Itroduction to R

Introduction to R language

Large Data Sets
Modeling and simulations
Statistical analysis
Extensive computational task

Genomics, transcryptomycs
Computational evolutionary biolo
Structural biology
Image analysis
Quantative ecology

3 diensions of languages

High vs low
General vs targeted
Interpretive vs compiled

Structure of R language

S language
Functions written in R itself

Specific task

Multiple testing
MCMC
Bias
Gauss
Plotting
Sequencing

Check graphics system

plot(density(rnorm(100)), col = "red")

Variables types

x = 5
x <- 5
assign("x", 5)

Commands and Basic Functions

function c()

x <- c(1, 3, 6, 7)

Vectors

numerical
character
logical

(factors are not classic vector objects)

char <- c("8", "edge", "turn8k")
logic <- c(TRUE, FALSE, TRUE, FALSE)

Dynamic typisation

dynam <- c(8, "dds", TRUE)
dynam <- c(1, 0, 1, 1, TRUE)
dynam

## [1] 1 0 1 1 1

Priority Char->integer->Logic

Functions

x=function(arg1,arg2,…)

Invocation - function call

args:

tagged(named)
positional

Positional: log(x,base)

Functions

log(x, 10)

## [1] 0.0000000 0.4771213 0.7781513 0.8450980

Tagged: log(base=base,x)

log(base = 10, x)

## [1] 0.0000000 0.4771213 0.7781513 0.8450980

Logical operations

<, >, <=, >=, ==

x = 10
x < 5

## [1] FALSE

Logical operations

x > 5

## [1] TRUE

x == 10

## [1] TRUE

Math operations

+, -, *, /, ^, sin(), cos(), sqrt(), log()

x^10

## [1] 1e+10

Quiz

x = 10/(5 - 5)
x

## [1] Inf

Recycling Rule

x <- c(2, 4, 5, 3, -4, 0)
x * 5

## [1]  10  20  25  15 -20   0

y <- c(5, 3)
x * y

## [1]  10  12  25   9 -20   0

Recycling Rule

## [1]  2  4  5  3 -4  0

z <- c(1, 2, 3, 4)
x * z

## Warning in x * z: longer object length is not a multiple of shorter object
## length

## [1]  2  8 15 12 -4  0

Length function

length(x)

## [1] 6

More basic functions

log(), mean(), min(), max(), sum(), prod(), abs()

x <- c(3, 4, 6, -7, 8)
mean = sum(x)/length(x)
mean

## [1] 2.8

Regular sequenses

x = 2:10
y = 5:1
z = -5:10
w = -5:-10
x

## [1]  2  3  4  5  6  7  8  9 10

## [1] 5 4 3 2 1

Regular sequence

##  [1] -5 -4 -3 -2 -1  0  1  2  3  4  5  6  7  8  9 10

## [1]  -5  -6  -7  -8  -9 -10

Regular sequence

seq(from=,to=,by=)

z = seq(2, 5, 0.5)
x = seq(3, 9.1, 0.1)
y = seq(9, 3, -0.2)
length(x)

## [1] 62

Regular sequence

length(y)

## [1] 31

x * y

##  [1] 27.00 27.28 27.52 27.72 27.88 28.00 28.08 28.12 28.12 28.08 28.00
## [12] 27.88 27.72 27.52 27.28 27.00 26.68 26.32 25.92 25.48 25.00 24.48
## [23] 23.92 23.32 22.68 22.00 21.28 20.52 19.72 18.88 18.00 54.90 54.56
## [34] 54.18 53.76 53.30 52.80 52.26 51.68 51.06 50.40 49.70 48.96 48.18
## [45] 47.36 46.50 45.60 44.66 43.68 42.66 41.60 40.50 39.36 38.18 36.96
## [56] 35.70 34.40 33.06 31.68 30.26 28.80 27.30

Regular sequence

rep(x, times=)

x = c("A", "B", "C")
rep(x, 4)

##  [1] "A" "B" "C" "A" "B" "C" "A" "B" "C" "A" "B" "C"

Logical vectors

mode(x)

x <- 1:10
y <- x <= -5
mode(x)

## [1] "numeric"

Logical vectors

mode(y)

## [1] "logical"

mode(mode(x))

## [1] "character"

Vector indexation

R is 1 based language

x = 1:20
x[2]

## [1] 2

x[0]

## integer(0)

Vector indexation

x[5:9]

## [1] 5 6 7 8 9

x[c(3, 7, 8, 9, 20)]

## [1]  3  7  8  9 20

Vector indexation

x[-19]

##  [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 20

x[-(1:6)]

##  [1]  7  8  9 10 11 12 13 14 15 16 17 18 19 20

Vector indexation

x[x > 10]

##  [1] 11 12 13 14 15 16 17 18 19 20

x[TRUE]

##  [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20

y = c(TRUE, FALSE)
x[y]

##  [1]  1  3  5  7  9 11 13 15 17 19

Adding to vectors

vector <- c()
v2 <- c(TRUE, FALSE, TRUE, TRUE, FALSE, TRUE)
vector = c(v2, vector)
vector = c(F, vector)
x = 1:3
x = c(5, x)
x

## [1] 5 1 2 3

Named vectors

x = 1:5
names(x)

## NULL

names(x) <- c("First", "Second", "Third", "Forth", "Fith")
names(x)

## [1] "First"  "Second" "Third"  "Forth"  "Fith"

x["First"]

## First 
##     1

Vector attributes

length() names() mode()

Some tricks

log(3) == log(3, base = exp(1))

## [1] TRUE

x = seq(5, 100, 0.1)
x[length(x)]

## [1] 100

Sort and order functions

x <- c(-10, 2, 78, 34, -98, 23, 0, -8)
order(x)

## [1] 5 1 8 7 2 6 4 3

sort(x)

## [1] -98 -10  -8   0   2  23  34  78

sort(x) == x[order(x)]

## [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE

Quiz

Turn vector x upside down

Quiz - turn vector upside down

a <- seq(-8,10,.5)
a

##  [1] -8.0 -7.5 -7.0 -6.5 -6.0 -5.5 -5.0 -4.5 -4.0 -3.5 -3.0 -2.5 -2.0 -1.5
## [15] -1.0 -0.5  0.0  0.5  1.0  1.5  2.0  2.5  3.0  3.5  4.0  4.5  5.0  5.5
## [29]  6.0  6.5  7.0  7.5  8.0  8.5  9.0  9.5 10.0

x = a[length(a):1]
x

##  [1] 10.0  9.5  9.0  8.5  8.0  7.5  7.0  6.5  6.0  5.5  5.0  4.5  4.0  3.5
## [15]  3.0  2.5  2.0  1.5  1.0  0.5  0.0 -0.5 -1.0 -1.5 -2.0 -2.5 -3.0 -3.5
## [29] -4.0 -4.5 -5.0 -5.5 -6.0 -6.5 -7.0 -7.5 -8.0

Quiz

Insert in middle of vector a - 99

Quiz - insert in middle of vector a - 99

y = c(a[1:round(length(a)/2)], 99, a[(round(length(a)/2) + 1):length(a)])

Quiz

Prove arcos(cos(x)) = x

Quiz prove arcos(cos(x)) = x

x = 0:3
y = acos(cos(x))
x == y

## [1]  TRUE FALSE  TRUE FALSE

Lets remember that we can name vectores

x = c(sin(10), log(5,8), log(3,exp(1)), log(38.6,10), cos(pi + 1), exp(1)^(cos(0)), atan(+Inf))
names(x) = c("sin(10)", "log8(5)", "ln3", "lg(38.6)", "cos(pi+1)", "e^cos(0)", "arctn(+Inf)");
sort(x)

##     sin(10)   cos(pi+1)     log8(5)         ln3 arctn(+Inf)    lg(38.6) 
##  -0.5440211  -0.5403023   0.7739760   1.0986123   1.5707963   1.5865873 
##    e^cos(0) 
##   2.7182818

Boolean operations

! = not
| = or
& = and

A U B - conjunction

Quiz - Boolean operations

x = seq(-10,10,.01)

Get all numbers from -10 to -3 and from 0 to 6, but not 3

Quiz - Boolean operations

x = seq(-10,10,.01)
y = x[(x > -10 & x < -3) | (x > 0 & x < 6 & x != 3)]
y

##    [1] -9.99 -9.98 -9.97 -9.96 -9.95 -9.94 -9.93 -9.92 -9.91 -9.90 -9.89
##   [12] -9.88 -9.87 -9.86 -9.85 -9.84 -9.83 -9.82 -9.81 -9.80 -9.79 -9.78
##   [23] -9.77 -9.76 -9.75 -9.74 -9.73 -9.72 -9.71 -9.70 -9.69 -9.68 -9.67
##   [34] -9.66 -9.65 -9.64 -9.63 -9.62 -9.61 -9.60 -9.59 -9.58 -9.57 -9.56
##   [45] -9.55 -9.54 -9.53 -9.52 -9.51 -9.50 -9.49 -9.48 -9.47 -9.46 -9.45
##   [56] -9.44 -9.43 -9.42 -9.41 -9.40 -9.39 -9.38 -9.37 -9.36 -9.35 -9.34
##   [67] -9.33 -9.32 -9.31 -9.30 -9.29 -9.28 -9.27 -9.26 -9.25 -9.24 -9.23
##   [78] -9.22 -9.21 -9.20 -9.19 -9.18 -9.17 -9.16 -9.15 -9.14 -9.13 -9.12
##   [89] -9.11 -9.10 -9.09 -9.08 -9.07 -9.06 -9.05 -9.04 -9.03 -9.02 -9.01
##  [100] -9.00 -8.99 -8.98 -8.97 -8.96 -8.95 -8.94 -8.93 -8.92 -8.91 -8.90
##  [111] -8.89 -8.88 -8.87 -8.86 -8.85 -8.84 -8.83 -8.82 -8.81 -8.80 -8.79
##  [122] -8.78 -8.77 -8.76 -8.75 -8.74 -8.73 -8.72 -8.71 -8.70 -8.69 -8.68
##  [133] -8.67 -8.66 -8.65 -8.64 -8.63 -8.62 -8.61 -8.60 -8.59 -8.58 -8.57
##  [144] -8.56 -8.55 -8.54 -8.53 -8.52 -8.51 -8.50 -8.49 -8.48 -8.47 -8.46
##  [155] -8.45 -8.44 -8.43 -8.42 -8.41 -8.40 -8.39 -8.38 -8.37 -8.36 -8.35
##  [166] -8.34 -8.33 -8.32 -8.31 -8.30 -8.29 -8.28 -8.27 -8.26 -8.25 -8.24
##  [177] -8.23 -8.22 -8.21 -8.20 -8.19 -8.18 -8.17 -8.16 -8.15 -8.14 -8.13
##  [188] -8.12 -8.11 -8.10 -8.09 -8.08 -8.07 -8.06 -8.05 -8.04 -8.03 -8.02
##  [199] -8.01 -8.00 -7.99 -7.98 -7.97 -7.96 -7.95 -7.94 -7.93 -7.92 -7.91
##  [210] -7.90 -7.89 -7.88 -7.87 -7.86 -7.85 -7.84 -7.83 -7.82 -7.81 -7.80
##  [221] -7.79 -7.78 -7.77 -7.76 -7.75 -7.74 -7.73 -7.72 -7.71 -7.70 -7.69
##  [232] -7.68 -7.67 -7.66 -7.65 -7.64 -7.63 -7.62 -7.61 -7.60 -7.59 -7.58
##  [243] -7.57 -7.56 -7.55 -7.54 -7.53 -7.52 -7.51 -7.50 -7.49 -7.48 -7.47
##  [254] -7.46 -7.45 -7.44 -7.43 -7.42 -7.41 -7.40 -7.39 -7.38 -7.37 -7.36
##  [265] -7.35 -7.34 -7.33 -7.32 -7.31 -7.30 -7.29 -7.28 -7.27 -7.26 -7.25
##  [276] -7.24 -7.23 -7.22 -7.21 -7.20 -7.19 -7.18 -7.17 -7.16 -7.15 -7.14
##  [287] -7.13 -7.12 -7.11 -7.10 -7.09 -7.08 -7.07 -7.06 -7.05 -7.04 -7.03
##  [298] -7.02 -7.01 -7.00 -6.99 -6.98 -6.97 -6.96 -6.95 -6.94 -6.93 -6.92
##  [309] -6.91 -6.90 -6.89 -6.88 -6.87 -6.86 -6.85 -6.84 -6.83 -6.82 -6.81
##  [320] -6.80 -6.79 -6.78 -6.77 -6.76 -6.75 -6.74 -6.73 -6.72 -6.71 -6.70
##  [331] -6.69 -6.68 -6.67 -6.66 -6.65 -6.64 -6.63 -6.62 -6.61 -6.60 -6.59
##  [342] -6.58 -6.57 -6.56 -6.55 -6.54 -6.53 -6.52 -6.51 -6.50 -6.49 -6.48
##  [353] -6.47 -6.46 -6.45 -6.44 -6.43 -6.42 -6.41 -6.40 -6.39 -6.38 -6.37
##  [364] -6.36 -6.35 -6.34 -6.33 -6.32 -6.31 -6.30 -6.29 -6.28 -6.27 -6.26
##  [375] -6.25 -6.24 -6.23 -6.22 -6.21 -6.20 -6.19 -6.18 -6.17 -6.16 -6.15
##  [386] -6.14 -6.13 -6.12 -6.11 -6.10 -6.09 -6.08 -6.07 -6.06 -6.05 -6.04
##  [397] -6.03 -6.02 -6.01 -6.00 -5.99 -5.98 -5.97 -5.96 -5.95 -5.94 -5.93
##  [408] -5.92 -5.91 -5.90 -5.89 -5.88 -5.87 -5.86 -5.85 -5.84 -5.83 -5.82
##  [419] -5.81 -5.80 -5.79 -5.78 -5.77 -5.76 -5.75 -5.74 -5.73 -5.72 -5.71
##  [430] -5.70 -5.69 -5.68 -5.67 -5.66 -5.65 -5.64 -5.63 -5.62 -5.61 -5.60
##  [441] -5.59 -5.58 -5.57 -5.56 -5.55 -5.54 -5.53 -5.52 -5.51 -5.50 -5.49
##  [452] -5.48 -5.47 -5.46 -5.45 -5.44 -5.43 -5.42 -5.41 -5.40 -5.39 -5.38
##  [463] -5.37 -5.36 -5.35 -5.34 -5.33 -5.32 -5.31 -5.30 -5.29 -5.28 -5.27
##  [474] -5.26 -5.25 -5.24 -5.23 -5.22 -5.21 -5.20 -5.19 -5.18 -5.17 -5.16
##  [485] -5.15 -5.14 -5.13 -5.12 -5.11 -5.10 -5.09 -5.08 -5.07 -5.06 -5.05
##  [496] -5.04 -5.03 -5.02 -5.01 -5.00 -4.99 -4.98 -4.97 -4.96 -4.95 -4.94
##  [507] -4.93 -4.92 -4.91 -4.90 -4.89 -4.88 -4.87 -4.86 -4.85 -4.84 -4.83
##  [518] -4.82 -4.81 -4.80 -4.79 -4.78 -4.77 -4.76 -4.75 -4.74 -4.73 -4.72
##  [529] -4.71 -4.70 -4.69 -4.68 -4.67 -4.66 -4.65 -4.64 -4.63 -4.62 -4.61
##  [540] -4.60 -4.59 -4.58 -4.57 -4.56 -4.55 -4.54 -4.53 -4.52 -4.51 -4.50
##  [551] -4.49 -4.48 -4.47 -4.46 -4.45 -4.44 -4.43 -4.42 -4.41 -4.40 -4.39
##  [562] -4.38 -4.37 -4.36 -4.35 -4.34 -4.33 -4.32 -4.31 -4.30 -4.29 -4.28
##  [573] -4.27 -4.26 -4.25 -4.24 -4.23 -4.22 -4.21 -4.20 -4.19 -4.18 -4.17
##  [584] -4.16 -4.15 -4.14 -4.13 -4.12 -4.11 -4.10 -4.09 -4.08 -4.07 -4.06
##  [595] -4.05 -4.04 -4.03 -4.02 -4.01 -4.00 -3.99 -3.98 -3.97 -3.96 -3.95
##  [606] -3.94 -3.93 -3.92 -3.91 -3.90 -3.89 -3.88 -3.87 -3.86 -3.85 -3.84
##  [617] -3.83 -3.82 -3.81 -3.80 -3.79 -3.78 -3.77 -3.76 -3.75 -3.74 -3.73
##  [628] -3.72 -3.71 -3.70 -3.69 -3.68 -3.67 -3.66 -3.65 -3.64 -3.63 -3.62
##  [639] -3.61 -3.60 -3.59 -3.58 -3.57 -3.56 -3.55 -3.54 -3.53 -3.52 -3.51
##  [650] -3.50 -3.49 -3.48 -3.47 -3.46 -3.45 -3.44 -3.43 -3.42 -3.41 -3.40
##  [661] -3.39 -3.38 -3.37 -3.36 -3.35 -3.34 -3.33 -3.32 -3.31 -3.30 -3.29
##  [672] -3.28 -3.27 -3.26 -3.25 -3.24 -3.23 -3.22 -3.21 -3.20 -3.19 -3.18
##  [683] -3.17 -3.16 -3.15 -3.14 -3.13 -3.12 -3.11 -3.10 -3.09 -3.08 -3.07
##  [694] -3.06 -3.05 -3.04 -3.03 -3.02 -3.01  0.01  0.02  0.03  0.04  0.05
##  [705]  0.06  0.07  0.08  0.09  0.10  0.11  0.12  0.13  0.14  0.15  0.16
##  [716]  0.17  0.18  0.19  0.20  0.21  0.22  0.23  0.24  0.25  0.26  0.27
##  [727]  0.28  0.29  0.30  0.31  0.32  0.33  0.34  0.35  0.36  0.37  0.38
##  [738]  0.39  0.40  0.41  0.42  0.43  0.44  0.45  0.46  0.47  0.48  0.49
##  [749]  0.50  0.51  0.52  0.53  0.54  0.55  0.56  0.57  0.58  0.59  0.60
##  [760]  0.61  0.62  0.63  0.64  0.65  0.66  0.67  0.68  0.69  0.70  0.71
##  [771]  0.72  0.73  0.74  0.75  0.76  0.77  0.78  0.79  0.80  0.81  0.82
##  [782]  0.83  0.84  0.85  0.86  0.87  0.88  0.89  0.90  0.91  0.92  0.93
##  [793]  0.94  0.95  0.96  0.97  0.98  0.99  1.00  1.01  1.02  1.03  1.04
##  [804]  1.05  1.06  1.07  1.08  1.09  1.10  1.11  1.12  1.13  1.14  1.15
##  [815]  1.16  1.17  1.18  1.19  1.20  1.21  1.22  1.23  1.24  1.25  1.26
##  [826]  1.27  1.28  1.29  1.30  1.31  1.32  1.33  1.34  1.35  1.36  1.37
##  [837]  1.38  1.39  1.40  1.41  1.42  1.43  1.44  1.45  1.46  1.47  1.48
##  [848]  1.49  1.50  1.51  1.52  1.53  1.54  1.55  1.56  1.57  1.58  1.59
##  [859]  1.60  1.61  1.62  1.63  1.64  1.65  1.66  1.67  1.68  1.69  1.70
##  [870]  1.71  1.72  1.73  1.74  1.75  1.76  1.77  1.78  1.79  1.80  1.81
##  [881]  1.82  1.83  1.84  1.85  1.86  1.87  1.88  1.89  1.90  1.91  1.92
##  [892]  1.93  1.94  1.95  1.96  1.97  1.98  1.99  2.00  2.01  2.02  2.03
##  [903]  2.04  2.05  2.06  2.07  2.08  2.09  2.10  2.11  2.12  2.13  2.14
##  [914]  2.15  2.16  2.17  2.18  2.19  2.20  2.21  2.22  2.23  2.24  2.25
##  [925]  2.26  2.27  2.28  2.29  2.30  2.31  2.32  2.33  2.34  2.35  2.36
##  [936]  2.37  2.38  2.39  2.40  2.41  2.42  2.43  2.44  2.45  2.46  2.47
##  [947]  2.48  2.49  2.50  2.51  2.52  2.53  2.54  2.55  2.56  2.57  2.58
##  [958]  2.59  2.60  2.61  2.62  2.63  2.64  2.65  2.66  2.67  2.68  2.69
##  [969]  2.70  2.71  2.72  2.73  2.74  2.75  2.76  2.77  2.78  2.79  2.80
##  [980]  2.81  2.82  2.83  2.84  2.85  2.86  2.87  2.88  2.89  2.90  2.91
##  [991]  2.92  2.93  2.94  2.95  2.96  2.97  2.98  2.99  3.01  3.02  3.03
## [1002]  3.04  3.05  3.06  3.07  3.08  3.09  3.10  3.11  3.12  3.13  3.14
## [1013]  3.15  3.16  3.17  3.18  3.19  3.20  3.21  3.22  3.23  3.24  3.25
## [1024]  3.26  3.27  3.28  3.29  3.30  3.31  3.32  3.33  3.34  3.35  3.36
## [1035]  3.37  3.38  3.39  3.40  3.41  3.42  3.43  3.44  3.45  3.46  3.47
## [1046]  3.48  3.49  3.50  3.51  3.52  3.53  3.54  3.55  3.56  3.57  3.58
## [1057]  3.59  3.60  3.61  3.62  3.63  3.64  3.65  3.66  3.67  3.68  3.69
## [1068]  3.70  3.71  3.72  3.73  3.74  3.75  3.76  3.77  3.78  3.79  3.80
## [1079]  3.81  3.82  3.83  3.84  3.85  3.86  3.87  3.88  3.89  3.90  3.91
## [1090]  3.92  3.93  3.94  3.95  3.96  3.97  3.98  3.99  4.00  4.01  4.02
## [1101]  4.03  4.04  4.05  4.06  4.07  4.08  4.09  4.10  4.11  4.12  4.13
## [1112]  4.14  4.15  4.16  4.17  4.18  4.19  4.20  4.21  4.22  4.23  4.24
## [1123]  4.25  4.26  4.27  4.28  4.29  4.30  4.31  4.32  4.33  4.34  4.35
## [1134]  4.36  4.37  4.38  4.39  4.40  4.41  4.42  4.43  4.44  4.45  4.46
## [1145]  4.47  4.48  4.49  4.50  4.51  4.52  4.53  4.54  4.55  4.56  4.57
## [1156]  4.58  4.59  4.60  4.61  4.62  4.63  4.64  4.65  4.66  4.67  4.68
## [1167]  4.69  4.70  4.71  4.72  4.73  4.74  4.75  4.76  4.77  4.78  4.79
## [1178]  4.80  4.81  4.82  4.83  4.84  4.85  4.86  4.87  4.88  4.89  4.90
## [1189]  4.91  4.92  4.93  4.94  4.95  4.96  4.97  4.98  4.99  5.00  5.01
## [1200]  5.02  5.03  5.04  5.05  5.06  5.07  5.08  5.09  5.10  5.11  5.12
## [1211]  5.13  5.14  5.15  5.16  5.17  5.18  5.19  5.20  5.21  5.22  5.23
## [1222]  5.24  5.25  5.26  5.27  5.28  5.29  5.30  5.31  5.32  5.33  5.34
## [1233]  5.35  5.36  5.37  5.38  5.39  5.40  5.41  5.42  5.43  5.44  5.45
## [1244]  5.46  5.47  5.48  5.49  5.50  5.51  5.52  5.53  5.54  5.55  5.56
## [1255]  5.57  5.58  5.59  5.60  5.61  5.62  5.63  5.64  5.65  5.66  5.67
## [1266]  5.68  5.69  5.70  5.71  5.72  5.73  5.74  5.75  5.76  5.77  5.78
## [1277]  5.79  5.80  5.81  5.82  5.83  5.84  5.85  5.86  5.87  5.88  5.89
## [1288]  5.90  5.91  5.92  5.93  5.94  5.95  5.96  5.97  5.98  5.99

Factors and summary() function

x = factor(“Mouse”)

f = c(rep("mouse", 3), rep("rat", 2), rep("fly", 11))
f = rep(c("mouse", "rat", "fly"), c(3, 2, 11))
x = factor(f)
summary(x)

##   fly mouse   rat 
##    11     3     2

summary(f)

##    Length     Class      Mode 
##        16 character character

Factors and summary() function

summary(1:10)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    1.00    3.25    5.50    5.50    7.75   10.00

summary(1:10)[4]

## Mean 
##  5.5

Quiz - factors

Make vector of DNA and calculate ratio of each nucleotide

dna=factor(rep(c("T","G","C","A"),c(16,38,6,10)))

Quiz - factors

dna=factor(rep(c("T","G","C","A"),c(16,38,6,10)))
ratio=summary(dna)/sum(summary(dna))
ratio

##          A          C          G          T 
## 0.14285714 0.08571429 0.54285714 0.22857143

Function sample()

sample:

mixing
generating

Function sample()

dna

##  [1] T T T T T T T T T T T T T T T T G G G G G G G G G G G G G G G G G G G
## [36] G G G G G G G G G G G G G G G G G G G C C C C C C A A A A A A A A A A
## Levels: A C G T

sample(dna)

##  [1] G C G G G T G T A G G G T A C G G C G T G G T G G G G G G G G T G G G
## [36] A T T A G G G C A G G A G A A G T G T T C T G G A T G A T T G C T G G
## Levels: A C G T

#sample(dna,size = 84, replace = FALSE) - will give error

Function sample()

sample(dna,size = 84, replace = TRUE)

##  [1] G G T G T G G C T G T C G C G T C G G C G A G T G T G A G C G G G C G
## [36] G G C T C G C G G G A G A A G G G G G T T G G A T G T T G C G A G G G
## [71] G T A G C G G A G G A T G T
## Levels: A C G T

sampledna = sample(c("A","T","G","C"), size = 10000, replace = TRUE)
ratio = summary(factor(sampledna)) / length(sampledna)
ratio2 = summary(factor(dna)) / length(dna)

Function sample()

ratio

##      A      C      G      T 
## 0.2500 0.2484 0.2489 0.2527

ratio2

##          A          C          G          T 
## 0.14285714 0.08571429 0.54285714 0.22857143

Functions union(x,y),intersect(x,y),setdiff(x,y)

x=1:10
y=6:14
union(x,y)

##  [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14

intersect(x,y)

## [1]  6  7  8  9 10

setdiff(x,y)

## [1] 1 2 3 4 5

setdiff(y,x)

## [1] 11 12 13 14

Removing all variables in session

rm(list=ls())

Function cumsum()

cumsum(1:10)

##  [1]  1  3  6 10 15 21 28 36 45 55

Quiz

make big sequence with ratio of G=0.5

Quiz make big sequence with ratio of G=0.5

dna2=sample(c("A","T","G","G","G","C"), size=3826513,replace=TRUE)
ratio=summary(factor(dna2))/length(dna2)
ratio

##         A         C         G         T 
## 0.1666951 0.1668088 0.4997414 0.1667547

dna2=sample(c("A","T","G","C"), size=3826513,prob=c(.5/3,.5/3,.5,.5/3),replace=TRUE)
ratio=summary(factor(dna2))/length(dna2)
ratio

##         A         C         G         T 
## 0.1662532 0.1670022 0.4998870 0.1668577

Subsettings

iris[iris$Species==c("setosa","virginica"),]

##     Sepal.Length Sepal.Width Petal.Length Petal.Width   Species
## 1            5.1         3.5          1.4         0.2    setosa
## 3            4.7         3.2          1.3         0.2    setosa
## 5            5.0         3.6          1.4         0.2    setosa
## 7            4.6         3.4          1.4         0.3    setosa
## 9            4.4         2.9          1.4         0.2    setosa
## 11           5.4         3.7          1.5         0.2    setosa
## 13           4.8         3.0          1.4         0.1    setosa
## 15           5.8         4.0          1.2         0.2    setosa
## 17           5.4         3.9          1.3         0.4    setosa
## 19           5.7         3.8          1.7         0.3    setosa
## 21           5.4         3.4          1.7         0.2    setosa
## 23           4.6         3.6          1.0         0.2    setosa
## 25           4.8         3.4          1.9         0.2    setosa
## 27           5.0         3.4          1.6         0.4    setosa
## 29           5.2         3.4          1.4         0.2    setosa
## 31           4.8         3.1          1.6         0.2    setosa
## 33           5.2         4.1          1.5         0.1    setosa
## 35           4.9         3.1          1.5         0.2    setosa
## 37           5.5         3.5          1.3         0.2    setosa
## 39           4.4         3.0          1.3         0.2    setosa
## 41           5.0         3.5          1.3         0.3    setosa
## 43           4.4         3.2          1.3         0.2    setosa
## 45           5.1         3.8          1.9         0.4    setosa
## 47           5.1         3.8          1.6         0.2    setosa
## 49           5.3         3.7          1.5         0.2    setosa
## 102          5.8         2.7          5.1         1.9 virginica
## 104          6.3         2.9          5.6         1.8 virginica
## 106          7.6         3.0          6.6         2.1 virginica
## 108          7.3         2.9          6.3         1.8 virginica
## 110          7.2         3.6          6.1         2.5 virginica
## 112          6.4         2.7          5.3         1.9 virginica
## 114          5.7         2.5          5.0         2.0 virginica
## 116          6.4         3.2          5.3         2.3 virginica
## 118          7.7         3.8          6.7         2.2 virginica
## 120          6.0         2.2          5.0         1.5 virginica
## 122          5.6         2.8          4.9         2.0 virginica
## 124          6.3         2.7          4.9         1.8 virginica
## 126          7.2         3.2          6.0         1.8 virginica
## 128          6.1         3.0          4.9         1.8 virginica
## 130          7.2         3.0          5.8         1.6 virginica
## 132          7.9         3.8          6.4         2.0 virginica
## 134          6.3         2.8          5.1         1.5 virginica
## 136          7.7         3.0          6.1         2.3 virginica
## 138          6.4         3.1          5.5         1.8 virginica
## 140          6.9         3.1          5.4         2.1 virginica
## 142          6.9         3.1          5.1         2.3 virginica
## 144          6.8         3.2          5.9         2.3 virginica
## 146          6.7         3.0          5.2         2.3 virginica
## 148          6.5         3.0          5.2         2.0 virginica
## 150          5.9         3.0          5.1         1.8 virginica

iris[iris$Species=="setosa" | iris$Species=="virginica",c("Petal.Length","Species")]

##     Petal.Length   Species
## 1            1.4    setosa
## 2            1.4    setosa
## 3            1.3    setosa
## 4            1.5    setosa
## 5            1.4    setosa
## 6            1.7    setosa
## 7            1.4    setosa
## 8            1.5    setosa
## 9            1.4    setosa
## 10           1.5    setosa
## 11           1.5    setosa
## 12           1.6    setosa
## 13           1.4    setosa
## 14           1.1    setosa
## 15           1.2    setosa
## 16           1.5    setosa
## 17           1.3    setosa
## 18           1.4    setosa
## 19           1.7    setosa
## 20           1.5    setosa
## 21           1.7    setosa
## 22           1.5    setosa
## 23           1.0    setosa
## 24           1.7    setosa
## 25           1.9    setosa
## 26           1.6    setosa
## 27           1.6    setosa
## 28           1.5    setosa
## 29           1.4    setosa
## 30           1.6    setosa
## 31           1.6    setosa
## 32           1.5    setosa
## 33           1.5    setosa
## 34           1.4    setosa
## 35           1.5    setosa
## 36           1.2    setosa
## 37           1.3    setosa
## 38           1.4    setosa
## 39           1.3    setosa
## 40           1.5    setosa
## 41           1.3    setosa
## 42           1.3    setosa
## 43           1.3    setosa
## 44           1.6    setosa
## 45           1.9    setosa
## 46           1.4    setosa
## 47           1.6    setosa
## 48           1.4    setosa
## 49           1.5    setosa
## 50           1.4    setosa
## 101          6.0 virginica
## 102          5.1 virginica
## 103          5.9 virginica
## 104          5.6 virginica
## 105          5.8 virginica
## 106          6.6 virginica
## 107          4.5 virginica
## 108          6.3 virginica
## 109          5.8 virginica
## 110          6.1 virginica
## 111          5.1 virginica
## 112          5.3 virginica
## 113          5.5 virginica
## 114          5.0 virginica
## 115          5.1 virginica
## 116          5.3 virginica
## 117          5.5 virginica
## 118          6.7 virginica
## 119          6.9 virginica
## 120          5.0 virginica
## 121          5.7 virginica
## 122          4.9 virginica
## 123          6.7 virginica
## 124          4.9 virginica
## 125          5.7 virginica
## 126          6.0 virginica
## 127          4.8 virginica
## 128          4.9 virginica
## 129          5.6 virginica
## 130          5.8 virginica
## 131          6.1 virginica
## 132          6.4 virginica
## 133          5.6 virginica
## 134          5.1 virginica
## 135          5.6 virginica
## 136          6.1 virginica
## 137          5.6 virginica
## 138          5.5 virginica
## 139          4.8 virginica
## 140          5.4 virginica
## 141          5.6 virginica
## 142          5.1 virginica
## 143          5.1 virginica
## 144          5.9 virginica
## 145          5.7 virginica
## 146          5.2 virginica
## 147          5.0 virginica
## 148          5.2 virginica
## 149          5.4 virginica
## 150          5.1 virginica

All main data types

Type	Function	Options
Vector	c()	[i] -position or logic
Factor	factor()	[] - position or logic
Matrix	matrix()	[row,col]; [i] - positional logical
List	list()	[[i]], $
dataframe	data.frame()	[,] $

Quiz - subsetting

Find species with Petal.Length>2 but <3, show them and their abundance

Quiz - subsetting

summary(factor(iris[(iris$Petal.Length>2 & iris$Petal.Length<6),"Species" ]))

## versicolor  virginica 
##         50         39

Functions

my_func = function(p) 
  {
    x=p^2
    y=x^3
    print("result")
    return(c(x,y))
  }
my_func(2)

## [1] "result"

## [1]  4 64

Functions

mathses = function(p,q)
  {
    result = c(p+q,log(p+q,10),exp(p+q))
    names(result) = c("summ", "log","exp")
    return(result)
  }
mathses(2,3)

##      summ       log       exp 
##   5.00000   0.69897 148.41316

Conditional instructions if functions

mf = function(p)
  {
  
    if (p>0)
      {
        x=log(p)
        return(x)
      }
    else
      {
        return(NULL)      
      }
  }
mf(-1)

## NULL

Quiz conditional questions

gamma(x) gives !(x-1), we need to make function which makes true factorial

Quiz conditional questions

myfactorial = function(p) 
  {
    if (p>0 & p%%1==0)
      {return(gamma(p+1))}
    else
      {return(NULL)}
  }
  
  myfactorial(5)

## [1] 120

Quiz conditional questions

 myfactorial = function(p) 
  {
    if (p>0 & p%%1==0)
      {return(gamma(p+1))}
    else
      {return(NULL)}
  }