Add different types of tracks

add_feats(x, ...)

add_links(x, ..., .adjacent_only = TRUE)

add_subfeats(x, ..., .track_id = "genes", .transform = "aa2nuc")

add_sublinks(x, ..., .track_id = "genes", .transform = "aa2nuc")

add_clusters(x, ..., .track_id = "genes")

Arguments

...

named data.frames, i.e. genes=gene_df, snps=snp_df

.track_id

track_id of the feats that subfeats, sublinks or clusters map to.

.transform

one of "aa2nuc", "none", "nuc2aa"

Functions

  • add_feats: Add feature annotations to sequences

  • add_links: Add links connecting sequences, such as whole-genome alignment data.

  • add_subfeats: Add features of features, such as gene/protein domains, blast hits to genes/proteins, etc.

  • add_sublinks: Add links that connect features, such as protein-protein alignments connecting genes.

  • add_clusters: Add gene clusters or other feature groups. Takes a data.frame with at least two required columns cluster_id and feat_id. The data.frame is converted to a link track connecting features belonging to the same cluster over their entire length. Additionally, the data.frame is joined to the parent feature track, adding cluster_id and all additional columns to the parent table.

Examples

# Add some repeat annotations
gggenomes(seqs=emale_seqs) %>%
  add_feats(repeats=emale_tirs) +
  geom_seq() + geom_feat()


# Add all-vs-all whole-genome alignments
gggenomes(seqs=emale_seqs) %>%
  add_links(links=emale_ava) +
  geom_seq() + geom_link()


# Add domains to genes
genes <- tibble(seq_id="A", start=100, end=200, feat_id="gene1")
domains <- tibble(feat_id = "gene1", start=40, end=80)
gggenomes(genes=genes) %>% add_subfeats(domains, .transform = "none") +
  geom_gene() + geom_feat()
#> No seqs provided, inferring seqs from feats


# Add protein-protein alignments
gggenomes(emale_genes) %>%
  add_sublinks(emale_prot_ava) +
  geom_gene() + geom_link()
#> No seqs provided, inferring seqs from feats
#> Transforming sublinks with "aa2nuc". Disable with `.transform = "none"`


# add clusters
gggenomes(emale_genes, emale_seqs) %>%
  add_clusters(emale_cogs) %>%
  flip_by_links() +    # works because clusters
  geom_link() +        # become links
  geom_seq() +
  # works because cluster info is joined to gene track
  geom_gene(aes(fill=ifelse(is.na(cluster_id), NA,
      str_glue("{cluster_id} [{cluster_size}]")))) +
  scale_fill_discrete("COGs")
#> Joining, by = "feat_id"
#> Flipping: 2,3,4