HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS REGISTER		Author Keyword(s) Vol Page [Advanced]

This Article Full Text Full Text (PDF) Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Services Email this link to a friend Similar articles in this journal Similar articles in PubMed Add article to my folders Download to citation manager Request Permissions Google Scholar Articles by George, R A Articles by Cotton, R G H PubMed PubMed Citation Articles by George, R A Articles by Cotton, R G H

Response to Stenson et al on the review of general mutation databases

¹ Structural and Computational Biology Program, Victor Chang Cardiac Research Institute, Darlinghurst, New South Wales, Australia
² Genomic Disorders Research Centre, St. Vincent’s Hospital Melbourne, Fitzroy, Victoria, Australia
³ Department of Medicine, The University of Melbourne, Melbourne, Victoria, Australia
⁴ Deceased. Victorian Bioinformatics Consortium, Monash University, Melbourne, Victoria, Australia

Correspondence to:
Dr M Wouters, Victor Chang Cardiac Research Institute, 384 Victoria St, Darlinghurst, New South Wales 2010, Australia; m.wouters@victorchang.unsw.edu.au]

The first 150 words of the full text of this article appear below.

We thank the Human Gene Mutation Database (HGMD) team for critically analysing our results and highlighting some potential problems with our analysis.¹

Many of the criticisms raised by Stenson et al² relate to mutations that were outside the terms of reference of the study. For instance, a major criticism raised by Stenson et al was that the review was not comprehensive in that we neglected to compare all categories of mutations. We limited our comparison to single-base mutations, as it was found to be too difficult to reliably text-mine other mutation types from Online Mendelian Inheritance in Man (OMIM). This could be viewed as indirect discrimination against HGMD, but these mutations do represent the majority of characterised mutations in the database and thus represent a reasonable variable to quantify.

We concluded that both OMIM and HGMD were the most comprehensive resources, but differences between them, including missing genes, highlighted . . . [Full text of this article]