The software uses a threshold of 0.5 and peptides below that value are discarded for not covarying enough with the other peptides of a particular protein. How well does such an approach work for stably-expressed proteins (sometimes called housekeeping proteins) that are expected to be fairly constantly abundant across all samples, with the main contribution to variation in measurements being Poisson sampling variability or technical batch effects. For example GAPDH or G3P_HUMAN in my data set has 58 transitions, of which only 25 are used for quantitation. That means 33, or more than half, are discarded for being incoherent. Is Diffacto biased against housekeeping proteins?
The software uses a threshold of 0.5 and peptides below that value are discarded for not covarying enough with the other peptides of a particular protein. How well does such an approach work for stably-expressed proteins (sometimes called housekeeping proteins) that are expected to be fairly constantly abundant across all samples, with the main contribution to variation in measurements being Poisson sampling variability or technical batch effects. For example GAPDH or G3P_HUMAN in my data set has 58 transitions, of which only 25 are used for quantitation. That means 33, or more than half, are discarded for being incoherent. Is Diffacto biased against housekeeping proteins?