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With higher throughput demands on today’s mass spec quantitative applications, the bottlenecks affecting sample turnaround time are moving from data acquisition to data processing. Most lab environments like this can’t afford the time it takes to re-integrate missed...
With bottom-up proteomics, we quantify peptides in the sample and then infer the protein level quantitation from that data. However, due to post-translational modifications, different protein isoforms, etc. we don’t always expect that all peptides associated with the...
When performing LC-MS quantitation, there are numerous sources of experimental variance that can confound the quality of your results (variation in the starting amount of sample, variation in the LC-MS measurements, etc.). Having a robust normalization strategy that...
In an LC-MS experiment there are multiple sources of variance that can confound the quality of your results. This variation can be biological e.g. differences between treated and control groups, but can also be non-biological, usually from small variations in...
A t-test (sometimes called Student’s t-test) is used to determine if the means of two sample groups are significantly different. So, for LC-MS data, we would typically use a t-test to find out if the amount of our variable of interest (protein, peptide, small...
In our previous post we discussed how to interpret the Scores and Loadings Plots produced by PCA. In many cases there are several dimensions that are found to have substantial influence over a specific principal component, and these dimensions are often correlated in...
When we measure anything, the resulting measurements are often referred to as variables or dimensions. For example, a cube has three dimensions that can be measured: length, width and height. When we measure a complex sample using mass spectrometry (like a proteome,...
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