Add descriptions and frequencies from the cluster assigned to each position in an annotated deep_mutational_scan
dataset. These were determined through analysis of the larger deep_landscape dataset. Numerical
summary statistics based on the same dataset can also be added, which give the mean characteristics of the subtype.
They include results from FoldX and Naccess and mean ER fitness score profiles.
describe_clusters(x, full = FALSE)
| x | |
|---|---|
| full | Logical. Include average statistics from the |
A tibble, with each row detailing a row of the input data and columns matching
those in the subtypes dataset.
The deep landscape properties summarised where chosen by benchmarking subtype based predictions against the landscape data and a separate deep mutational scan of SARS-CoV-2 Spike by Starr et al. (2020). Metrics are only shown when the average value of positions of that subtype is meaningfully related to the observed values.
Properties are not shown for outlier subtypes, which do not have consistent properties, and ambiguously assigned positions, since the properties could be that of either of the subtypes the position could have been assigned to.
#> Warning: deep_mutational_scan is not annotated. Annotating using annotate_dms().#> # A tibble: 191 x 8 #> name position wt cluster global_cluster_f… group description notes #> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr> <chr> #> 1 Kotle… 1 T T5 0.0615 Nega… Weak selectio… Weak se… #> 2 Kotle… 2 Y Y3 0.227 Arom… Generally sel… General… #> 3 Kotle… 3 Q Q2 0.2 Not … Anything but … Anythin… #> 4 Kotle… 4 G G6 0.0512 Uniq… Largely permi… Largely… #> 5 Kotle… 5 S S1 0.398 Smal… Only tolerate… Only to… #> 6 Kotle… 6 Y Y3 0.227 Arom… Generally sel… General… #> 7 Kotle… 7 G G6 0.0512 Uniq… Largely permi… Largely… #> 8 Kotle… 8 F FO 0.00722 Outl… Outlier NA #> 9 Kotle… 9 R R1 0.461 Posi… Intolerant of… Intoler… #> 10 Kotle… 10 L LO 0.0561 Outl… Outlier NA #> # … with 181 more rows# More details describe_clusters(dms, full = TRUE)#> Warning: deep_mutational_scan is not annotated. Annotating using annotate_dms().#> # A tibble: 191 x 46 #> name position wt cluster global_cluster_… group description notes A #> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr> <chr> <dbl> #> 1 Kotl… 1 T T5 0.0615 Nega… Weak selec… Weak… -0.0596 #> 2 Kotl… 2 Y Y3 0.227 Arom… Generally … Gene… -0.550 #> 3 Kotl… 3 Q Q2 0.2 Not … Anything b… Anyt… -0.0168 #> 4 Kotl… 4 G G6 0.0512 Uniq… Largely pe… Larg… 0.0407 #> 5 Kotl… 5 S S1 0.398 Smal… Only toler… Only… -0.247 #> 6 Kotl… 6 Y Y3 0.227 Arom… Generally … Gene… -0.550 #> 7 Kotl… 7 G G6 0.0512 Uniq… Largely pe… Larg… 0.0407 #> 8 Kotl… 8 F FO 0.00722 Outl… Outlier NA NA #> 9 Kotl… 9 R R1 0.461 Posi… Intolerant… Into… -0.605 #> 10 Kotl… 10 L LO 0.0561 Outl… Outlier NA NA #> # … with 181 more rows, and 37 more variables: C <dbl>, D <dbl>, E <dbl>, #> # F <dbl>, G <dbl>, H <dbl>, I <dbl>, K <dbl>, L <dbl>, M <dbl>, N <dbl>, #> # P <dbl>, Q <dbl>, R <dbl>, S <dbl>, T <dbl>, V <dbl>, W <dbl>, Y <dbl>, #> # mean_score <dbl>, total_energy <dbl>, backbone_hbond <dbl>, #> # sidechain_hbond <dbl>, van_der_waals <dbl>, electrostatics <dbl>, #> # solvation_polar <dbl>, solvation_hydrophobic <dbl>, #> # van_der_waals_clashes <dbl>, entropy_sidechain <dbl>, #> # entropy_mainchain <dbl>, cis_bond <dbl>, torsional_clash <dbl>, #> # backbone_clash <dbl>, disulfide <dbl>, partial_covalent_bonds <dbl>, #> # energy_ionisation <dbl>, all_atom_rel <dbl>