Description Usage Arguments Details Value See Also Examples

Computes the encoding distance between two encodings.

1 | ```
calc_pi(a, b)
``` |

`a` |
encoding (see |

`b` |
encoding to which |

The encoding distance between `a`

and `b`

is defined as the
minimum number of amino acids that have to be moved between subgroups of encoding
to make `a`

identical to `b`

(order of subgroups in the encoding and amino
acids in a group is unimportant).

If the parameter `prop`

is supplied, the encoding distance is normalized by the
factor equal to the sum of distances for each group in `a`

and the closest group
in `b`

. The position of a group is defined as the mean value of properties of
amino acids or nucleotides belonging the group.

See the package vignette for more details.

an encoding distance.

`calc_si`

: compute the similarity index of two encodings.
`encoding2df`

: converts an encoding to a data frame.
`validate_encoding`

: validate a structure of an encoding.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
# calculate encoding distance between two encodings of amino acids
aa1 = list(`1` = c("g", "a", "p", "v", "m", "l", "i"),
`2` = c("k", "h"),
`3` = c("d", "e"),
`4` = c("f", "r", "w", "y", "s", "t", "c", "n", "q"))
aa2 = list(`1` = c("g", "a", "p", "v", "m", "l", "q"),
`2` = c("k", "h", "d", "e", "i"),
`3` = c("f", "r", "w", "y", "s", "t", "c", "n"))
calc_pi(aa1, aa2)
# the encoding distance between two identical encodings is 0
calc_pi(aa1, aa1)
``` |

biogram documentation built on March 31, 2020, 5:14 p.m.

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