inst/scripts/history.R
In bhagwataditya/importomics: Unified statistal Modeling of Omics Data
devtools::document()
set.seed(42)
# normal distribution
dt <- data.table(y = rnorm(10000, 0))
p <- ggplot(dt) +
theme_minimal() +
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
) +
geom_density(aes(y = y), color = 'white') +
geom_vline(xintercept = 0, color = '#F8766D')
p <- p + annotate('point', y = 0, x = 0, color ='#F8766D')
p <- p + annotate('point', y = -2, x = 0, color ='#F8766D')
p <- p + annotate('point', y = +2, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 0.4, x = 0, color ='#F8766D')
p <- p + annotate('point', y = -0.4, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 0.2, x = 0, color ='#F8766D')
p <- p + annotate('point', y = -0.2, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 1, x = 0, color ='#F8766D')
p <- p + annotate('point', y = -1, x = 0, color ='#F8766D')
p <- p + geom_density(aes(y = y), color ='#F8766D')
# t distribution
p <- ggplot() +
theme_minimal() +
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
)
p + geom_density(data = data.table(x = rnorm(10000)), mapping = aes(y = x), color = '#F8766D') +
geom_density(data = data.table(x = rt(10000,4)/sqrt(10)), mapping = aes(y = x), color = '#00BFC4') # 5 samples # #00BFC4
p + geom_density(data = data.table(x = rnorm(10000)), mapping = aes(y = x), color = '#F8766D') +
geom_density(data = data.table(x = rt(10000,4)/sqrt(10)), mapping = aes(y = x), color = 'white') # 5 samples # #00BFC4
p + geom_density(data = data.table(x = rnorm(10000)), mapping = aes(y = x), color = 'white') +
geom_density(data = data.table(x = rt(10000,4)/sqrt(10)), mapping = aes(y = x), color = '#00BFC4') # 5 samples # #00BFC4
dt <- rbind(data.table(batch = '1', y = rnorm(10000, 13, sd = 0.5)),
data.table(batch = '2', y = rnorm(10000, 15, sd = 0.5)))
p <- ggplot(dt) +
theme_minimal() +
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
) +
geom_density(aes(y = y, linetype = batch), color = 'white') +
geom_vline(xintercept = 0, color = '#F8766D')
p <- p + annotate('point', y = 13, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 12, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 14, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 13.2, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 12.8, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 13.1, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 13.5, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 12.5, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 15, x = 0, color ='#F8766D', shape = 17)
p <- p + annotate('point', y = 14, x = 0, color ='#F8766D', shape = 17)
p <- p + annotate('point', y = 16, x = 0, color ='#F8766D', shape = 17)
p <- p + annotate('point', y = 15.2, x = 0, color ='#F8766D', shape = 17)
p <- p + annotate('point', y = 14.8, x = 0, color ='#F8766D', shape = 17)
p <- p + annotate('point', y = 15.1, x = 0, color ='#F8766D', shape = 17)
p <- p + annotate('point', y = 15.5, x = 0, color ='#F8766D', shape = 17)
p <- p + annotate('point', y = 14.5, x = 0, color ='#F8766D', shape = 17)
p <- p + geom_density(aes(y = y, linetype = batch), color = '#F8766D')
# Two sample t test
#------------------
# Single curve
set.seed(1)
y0 <- seq(-4, +4, length.out = 100)
plotdt <- rbind(data.table(y = y0 + 2, x = -dnorm(y0), type = 'sample'))
p <- ggplot(plotdt, aes(x = x, y = y)) + theme_bw() #+ facet_grid(rows = vars(type), scales = 'free_y')
p <- p + theme(panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_blank())
p <- p + scale_y_continuous(breaks = c(0,2,5,8))
p <- p + guides(color = 'none')
p <- p + ylab(expression(Glc)) + xlab(expression(Frequency))
p <- p + geom_path(aes(linetype = type), color = '#F8766D')
# Add triplets
# p <- p + xlim(-0.4, 0.13)
pointdt <- rbind(data.table(y = rnorm(3,2), x = rep(-0.07, 3), i = rep(1,3)),
data.table(y = rnorm(3,2), x = rep(-0.04, 3), i = rep(2,3)),
data.table(y = rnorm(3,2), x = rep(-0.01, 3), i = rep(3,3)),
data.table(y = rnorm(3,2), x = rep( 0.02, 3), i = rep(4,3)),
data.table(y = rnorm(3,2), x = rep( 0.05, 3), i = rep(5,3)),
data.table(y = rnorm(3,2), x = rep( 0.08, 3), i = rep(6,3)))
meandt <- pointdt[, .( y = mean(y),
ymin = mean(y) - sd(y)/2,
ymax = mean(y) + sd(y)/2,
x = unique(x)), by = c('i') ]
(pp <- p + geom_line(data = pointdt, color = '#F8766D', aes(group = i)) + geom_point(data = pointdt, color = '#F8766D') + guides(linetype = 'none'))
(pp <- p + geom_point(data = meandt, size = 3, shape = 3, color = '#F8766D') + geom_line(data = pointdt, color = '#F8766D', aes(group = i)) + geom_point(data = pointdt, color = '#F8766D') + guides(linetype = 'none'))
t0 <- seq(-4, 4, length.out = 100)
tdt <- data.table( y = 2 +t0, x = -dnorm(t0, sd = 1/sqrt(3)), type = 'samplemean(3)')
pp + geom_path(data = tdt, aes(x = x, y = y, linetype = type), color = '#F8766D')
# Add decets
pointdt <- rbind(data.table(y = rnorm(10,2), x = rep(-0.07, 10), i = rep(1,10)),
data.table(y = rnorm(10,2), x = rep(-0.04, 10), i = rep(2,10)),
data.table(y = rnorm(10,2), x = rep(-0.01, 10), i = rep(3,10)),
data.table(y = rnorm(10,2), x = rep( 0.02, 10), i = rep(4,10)),
data.table(y = rnorm(10,2), x = rep( 0.05, 10), i = rep(5,10)),
data.table(y = rnorm(10,2), x = rep( 0.08, 10), i = rep(6,10)))
meandt <- pointdt[, .( y = mean(y),
ymin = mean(y) - sd(y)/2,
ymax = mean(y) + sd(y)/2,
x = unique(x)), by = c('i') ]
(pp <- p + geom_line(data = pointdt, color = '#F8766D', aes(group = i)) + geom_point(data = pointdt, color = '#F8766D') + guides(linetype = 'none'))
(pp <- p + geom_point(data = meandt, size = 3, shape = 3, color = '#F8766D') + geom_line(data = pointdt, color = '#F8766D', aes(group = i)) + geom_point(data = pointdt, color = '#F8766D') + guides(linetype = 'none'))
t0 <- seq(-4, 4, length.out = 100)
tdt <- data.table( y = 2 +t0, x = -dnorm(t0, sd = 1/sqrt(10)), type = 'samplemean(3)')
pp + geom_path(data = tdt, aes(x = x, y = y, linetype = type), color = '#F8766D')
# p value
y0 <- seq(-4,+4, length.out = 100)
x <- dt(y0, df = 3)
ggplot(data.table(x = -x, y = y0), aes(x = x, y = y)) + theme_bw() + geom_path(color = '#F8766D') +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + xlab(expression(density)) + ylab(expression(t))
# Two curves - very near
y0 <- seq(-4, +4, length.out = 100)
x1 <- dnorm(y0)
x2 <- dnorm(y0)
plotdt <- rbind(data.table(x = - x1, y = 2.0 + y0, group = 'group1'),
data.table(x = - x2, y = 2.2 + y0, group = 'group2'))
pointdt <- rbind(data.table(y = rnorm(3, 2.0), x = -0.05, group = 'group1'),
data.table(y = rnorm(3, 2.2), x = 0, group = 'group2'))
meandt <- pointdt[, .(x = unique(x), y = mean(y)), by = 'group']
ggplot(plotdt) +
geom_path(aes(x = x, y = y, color = group)) + theme_bw() +
theme(panel.grid = element_blank()) +
guides(color = FALSE) +
geom_point(data = pointdt, aes(x =x, y = y, color = group)) +
geom_line(data = pointdt, aes(x = x, y = y, color = group, group = group)) +
geom_point(data = meandt, aes(x = x, y = y, color = group), shape = 3)
# Two curves - nearer
y0 <- seq(-4, +4, length.out = 100)
x1 <- dnorm(y0)
x2 <- dnorm(y0)
plotdt <- rbind(data.table(x = - x1, y = 2 + y0, group = 'group1'),
data.table(x = - x2, y = 5 + y0, group = 'group2'))
pointdt <- rbind(data.table(y = rnorm(3, 2), x = 0, group = 'group1'),
data.table(y = rnorm(3, 5), x = 0, group = 'group2'))
meandt <- pointdt[, .(x = unique(x), y = mean(y)), by = 'group']
ggplot(plotdt) +
geom_path(aes(x = x, y = y, color = group)) + theme_bw() +
theme(panel.grid = element_blank()) +
guides(color = FALSE) +
geom_point(data = pointdt, aes(x =x, y = y, color = group)) +
geom_line(data = pointdt, aes(x = x, y = y, color = group, group = group)) +
geom_point(data = meandt, aes(x = x, y = y, color = group), shape = 3)
# Two curves
y0 <- seq(-4, +4, length.out = 100)
plotdt <- rbind(
data.table(y = y0 + 2, x = -dnorm(y0), group = 'Control', type = 'sample', block = 1),
data.table(y = y0 + 5, x = -dnorm(y0), group = 'Diabetic', type = 'sample', block = 2))
p <- ggplot(plotdt, aes(x = x, y = y, color = group, group = group)) + theme_bw() #+ facet_grid(rows = vars(type), scales = 'free_y')
p <- p + theme(panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_blank())
p <- p + scale_y_continuous(breaks = c(0,2,5,8))
p <- p + guides(color = 'none')
p <- p + ylab(expression(Glc)) + xlab(expression(Frequency))
(p <- p + geom_path(linewidth = 0.8))
(p <- p + xlim(-0.4, 0.13))
# p <- p + annotate('text', y = 2, x = -0.25, label = 'Control', color = '#F8766D', hjust = 0)
# p <- p + annotate('text', y = 5, x = -0.25, label = 'Diabetic', color = '#00BFC4', hjust = 0)
# Samples
pointdt <- rbind(data.table(y = c(rnorm(3,2), rnorm(3,5)), x = c(rep(0.08, 3), rep(0.08, 3)), group = c(rep('Control', 3), rep('Diabetic', 3)), i = rep(1,6)),
data.table(y = c(rnorm(3,2), rnorm(3,5)), x = c(rep(0.08, 3), rep(0.08, 3)), group = c(rep('Control', 3), rep('Diabetic', 3)), i = rep(2,6)),
data.table(y = c(rnorm(3,2), rnorm(3,5)), x = c(rep(0.08, 3), rep(0.08, 3)), group = c(rep('Control', 3), rep('Diabetic', 3)), i = rep(3,6)),
data.table(y = c(rnorm(3,2), rnorm(3,5)), x = c(rep(0.08, 3), rep(0.08, 3)), group = c(rep('Control', 3), rep('Diabetic', 3)), i = rep(4,6)),
data.table(y = c(rnorm(3,2), rnorm(3,5)), x = c(rep(0.08, 3), rep(0.08, 3)), group = c(rep('Control', 3), rep('Diabetic', 3)), i = rep(5,6)),
data.table(y = c(rnorm(3,2), rnorm(3,5)), x = c(rep(0.08, 3), rep(0.08, 3)), group = c(rep('Control', 3), rep('Diabetic', 3)), i = rep(6,6)))
meandt <- pointdt[, .( y = mean(y),
ymin = mean(y) - sd(y)/2,
ymax = mean(y) + sd(y)/2,
x = 0.17), by = c('group', 'i') ]
j <- 1
(pp <- p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]))
pp <- pp + xlim(c(-0.4, 0.50))
(pp <- pp + geom_crossbar(data = meandt[ i==j], aes(y = y, ymin = ymin, ymax = ymax), width = 0.02))
pp + annotate('segment', x = 0.35, xend = 0.35, y = meandt[i==j, min(ymax)]+0.2, yend = meandt[i==j, max(ymin)], arrow = arrow(ends = 'both', length = unit(.2, 'cm'))) +
annotate('segment', x = 0.29, xend = 0.45, y = meandt[i==j, min(ymax)], yend = meandt[i==j, min(ymax)]) +
annotate('segment', x = 0.35, xend = 0.35, y = meandt[i==j, min(ymin)+0.1], yend = meandt[i==j, min(ymax)-0.2], arrow = arrow(ends = 'both', length = unit(.2, 'cm'))) +
annotate('segment', x = 0.33, xend = 0.37, y = meandt[i==j, min(ymin)], yend = meandt[i==j, min(ymin)]) +
annotate('point', x = 0.33, y = meandt[i==j, min(ymin)]-0.4) +
annotate('point', x = 0.35, y = meandt[i==j, min(ymin)]-0.4) +
annotate('point', x = 0.37, y = meandt[i==j, min(ymin)]-0.4) +
annotate('text', x = 0.27, y = meandt[i==j, min(ymax)], label = 't = ') +
annotate('text', x = 0.37, y = meandt[i==j, mean(c(min(ymax), max(ymin)))], label = 'between', hjust = 0) +
annotate('text', x = 0.38, y = meandt[i==j, mean(c(min(ymin), min(ymax)))], label = 'within', hjust = 0) +
annotate('text', x = 0.39, y = meandt[i==j, min(ymin)-0.3 ], label = 'sqrt(n)', hjust = 0, parse = TRUE)
j <- 1; (p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]))
j <- 1; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]) + geom_crossbar(data = meandt[i==j], aes(x = x, xmin = xmin, xmax = xmax), width = 0.02, fill = 'white') + geom_point( data = pointdt[i==j])
j <- 2; (p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]))
j <- 2; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]) + geom_crossbar(data = meandt[i==j], aes(x = x, xmin = xmin, xmax = xmax), width = 0.02, fill = 'white') + geom_point( data = pointdt[i==j])
j <- 3; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j])
j <- 3; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]) + geom_crossbar(data = meandt[i==j], aes(x = x, xmin = xmin, xmax = xmax), width = 0.02, fill = 'white') + geom_point( data = pointdt[i==j])
j <- 4; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j])
j <- 4; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]) + geom_crossbar(data = meandt[i==j], aes(x = x, xmin = xmin, xmax = xmax), width = 0.02, fill = 'white') + geom_point( data = pointdt[i==j])
j <- 5; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j])
j <- 5; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]) + geom_crossbar(data = meandt[i==j], aes(x = x, xmin = xmin, xmax = xmax), width = 0.02, fill = 'white') + geom_point( data = pointdt[i==j])
# tvalues
tdt <- pointdt[,
.(mean1 = mean(.SD[group == 'Control', x ]),
mean1 = mean(.SD[group == 'T2D', x ]),
sd1 = sd(.SD[group == 'Control', x ]),
sd2 = sd(.SD[group == 'T2D', x ]),
n1 = 3,
n2 = 3), by = 'i']
tdt[, t := (mean2 - mean1) / sqrt((sd1^2/n1 + sd2^2/n2)) ]
tpoints <- data.table(x = seq(-4, +4, length.out = 100))
tpoints[, y := dt(x, df = 4) ]
tpoints[, group := 'T2D-Control']
q <- ggplot(tpoints, aes(x = 2+x, y = y)) + theme_bw() + geom_line() +
xlab(expression(frac(Glc[T2D] - Glc[Control], frac(s, sqrt(n))))) +
ylab(expression(Density))
gridExtra::grid.arrange(p, q, nrow = 2)
j <- 1
pp <- p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j])
pp <- pointdt[i==j & group == 'Control'][, pp + annotate('point', x = mean(x), y = mean(y), color = '#F8766D', shape = 108, size = 10) ]
pp <- pointdt[i==j & group == 'T2D' ][, pp + annotate('point', x = mean(x), y = mean(y), color = '#00BFC4', shape = 108, size = 10) ]
pp + coord_flip()
gridExtra::grid.arrange(pp, q, nrow = 2)
pp <- pp + geom_crossbar(data = meandt[i==j], aes(x = x, xmin = xmin, xmax = xmax), width = 0.02, fill = 'white') + geom_point( data = pointdt[i==j])
gridExtra::grid.arrange(pp, q, nrow = 2)
pp + annotate(x = )
bhagwataditya/importomics documentation built on May 1, 2024, 2:01 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
devtools::document()
set.seed(42)
# normal distribution
dt <- data.table(y = rnorm(10000, 0))
p <- ggplot(dt) +
theme_minimal() +
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
) +
geom_density(aes(y = y), color = 'white') +
geom_vline(xintercept = 0, color = '#F8766D')
p <- p + annotate('point', y = 0, x = 0, color ='#F8766D')
p <- p + annotate('point', y = -2, x = 0, color ='#F8766D')
p <- p + annotate('point', y = +2, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 0.4, x = 0, color ='#F8766D')
p <- p + annotate('point', y = -0.4, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 0.2, x = 0, color ='#F8766D')
p <- p + annotate('point', y = -0.2, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 1, x = 0, color ='#F8766D')
p <- p + annotate('point', y = -1, x = 0, color ='#F8766D')
p <- p + geom_density(aes(y = y), color ='#F8766D')
# t distribution
p <- ggplot() +
theme_minimal() +
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
)
p + geom_density(data = data.table(x = rnorm(10000)), mapping = aes(y = x), color = '#F8766D') +
geom_density(data = data.table(x = rt(10000,4)/sqrt(10)), mapping = aes(y = x), color = '#00BFC4') # 5 samples # #00BFC4
p + geom_density(data = data.table(x = rnorm(10000)), mapping = aes(y = x), color = '#F8766D') +
geom_density(data = data.table(x = rt(10000,4)/sqrt(10)), mapping = aes(y = x), color = 'white') # 5 samples # #00BFC4
p + geom_density(data = data.table(x = rnorm(10000)), mapping = aes(y = x), color = 'white') +
geom_density(data = data.table(x = rt(10000,4)/sqrt(10)), mapping = aes(y = x), color = '#00BFC4') # 5 samples # #00BFC4
dt <- rbind(data.table(batch = '1', y = rnorm(10000, 13, sd = 0.5)),
data.table(batch = '2', y = rnorm(10000, 15, sd = 0.5)))
p <- ggplot(dt) +
theme_minimal() +
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.text.x = element_blank(),
axis.text.y = element_blank(),
) +
geom_density(aes(y = y, linetype = batch), color = 'white') +
geom_vline(xintercept = 0, color = '#F8766D')
p <- p + annotate('point', y = 13, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 12, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 14, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 13.2, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 12.8, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 13.1, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 13.5, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 12.5, x = 0, color ='#F8766D')
p <- p + annotate('point', y = 15, x = 0, color ='#F8766D', shape = 17)
p <- p + annotate('point', y = 14, x = 0, color ='#F8766D', shape = 17)
p <- p + annotate('point', y = 16, x = 0, color ='#F8766D', shape = 17)
p <- p + annotate('point', y = 15.2, x = 0, color ='#F8766D', shape = 17)
p <- p + annotate('point', y = 14.8, x = 0, color ='#F8766D', shape = 17)
p <- p + annotate('point', y = 15.1, x = 0, color ='#F8766D', shape = 17)
p <- p + annotate('point', y = 15.5, x = 0, color ='#F8766D', shape = 17)
p <- p + annotate('point', y = 14.5, x = 0, color ='#F8766D', shape = 17)
p <- p + geom_density(aes(y = y, linetype = batch), color = '#F8766D')
# Two sample t test
#------------------
# Single curve
set.seed(1)
y0 <- seq(-4, +4, length.out = 100)
plotdt <- rbind(data.table(y = y0 + 2, x = -dnorm(y0), type = 'sample'))
p <- ggplot(plotdt, aes(x = x, y = y)) + theme_bw() #+ facet_grid(rows = vars(type), scales = 'free_y')
p <- p + theme(panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_blank())
p <- p + scale_y_continuous(breaks = c(0,2,5,8))
p <- p + guides(color = 'none')
p <- p + ylab(expression(Glc)) + xlab(expression(Frequency))
p <- p + geom_path(aes(linetype = type), color = '#F8766D')
# Add triplets
# p <- p + xlim(-0.4, 0.13)
pointdt <- rbind(data.table(y = rnorm(3,2), x = rep(-0.07, 3), i = rep(1,3)),
data.table(y = rnorm(3,2), x = rep(-0.04, 3), i = rep(2,3)),
data.table(y = rnorm(3,2), x = rep(-0.01, 3), i = rep(3,3)),
data.table(y = rnorm(3,2), x = rep( 0.02, 3), i = rep(4,3)),
data.table(y = rnorm(3,2), x = rep( 0.05, 3), i = rep(5,3)),
data.table(y = rnorm(3,2), x = rep( 0.08, 3), i = rep(6,3)))
meandt <- pointdt[, .( y = mean(y),
ymin = mean(y) - sd(y)/2,
ymax = mean(y) + sd(y)/2,
x = unique(x)), by = c('i') ]
(pp <- p + geom_line(data = pointdt, color = '#F8766D', aes(group = i)) + geom_point(data = pointdt, color = '#F8766D') + guides(linetype = 'none'))
(pp <- p + geom_point(data = meandt, size = 3, shape = 3, color = '#F8766D') + geom_line(data = pointdt, color = '#F8766D', aes(group = i)) + geom_point(data = pointdt, color = '#F8766D') + guides(linetype = 'none'))
t0 <- seq(-4, 4, length.out = 100)
tdt <- data.table( y = 2 +t0, x = -dnorm(t0, sd = 1/sqrt(3)), type = 'samplemean(3)')
pp + geom_path(data = tdt, aes(x = x, y = y, linetype = type), color = '#F8766D')
# Add decets
pointdt <- rbind(data.table(y = rnorm(10,2), x = rep(-0.07, 10), i = rep(1,10)),
data.table(y = rnorm(10,2), x = rep(-0.04, 10), i = rep(2,10)),
data.table(y = rnorm(10,2), x = rep(-0.01, 10), i = rep(3,10)),
data.table(y = rnorm(10,2), x = rep( 0.02, 10), i = rep(4,10)),
data.table(y = rnorm(10,2), x = rep( 0.05, 10), i = rep(5,10)),
data.table(y = rnorm(10,2), x = rep( 0.08, 10), i = rep(6,10)))
meandt <- pointdt[, .( y = mean(y),
ymin = mean(y) - sd(y)/2,
ymax = mean(y) + sd(y)/2,
x = unique(x)), by = c('i') ]
(pp <- p + geom_line(data = pointdt, color = '#F8766D', aes(group = i)) + geom_point(data = pointdt, color = '#F8766D') + guides(linetype = 'none'))
(pp <- p + geom_point(data = meandt, size = 3, shape = 3, color = '#F8766D') + geom_line(data = pointdt, color = '#F8766D', aes(group = i)) + geom_point(data = pointdt, color = '#F8766D') + guides(linetype = 'none'))
t0 <- seq(-4, 4, length.out = 100)
tdt <- data.table( y = 2 +t0, x = -dnorm(t0, sd = 1/sqrt(10)), type = 'samplemean(3)')
pp + geom_path(data = tdt, aes(x = x, y = y, linetype = type), color = '#F8766D')
# p value
y0 <- seq(-4,+4, length.out = 100)
x <- dt(y0, df = 3)
ggplot(data.table(x = -x, y = y0), aes(x = x, y = y)) + theme_bw() + geom_path(color = '#F8766D') +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + xlab(expression(density)) + ylab(expression(t))
# Two curves - very near
y0 <- seq(-4, +4, length.out = 100)
x1 <- dnorm(y0)
x2 <- dnorm(y0)
plotdt <- rbind(data.table(x = - x1, y = 2.0 + y0, group = 'group1'),
data.table(x = - x2, y = 2.2 + y0, group = 'group2'))
pointdt <- rbind(data.table(y = rnorm(3, 2.0), x = -0.05, group = 'group1'),
data.table(y = rnorm(3, 2.2), x = 0, group = 'group2'))
meandt <- pointdt[, .(x = unique(x), y = mean(y)), by = 'group']
ggplot(plotdt) +
geom_path(aes(x = x, y = y, color = group)) + theme_bw() +
theme(panel.grid = element_blank()) +
guides(color = FALSE) +
geom_point(data = pointdt, aes(x =x, y = y, color = group)) +
geom_line(data = pointdt, aes(x = x, y = y, color = group, group = group)) +
geom_point(data = meandt, aes(x = x, y = y, color = group), shape = 3)
# Two curves - nearer
y0 <- seq(-4, +4, length.out = 100)
x1 <- dnorm(y0)
x2 <- dnorm(y0)
plotdt <- rbind(data.table(x = - x1, y = 2 + y0, group = 'group1'),
data.table(x = - x2, y = 5 + y0, group = 'group2'))
pointdt <- rbind(data.table(y = rnorm(3, 2), x = 0, group = 'group1'),
data.table(y = rnorm(3, 5), x = 0, group = 'group2'))
meandt <- pointdt[, .(x = unique(x), y = mean(y)), by = 'group']
ggplot(plotdt) +
geom_path(aes(x = x, y = y, color = group)) + theme_bw() +
theme(panel.grid = element_blank()) +
guides(color = FALSE) +
geom_point(data = pointdt, aes(x =x, y = y, color = group)) +
geom_line(data = pointdt, aes(x = x, y = y, color = group, group = group)) +
geom_point(data = meandt, aes(x = x, y = y, color = group), shape = 3)
# Two curves
y0 <- seq(-4, +4, length.out = 100)
plotdt <- rbind(
data.table(y = y0 + 2, x = -dnorm(y0), group = 'Control', type = 'sample', block = 1),
data.table(y = y0 + 5, x = -dnorm(y0), group = 'Diabetic', type = 'sample', block = 2))
p <- ggplot(plotdt, aes(x = x, y = y, color = group, group = group)) + theme_bw() #+ facet_grid(rows = vars(type), scales = 'free_y')
p <- p + theme(panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_blank())
p <- p + scale_y_continuous(breaks = c(0,2,5,8))
p <- p + guides(color = 'none')
p <- p + ylab(expression(Glc)) + xlab(expression(Frequency))
(p <- p + geom_path(linewidth = 0.8))
(p <- p + xlim(-0.4, 0.13))
# p <- p + annotate('text', y = 2, x = -0.25, label = 'Control', color = '#F8766D', hjust = 0)
# p <- p + annotate('text', y = 5, x = -0.25, label = 'Diabetic', color = '#00BFC4', hjust = 0)
# Samples
pointdt <- rbind(data.table(y = c(rnorm(3,2), rnorm(3,5)), x = c(rep(0.08, 3), rep(0.08, 3)), group = c(rep('Control', 3), rep('Diabetic', 3)), i = rep(1,6)),
data.table(y = c(rnorm(3,2), rnorm(3,5)), x = c(rep(0.08, 3), rep(0.08, 3)), group = c(rep('Control', 3), rep('Diabetic', 3)), i = rep(2,6)),
data.table(y = c(rnorm(3,2), rnorm(3,5)), x = c(rep(0.08, 3), rep(0.08, 3)), group = c(rep('Control', 3), rep('Diabetic', 3)), i = rep(3,6)),
data.table(y = c(rnorm(3,2), rnorm(3,5)), x = c(rep(0.08, 3), rep(0.08, 3)), group = c(rep('Control', 3), rep('Diabetic', 3)), i = rep(4,6)),
data.table(y = c(rnorm(3,2), rnorm(3,5)), x = c(rep(0.08, 3), rep(0.08, 3)), group = c(rep('Control', 3), rep('Diabetic', 3)), i = rep(5,6)),
data.table(y = c(rnorm(3,2), rnorm(3,5)), x = c(rep(0.08, 3), rep(0.08, 3)), group = c(rep('Control', 3), rep('Diabetic', 3)), i = rep(6,6)))
meandt <- pointdt[, .( y = mean(y),
ymin = mean(y) - sd(y)/2,
ymax = mean(y) + sd(y)/2,
x = 0.17), by = c('group', 'i') ]
j <- 1
(pp <- p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]))
pp <- pp + xlim(c(-0.4, 0.50))
(pp <- pp + geom_crossbar(data = meandt[ i==j], aes(y = y, ymin = ymin, ymax = ymax), width = 0.02))
pp + annotate('segment', x = 0.35, xend = 0.35, y = meandt[i==j, min(ymax)]+0.2, yend = meandt[i==j, max(ymin)], arrow = arrow(ends = 'both', length = unit(.2, 'cm'))) +
annotate('segment', x = 0.29, xend = 0.45, y = meandt[i==j, min(ymax)], yend = meandt[i==j, min(ymax)]) +
annotate('segment', x = 0.35, xend = 0.35, y = meandt[i==j, min(ymin)+0.1], yend = meandt[i==j, min(ymax)-0.2], arrow = arrow(ends = 'both', length = unit(.2, 'cm'))) +
annotate('segment', x = 0.33, xend = 0.37, y = meandt[i==j, min(ymin)], yend = meandt[i==j, min(ymin)]) +
annotate('point', x = 0.33, y = meandt[i==j, min(ymin)]-0.4) +
annotate('point', x = 0.35, y = meandt[i==j, min(ymin)]-0.4) +
annotate('point', x = 0.37, y = meandt[i==j, min(ymin)]-0.4) +
annotate('text', x = 0.27, y = meandt[i==j, min(ymax)], label = 't = ') +
annotate('text', x = 0.37, y = meandt[i==j, mean(c(min(ymax), max(ymin)))], label = 'between', hjust = 0) +
annotate('text', x = 0.38, y = meandt[i==j, mean(c(min(ymin), min(ymax)))], label = 'within', hjust = 0) +
annotate('text', x = 0.39, y = meandt[i==j, min(ymin)-0.3 ], label = 'sqrt(n)', hjust = 0, parse = TRUE)
j <- 1; (p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]))
j <- 1; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]) + geom_crossbar(data = meandt[i==j], aes(x = x, xmin = xmin, xmax = xmax), width = 0.02, fill = 'white') + geom_point( data = pointdt[i==j])
j <- 2; (p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]))
j <- 2; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]) + geom_crossbar(data = meandt[i==j], aes(x = x, xmin = xmin, xmax = xmax), width = 0.02, fill = 'white') + geom_point( data = pointdt[i==j])
j <- 3; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j])
j <- 3; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]) + geom_crossbar(data = meandt[i==j], aes(x = x, xmin = xmin, xmax = xmax), width = 0.02, fill = 'white') + geom_point( data = pointdt[i==j])
j <- 4; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j])
j <- 4; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]) + geom_crossbar(data = meandt[i==j], aes(x = x, xmin = xmin, xmax = xmax), width = 0.02, fill = 'white') + geom_point( data = pointdt[i==j])
j <- 5; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j])
j <- 5; p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j]) + geom_crossbar(data = meandt[i==j], aes(x = x, xmin = xmin, xmax = xmax), width = 0.02, fill = 'white') + geom_point( data = pointdt[i==j])
# tvalues
tdt <- pointdt[,
.(mean1 = mean(.SD[group == 'Control', x ]),
mean1 = mean(.SD[group == 'T2D', x ]),
sd1 = sd(.SD[group == 'Control', x ]),
sd2 = sd(.SD[group == 'T2D', x ]),
n1 = 3,
n2 = 3), by = 'i']
tdt[, t := (mean2 - mean1) / sqrt((sd1^2/n1 + sd2^2/n2)) ]
tpoints <- data.table(x = seq(-4, +4, length.out = 100))
tpoints[, y := dt(x, df = 4) ]
tpoints[, group := 'T2D-Control']
q <- ggplot(tpoints, aes(x = 2+x, y = y)) + theme_bw() + geom_line() +
xlab(expression(frac(Glc[T2D] - Glc[Control], frac(s, sqrt(n))))) +
ylab(expression(Density))
gridExtra::grid.arrange(p, q, nrow = 2)
j <- 1
pp <- p + geom_point( data = pointdt[i==j]) + geom_line(data = pointdt[i==j])
pp <- pointdt[i==j & group == 'Control'][, pp + annotate('point', x = mean(x), y = mean(y), color = '#F8766D', shape = 108, size = 10) ]
pp <- pointdt[i==j & group == 'T2D' ][, pp + annotate('point', x = mean(x), y = mean(y), color = '#00BFC4', shape = 108, size = 10) ]
pp + coord_flip()
gridExtra::grid.arrange(pp, q, nrow = 2)
pp <- pp + geom_crossbar(data = meandt[i==j], aes(x = x, xmin = xmin, xmax = xmax), width = 0.02, fill = 'white') + geom_point( data = pointdt[i==j])
gridExtra::grid.arrange(pp, q, nrow = 2)
pp + annotate(x = )
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.