第三课

df1 <- data.frame(gene = paste0("gene",1:4),
                  change = rep(c("up","down"),each = 2),
                  score = c(3,5,-2,-4))
df1

##    gene change score
## 1 gene1     up     3
## 2 gene2     up     5
## 3 gene3   down    -2
## 4 gene4   down    -4

df2 <- read.csv("gene.csv")
df2

##    gene change score
## 1 gene1     up     5
## 2 gene2     up     3
## 3 gene3   down    -2
## 4 gene4   down    -4

dim(df1)

## [1] 4 3

nrow(df1)

## [1] 4

ncol(df1)

## [1] 3

rownames(df1)

## [1] "1" "2" "3" "4"

colnames(df1)

## [1] "gene"   "change" "score"

df1$gene

## [1] "gene1" "gene2" "gene3" "gene4"

df1$change

## [1] "up"   "up"   "down" "down"

df1$score

## [1]  3  5 -2 -4

mean(df1$score)

## [1] 0.5

df1[2,2]

## [1] "up"

df1[2,]

##    gene change score
## 2 gene2     up     5

df1[,2]

## [1] "up"   "up"   "down" "down"

df1[c(1,3),1:2]

##    gene change
## 1 gene1     up
## 3 gene3   down

df1[,"gene"]

## [1] "gene1" "gene2" "gene3" "gene4"

df1[,c("gene","change")]

##    gene change
## 1 gene1     up
## 2 gene2     up
## 3 gene3   down
## 4 gene4   down

df1[df1$score>0,]

##    gene change score
## 1 gene1     up     3
## 2 gene2     up     5

df1$gene[df1$score>0]

## [1] "gene1" "gene2"

df1[,ncol(df1)]

## [1]  3  5 -2 -4

df1[,-ncol(df1)]

##    gene change
## 1 gene1     up
## 2 gene2     up
## 3 gene3   down
## 4 gene4   down

df1[3,3] <- 5
df1

##    gene change score
## 1 gene1     up     3
## 2 gene2     up     5
## 3 gene3   down     5
## 4 gene4   down    -4

df1$score <- c(12,23,50,2)
df1

##    gene change score
## 1 gene1     up    12
## 2 gene2     up    23
## 3 gene3   down    50
## 4 gene4   down     2

df1$p.value <- c(0.01,0.02,0.07,0.05)
df1

##    gene change score p.value
## 1 gene1     up    12    0.01
## 2 gene2     up    23    0.02
## 3 gene3   down    50    0.07
## 4 gene4   down     2    0.05

rownames(df1) <- c("r1","r2","r3","r4")
colnames(df1)[2] <- "CHANGE" 
test1 <- data.frame(name = c("jimmy","nicker","Damon","Sophie"),
                    blood_type = c("A","B","O","AB"))
test1

##     name blood_type
## 1  jimmy          A
## 2 nicker          B
## 3  Damon          O
## 4 Sophie         AB

test2 <- data.frame(name = c("Damon","jimmy","nicker","tony"),
                    group = rep(c("group1","group2"),2),
                    vision = c(4.2,4.3,4.9,4.5))
test2

##     name  group vision
## 1  Damon group1    4.2
## 2  jimmy group2    4.3
## 3 nicker group1    4.9
## 4   tony group2    4.5

merge(test1,test2,by="name")

##     name blood_type  group vision
## 1  Damon          O group1    4.2
## 2  jimmy          A group2    4.3
## 3 nicker          B group1    4.9

m <- matrix(1:9,nrow=3)
m

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

m[2,]

## [1] 2 5 8

m[,2]

## [1] 4 5 6

m[2,3]

## [1] 8

m[c(1,3),1:2]

##      [,1] [,2]
## [1,]    1    4
## [2,]    3    6

colnames(m) <- c("a","b","c")
m

##      a b c
## [1,] 1 4 7
## [2,] 2 5 8
## [3,] 3 6 9

t(m)

##   [,1] [,2] [,3]
## a    1    2    3
## b    4    5    6
## c    7    8    9

as.data.frame(m)

##   a b c
## 1 1 4 7
## 2 2 5 8
## 3 3 6 9

m

##      a b c
## [1,] 1 4 7
## [2,] 2 5 8
## [3,] 3 6 9

pheatmap::pheatmap(m)
pheatmap::pheatmap(m,cluster_cols = F,cluster_rows = F)

l<-list(m1=matrix(1:9,nrow = 3),
        m2=matrix(2:9,nrow = 2))
l

## $m1
##      [,1] [,2] [,3]
## [1,]    1    4    7
## [2,]    2    5    8
## [3,]    3    6    9
## 
## $m2
##      [,1] [,2] [,3] [,4]
## [1,]    2    4    6    8
## [2,]    3    5    7    9

l[[2]]

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

l$m1

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

scores <- c(11,59,73,95,45)
names(scores) = c("jimmy","nicker","Damon","Sophie","tony")
scores

##  jimmy nicker  Damon Sophie   tony 
##     11     59     73     95     45

scores["jimmy"]

## jimmy 
##    11

scores[c("jimmy","nicker")]

##  jimmy nicker 
##     11     59

names(scores)[scores>60]

## [1] "Damon"  "Sophie"