Telomere length measurement validity: the coefficient of variation is invalid and cannot be used to compare quantitative polymerase chain reaction and Southern blot telomere length measurement techniques.
Coefficient of variation Verhulst and colleagues note that the coefficient of variation (CV) may be a problematic measure of precision because it assumes that measurement error is proportional to the mean. There is, however, an even more fundamental problem with the CV measure. The CV statistic is an appropriate measure only for ratio variables, that is continuous variables with natural zero points (i.e. where zero clearly signifies having none of the thing being measured) In theory, the zero point of quantitative polymerase chain reaction (qPCR) measured telomere length (TL) represents the point of essentially no telomere sequence in a sample. For TL measured using Southern blot (SB) the zero point represents having no telomere and none of the sub telomeric portions which are also measured by SB. As shown below, these zero points between SB and qPCR measures do not correspond with each other and thereby create highly misleading estimates of measurement error. Further, within the same type of TL measure (SB or qPCR) the zero points often do not correspond across different implementations of these measurement techniques in different laboratories. When these zero points do not correspond, comparisons of CV are invalid. To illustrate the problem of calculating CVs for data where measures do not correspond in their zero points, consider temperature measured three times with a thermometer which has both degrees Celsius C) and degrees Fahrenheit F) scales on it (Table 1, columns 1 and 2) In this case, for C the CV is 10% but for F the CV is 3.6% This is because the zero points of both C and F are arbitrary and do not correspond with each other. As shown below, the same problem of differing zero points is evident in measuring TL. The problem of comparing CVs between qPCRand SB measured TL can be shown with an example similar to the temperature illustration above. This can be done by using the results of a previous regression analysis of the same DNA samples measured with qPCR and SB. This regression analysis with SB TL as the dependent variable (Y) and qPCR TL as the independent variable (X) yielded a b estimate of 3.33 kilobase pairs (kbp) and y intercept of 3.73 kbp. This y intercept value implies that when qPCR TL is at zero, SB TL would be measured as 3.73 kbp. Similarly large y intercept values are found in other
International journal of epidemiology