Filtering data from high-throughput experiments based on measurement reliability

In the context of the plethora of data currently generated in molecular biology, the paper by Bourgon et al. in PNAS (1) is pivotal, because it shows that an initial data filter can appropriately increase the detection power of a high-throughput experiment. Bourgon et al. (1) showed that filtering on overall variance outperforms filtering on overall mean, but they do not address two weaknesses of the methodology. First, because filtering is done on the overall variance, it does not disentangle the biological variation (containing the potentially interesting signals) from the technical variation (i.e., the measurement noise). Second, the threshold choice when the overall variation should be considered too low is very arbitrary and makes the method … 1To whom correspondence should be addressed. E-mail: wtalloen{at}its.jnj.com.