Intrahost SNPs Track Settings
Intrahost SNP patient data from Todd Treangen's group   (All Variation and Repeats tracks)

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Data last updated at UCSC: 2020-10-26 13:33:42


This track shows iSNPs (intrahost SNPs). These are SNPs that have evidence for variation within one host. That is, a single patient can have variation among the various SARS-CoV-2 viruses infecting their cells. This variation is lost when a single consensus genome sequence is reported for a patient. The data were published in Sapoval et al, 2020 "Hidden genomic diversity of SARS-CoV-2: implications for qRT-PCR diagnostics and transmission".

In this track, iSNPs (intrahost SNP's) of human patients from New York City and Houston are shown.

Display Conventions and Configuration

The track contains a list of iSNPs found in patient data from New York City and Houston with nucleotide and amino acid changes, one feature per variant. The name field in this track represents the median observed allele frequency for patients meeting inclusion criteria in the VCFs provided by Sapoval et al. Finally, bedToBigBed was used to create the BigBed track.

Interested users may wish to inspect each of the individual VCFs; for this track we have chosen to show a condensed version of all VCFs (see Methods).


VCF files were downloaded from the Rice University data repository. SARS-CoV-2 iSNPs from New York City and Houston patient data were parsed, and if the base position was modified in more than one sample then it was included. The frequency of observing a particular base (A,C,G,T) at the position when a change was recorded was then included, and the dominant base change was used to determine whether the base modification would also result in an amino acid change.

The original data files are available from a shared folder with VCF files.


Sapoval N, Mahmoud M, Jochum MD, Liu Y, Leo Elworth RA, Wang Q, Albin D, Ogilvie H, Lee MD, Villapol S et al. Hidden genomic diversity of SARS-CoV-2: implications for qRT-PCR diagnostics and transmission. bioRxiv. 2020 Jul 2;. PMID: 32637955; PMC: PMC7337385