds of peptides in a complex mixture. Quantitative measurements for a series of predefined transitions (precursor/fragment ion pairs) are collected through two mass filters of a triple quadrupole instrument over time for precise quantifications. These measurements can be used to estimate expression levels for corresponding peptides and proteins. Although MRM allows researchers to compare protein expression profiles across different experimental conditions, the field is relatively new and many data evaluation and analysis steps still rely on manual inspection of each transition-level observation, making it a tedious and subjective exercise for people analyzing MRM data. Here, we present an automated approach to assessing the quality of transition-level MRM data, which can be applicable for both labeled and label-free MRM experiments. Our approach includes quality control across replicated samples, the detection of outlying observations, inaccurate transitions with signal interference, and other features. The usefulness of our approach is demonstrated through its application to several real MRM data sets.
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Authors who are presenting talks have a * after their name.
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