For all sequences in a cluster(s) calculate the frequency of separate words in either the sequence definitions or the reported feature name.
Usage
calc_wrdfrq(
phylota,
cid,
min_frq = 0.1,
min_nchar = 1,
type = c("dfln", "nm"),
ignr_pttrn = "[^a-z0-9]"
)Arguments
- phylota
Phylota object
- cid
Cluster ID(s)
- min_frq
Minimum frequency
- min_nchar
Minimum number of characters for a word
- type
Definitions (dfln) or features (nm)
- ignr_pttrn
Ignore pattern, REGEX for text to ignore.
Details
By default, anything that is not alphanumeric is ignored. 'dfln' and 'nm' match the slot names in a SeqRec, see list_seqrec_slots().
See also
Other tools-public:
calc_mad(),
drop_by_rank(),
drop_clstrs(),
drop_sqs(),
get_clstr_slot(),
get_nsqs(),
get_ntaxa(),
get_sq_slot(),
get_stage_times(),
get_tx_slot(),
get_txids(),
is_txid_in_clstr(),
is_txid_in_sq(),
list_clstrrec_slots(),
list_ncbi_ranks(),
list_seqrec_slots(),
list_taxrec_slots(),
plot_phylota_pa(),
plot_phylota_treemap(),
read_phylota(),
write_sqs()
Examples
data('dragonflies')
# work out what gene region the cluster is likely representing with word freqs.
random_cids <- sample(dragonflies@cids, 10)
# most frequent words in definition line
(calc_wrdfrq(phylota = dragonflies, cid = random_cids, type = 'dfln'))
#> $`221`
#> aenea
#> 0.1692308
#>
#> $`196`
#> wrds
#> gene 28s partial sequence
#> 0.1118881 0.1048951 0.1048951 0.1048951
#>
#> $`346`
#> named numeric(0)
#>
#> $`607`
#> named numeric(0)
#>
#> $`628`
#> named numeric(0)
#>
#> $`232`
#> named numeric(0)
#>
#> $`402`
#> named numeric(0)
#>
#> $`699`
#> named numeric(0)
#>
#> $`29`
#> named numeric(0)
#>
#> $`448`
#> named numeric(0)
#>
# most frequent words in feature name
(calc_wrdfrq(phylota = dragonflies, cid = random_cids, type = 'nm'))
#> $`221`
#> numeric(0)
#>
#> $`196`
#> numeric(0)
#>
#> $`346`
#> numeric(0)
#>
#> $`607`
#> numeric(0)
#>
#> $`628`
#> numeric(0)
#>
#> $`232`
#> numeric(0)
#>
#> $`402`
#> numeric(0)
#>
#> $`699`
#> barcode
#> 1
#>
#> $`29`
#> numeric(0)
#>
#> $`448`
#> numeric(0)
#>