Implementing a New Quality Control Protocol for LCMS: A Case Study Comparing Commercially Produced Columns to Homemade Columns
Abstract
With the increasing size of proteomics data sets, there is an emerging need for reliable methods of monitoring LC-MS instrument performance over time to ensure consistency in the data. In this poster, I present a quality control protocol for assessing variation within LC-MS data. The software Skyline is used to extract three analytical figures of merit from bovine serum albumin (BSA) chromatograms. These figures are compared longitudinally to monitor changes in instrument performance over time. I also use the protocol to compare two different types of LC columns used in our facility, homemade and commercial, to determine which yields superior data.
Primary Faculty Mentor Name
Ying Wai Lam
Status
Undergraduate
Student College
College of Arts and Sciences
Program/Major
Biochemistry
Primary Research Category
Life Sciences
Implementing a New Quality Control Protocol for LCMS: A Case Study Comparing Commercially Produced Columns to Homemade Columns
With the increasing size of proteomics data sets, there is an emerging need for reliable methods of monitoring LC-MS instrument performance over time to ensure consistency in the data. In this poster, I present a quality control protocol for assessing variation within LC-MS data. The software Skyline is used to extract three analytical figures of merit from bovine serum albumin (BSA) chromatograms. These figures are compared longitudinally to monitor changes in instrument performance over time. I also use the protocol to compare two different types of LC columns used in our facility, homemade and commercial, to determine which yields superior data.
