Reducing the standard deviation in multiple-assay experiments where the variation matters but the absolute value does not

PLoS One. 2013 Oct 30;8(10):e78205. doi: 10.1371/journal.pone.0078205. eCollection 2013.

Abstract

When the value of a quantity x for a number of systems (cells, molecules, people, chunks of metal, DNA vectors, so on) is measured and the aim is to replicate the whole set again for different trials or assays, despite the efforts for a near-equal design, scientists might often obtain quite different measurements. As a consequence, some systems' averages present standard deviations that are too large to render statistically significant results. This work presents a novel correction method of a very low mathematical and numerical complexity that can reduce the standard deviation of such results and increase their statistical significance. Two conditions are to be met: the inter-system variations of x matter while its absolute value does not, and a similar tendency in the values of x must be present in the different assays (or in other words, the results corresponding to different assays must present a high linear correlation). We demonstrate the improvements this method offers with a cell biology experiment, but it can definitely be applied to any problem that conforms to the described structure and requirements and in any quantitative scientific field that deals with data subject to uncertainty.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biological Assay / methods*
  • Gene Regulatory Networks / genetics
  • Humans
  • Membrane Proteins / genetics
  • Mitochondrial Proteins / genetics

Substances

  • MTCH1 protein, human
  • Membrane Proteins
  • Mitochondrial Proteins

Grant support

This work has been supported by grants FIS2009-13364-C02-01 (Ministerio de Ciencia e Innovación, Spain), UZ2012-CIE-06 (Universidad de Zaragoza, Spain), Grupo Consolidado "Biocomputación y Física de Sistemas Complejos" (DGA, Spain), also by grants BFU2009-11800 (Ministerio de Ciencia e Innovación, Spain), and UZ2010-BIO-03 and UZ2011-BIO-02 (Universidad de Zaragoza, Spain) to J.A.C. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.