R is free and powerful programming language for statistical computing and data visualization.
1. R can be used to compute a large variety of classical statistic tests including:
- Student's t-test: comparing the means of two groups of samples
- Wilcoxon test: a non-parametric alternative of t-test
- Analysis of variance (ANOVA): comparing the means off more than two groups
- Chi-square test: comparing proportions/distributions
- Correlation analysis: is for evaluating the relationship between two or more variables
2. It's also possible to use R for performing classfication analysis such as:
- Principal component analysis
- clustering
3. Many types of graphs can be drawn using R, including: box plot, histogram, density curve, scatter plot, line plot, bar plot,...
Install R && R Studio
R grammar
Function and Package
R has five basic or "atomic" classes of objects: character, numeric(real number), integer, logical(TRUE/FALSE)
Operational Symbol
Variable
Basic Data Types in R: Vector, List, Matrix, Data frame, Factor
Control Structures
Common mistakes in using R:
- Case sensitive
- Forget the necessary quotes
- Forget to use parentheses when calling a function
- Mix the usage of various sign
- Need to discriminate the signs in English and Chinese, such as quote and comma
Statistic Functions: max(), min(), mean(), median(), sum(), sd(), summary()
# assignment operators:
a <- 6 ## recommend 推荐这种赋值方式
print(a)
b = 5
print(5)1. Variable2=c("learn","R")
c本身在这里应该是“combine”的首字母，用于合并一系列数字从而形成向量/数列。
2. M = matrix(c('a','a','b','c','b','a'),nrow = 2, ncol = 3, byrow = FALSE)
byrow logical. If FALSE (the default) the matrix is filled by columns, otherwise the matrix is filled by rows.
3. factor_apple <- factor(apple)
因子就是用于表示一组数据中的类别，可以记录这组数据中的类别名称及类别数目。
4. R语言命令行敲代码换行：shift+enter
5. NOLC1[-5] ## print NOLC1 except for the 5th element
6. NOLC1[-(1:5)] ## print NOLC1 except for the first 5 elements
7. union(x, y) ## return the union of x and y(elements either in x or in y)
intersect(x, y) ## return the intersect of x and y(elements both in x and in y)
setdiff(x, y) ## return the elements only belongs to x while not belongs to y
identical(x, y) ## test objects for strict equality
8.
ct <- data.frame(
treatment,
GAPDH,
NOLC1,
EFN2B
)
ctValues <- ct[,c("GAPDH","NOLC1","EFN2B")] ##select three colomns of ct
dim(ctValues) ## return the dimension of ct
ncol(ctValues) ## return the number of columns of ct
nrow(ctValues) ## return the number of rows of ct
t(ctValues) ## transpose ct
rowSums(ctValues) ## calculate the sum of each row
rowMeans(ctValues) ## calculate the mean of each row
colSums(ctValues) ## calculate the sum of each column
colMeans(ctValues) ## calculate the mean of each column9. 画图细节还可以再仔细琢磨一下，最好是自己分析的数据来画一组图。
