Response to comment on "Genomic epidemiology of superspreading events in Austria reveals mutational dynamics and transmission properties of SARS-CoV-2"
Sci Transl Med. 2021 Oct 27;13(617):eabj3222.
doi: 10.1126/scitranslmed.abj3222.
Epub 2021 Oct 27.
1 Cancer Research UK Edinburgh Centre, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK.
2 CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria.
3 Institute of Artificial Intelligence, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, 1090 Vienna, Austria.
4 Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
5 Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA.
6 Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA.
7 The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
8 The Ludwig Center at Harvard, Boston, MA 02115, USA.
9 Center for Cancer Evolution, Dana-Farber Cancer Institute, Boston, MA 02115, USA.
Further analysis of SARS-CoV-2 genome sequencing data identifies several highly recurrent genetic variants with low allele frequencies, which, if filtered out, provide estimates consistent with tighter transmission bottlenecks.