Description Usage Arguments Value Author(s) See Also Examples
Motif-related utility functions.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | add_gap(motif, gaploc = ncol(motif)%/%2, mingap = 1, maxgap = 5)
compare_columns(x, y, method, bkg1 = rep(1/length(x), length(x)),
bkg2 = rep(1/length(y), length(y)), nsites1 = 100, nsites2 = 100)
consensus_to_ppm(letter)
consensus_to_ppmAA(letter)
get_consensus(position, alphabet = "DNA", type = "PPM", pseudocount = 1)
get_consensusAA(position, type = "PPM", pseudocount = 0)
get_matches(motif, score, allow.nonfinite = FALSE)
get_scores(motif, allow.nonfinite = FALSE)
icm_to_ppm(position)
motif_score(motif, threshold = c(0, 1), use.freq = 1,
allow.nonfinite = FALSE, threshold.type = c("total", "fromzero"))
log_string_pval(pval)
pcm_to_ppm(position, pseudocount = 0)
position_icscore(position, bkg = numeric(), type = "PPM",
pseudocount = 1, nsites = 100, relative_entropy = FALSE,
schneider_correction = FALSE)
ppm_to_icm(position, bkg = numeric(), schneider_correction = FALSE,
nsites = 100, relative_entropy = FALSE)
ppm_to_pcm(position, nsites = 100)
ppm_to_pwm(position, bkg = numeric(), pseudocount = 1, nsites = 100,
smooth = TRUE)
prob_match(motif, match, allow.zero = TRUE)
prob_match_bkg(bkg, match)
pwm_to_ppm(position, bkg = numeric())
round_motif(motif, pct.tolerance = 0.05)
score_match(motif, match, allow.nonfinite = FALSE)
summarise_motifs(motifs, na.rm = TRUE)
ungap(motif, delete = FALSE)
|
motif |
Motif object to calculate scores from, or add/remove gap, or round. |
gaploc |
|
mingap |
|
maxgap |
|
x |
|
y |
|
method |
|
bkg1 |
|
bkg2 |
|
nsites1 |
|
nsites2 |
|
letter |
|
position |
|
alphabet |
|
type |
|
pseudocount |
|
score |
|
allow.nonfinite |
|
threshold |
|
use.freq |
|
threshold.type |
|
pval |
|
bkg |
|
nsites |
|
relative_entropy |
|
schneider_correction |
|
smooth |
|
match |
|
allow.zero |
|
pct.tolerance |
|
motifs |
|
na.rm |
|
delete |
|
For consensus_to_ppm()
and consensus_to_ppmAA()
: a numeric
vector of length 4 and 20, respectively.
For get_consensus()
and get_consensusAA()
: a character vector
of length 1.
For get_matches()
: a character
vector of motif matches.
For motif_score()
: a named numeric
vector of motif scores.
For log_string_pval()
: a numeric
vector of length 1.
For position_icscore()
: a numeric
vector of length 1.
For ppm_to_icm()
, icm_to_ppm()
, pcm_to_ppm()
,
ppm_to_pcm()
, ppm_to_pwm()
, and pwm_to_ppm()
: a numeric
vector with length equal to input numeric
vector.
For prob_match()
: a numeric
vector of probabilities.
For round_motif()
: the input motif, rounded.
For score_match()
: a numeric
vector with the match motif score.
For summarise_motifs()
: a data.frame
with columns representing
the universalmotif slots.
Benjamin Jean-Marie Tremblay, b2tremblay@uwaterloo.ca
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 | data(examplemotif)
examplemotif0 <- examplemotif
examplemotif0["pseudocount"] <- 0
#######################################################################
## add_gap
## Add gap information to a motif.
m <- create_motif()
# Add a gap size 5-8 between positions 4 and 5:
m <- add_gap(m, gaploc = 4, mingap = 5, maxgap = 8)
#######################################################################
## compare_columns
## Compare two numeric vectors using the metrics from compare_motifs()
compare_columns(c(0.5, 0.1, 0.1, 0.2), c(0.7, 0.1, 0.1, 0.1), "PCC")
#######################################################################
## consensus_to_ppm
## Do the opposite of get_consensus. Note that loss of information is
## inevitable. Generates a sequence matrix.
sapply(c("A", "G", "T", "B"), consensus_to_ppm)
#######################################################################
## consensus_to_ppmAA
## Do the opposite of get_consensusAA and generate a motif matrix.
sapply(c("V", "A", "L"), consensus_to_ppmAA)
#######################################################################
## get_consensus
## Get a consensus string from a DNA/RNA motif.
m <- create_motif()["motif"]
apply(m, 2, get_consensus)
#######################################################################
## get_consensusAA
## Get a consensus string from an amino acid motif. Unless each position
## is clearly dominated by a single amino acid, the resulting string will
## likely be useless.
m <- create_motif(alphabet = "AA")["motif"]
apply(m, 2, get_consensusAA, type = "PPM")
#######################################################################
## get_match
## Get all possible motif matches above input score
get_matches(examplemotif, 0)
get_matches(examplemotif0, 0, allow.nonfinite = TRUE)
#######################################################################
## get_scores
## Get all possible scores for a motif
length(get_scores(examplemotif))
get_scores(examplemotif)
get_scores(examplemotif0, allow.nonfinite = TRUE)
#######################################################################
## icm_to_ppm
## Do the opposite of ppm_to_icm.
m <- create_motif(type = "ICM")["motif"]
apply(m, 2, icm_to_ppm)
#######################################################################
## motif_score
## Calculate motif score from different thresholds
m <- normalize(examplemotif)
motif_score(m, c(0, 0.8, 1))
motif_score(examplemotif0, c(0, 0.8, 1), allow.nonfinite = TRUE,
threshold.type = "fromzero")
#######################################################################
## log_string_pval
## Get the log of a string-formatted p-value
log_string_pval("1e-400")
#######################################################################
## pcm_to_ppm
## Go from a count type motif to a probability type motif.
m <- create_motif(type = "PCM", nsites = 50)["motif"]
apply(m, 2, pcm_to_ppm, pseudocount = 1)
#######################################################################
## position_icscore
## Similar to ppm_to_icm, except this calculates the position sum.
m <- create_motif()["motif"]
apply(m, 2, position_icscore, type = "PPM", bkg = rep(0.25, 4))
#######################################################################
## ppm_to_icm
## Convert one column from a probability type motif to an information
## content type motif.
m <- create_motif(nsites = 100, pseudocount = 0.8)["motif"]
apply(m, 2, ppm_to_icm, nsites = 100, bkg = rep(0.25, 4))
#######################################################################
## ppm_to_pcm
## Do the opposite of pcm_to_ppm.
m <- create_motif()["motif"]
apply(m, 2, ppm_to_pcm, nsites = 50)
#######################################################################
## ppm_to_pwm
## Go from a probability type motif to a weight type motif.
m <- create_motif()["motif"]
apply(m, 2, ppm_to_pwm, nsites = 100, bkg = rep(0.25, 4))
#######################################################################
## prob_match, prob_match_bkg
## Calculate probability of a particular match based on background
## frequencies
prob_match(examplemotif, "TATATAT")
## Since this motif has a uniform background, the probability of
## finding any motif hit within the sequence is equal
prob_match(examplemotif, "TATATAG")
m <- examplemotif
m["bkg"] <- c(0.3, 0.2, 0.2, 0.3)
prob_match(m, "TATATAT")
## The prob_match_bkg alternative allows you to simply pass along the
## background frequencies
prob_match_bkg(c(A=0.3, C=0.2, G=0.2, T=0.3), c("TATATAT", "TATATAG"))
#######################################################################
## pwm_to_ppm
## Do the opposite of ppm_to_pwm.
m <- create_motif(type = "PWM")["motif"]
apply(m, 2, pwm_to_ppm, bkg = rep(0.25, 4))
#######################################################################
## Note that not all type conversions can be done directly; for those
## type conversions which are unavailable, universalmotif just chains
## together others (i.e. from PCM -> ICM => pcm_to_ppm -> ppm_to_icm)
#######################################################################
## round_motif
## Round down letter scores to 0
m <- create_motif()
## Remove letters from positions which are less than 5% of the total
## position:
round_motif(m, pct.tolerance = 0.05)
#######################################################################
## score_match
## Calculate score of a particular match
score_match(examplemotif, "TATATAT")
score_match(examplemotif, "TATATAG")
score_match(examplemotif0, "TATATAT", allow.nonfinite = TRUE)
score_match(examplemotif0, "TATATAG", allow.nonfinite = TRUE)
#######################################################################
## summarise_motifs
## Create a data.frame of information based on a list of motifs.
m1 <- create_motif()
m2 <- create_motif()
m3 <- create_motif()
summarise_motifs(list(m1, m2, m3))
#######################################################################
## ungap
## Unset motif's gap status. Does not delete actual gap data unless
## delete = TRUE.
m <- create_motif()
m <- add_gap(m, 3, 2, 4)
m <- ungap(m)
# Restore gap data:
m <- add_gap(m)
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