PMC:7519301 / 35757-36322
Annnotations
LitCovid-PD-UBERON
To identify individual sequences that were much more divergent than expected, given their sampling date, which likely reflected sequencing artifacts rather than evolution, we obtained a tree using FastTree v2.10.1 compiled with double precision under the general time reversible (GTR) model with gamma heterogeneity (51). This tree was rooted at the reference sequence, and root-to-tip regression was performed following TempEst using the ape package in R (52, 53). Outliers were defined as sequences that had studentized residuals greater than 3, and were removed.
LitCovid-PD-CLO
To identify individual sequences that were much more divergent than expected, given their sampling date, which likely reflected sequencing artifacts rather than evolution, we obtained a tree using FastTree v2.10.1 compiled with double precision under the general time reversible (GTR) model with gamma heterogeneity (51). This tree was rooted at the reference sequence, and root-to-tip regression was performed following TempEst using the ape package in R (52, 53). Outliers were defined as sequences that had studentized residuals greater than 3, and were removed.
LitCovid-sentences
To identify individual sequences that were much more divergent than expected, given their sampling date, which likely reflected sequencing artifacts rather than evolution, we obtained a tree using FastTree v2.10.1 compiled with double precision under the general time reversible (GTR) model with gamma heterogeneity (51). This tree was rooted at the reference sequence, and root-to-tip regression was performed following TempEst using the ape package in R (52, 53). Outliers were defined as sequences that had studentized residuals greater than 3, and were removed.
LitCovid-PD-CHEBI
To identify individual sequences that were much more divergent than expected, given their sampling date, which likely reflected sequencing artifacts rather than evolution, we obtained a tree using FastTree v2.10.1 compiled with double precision under the general time reversible (GTR) model with gamma heterogeneity (51). This tree was rooted at the reference sequence, and root-to-tip regression was performed following TempEst using the ape package in R (52, 53). Outliers were defined as sequences that had studentized residuals greater than 3, and were removed.
2_test
To identify individual sequences that were much more divergent than expected, given their sampling date, which likely reflected sequencing artifacts rather than evolution, we obtained a tree using FastTree v2.10.1 compiled with double precision under the general time reversible (GTR) model with gamma heterogeneity (51). This tree was rooted at the reference sequence, and root-to-tip regression was performed following TempEst using the ape package in R (52, 53). Outliers were defined as sequences that had studentized residuals greater than 3, and were removed.