R

RNA-seq analysis in R

Analysis of RNA-seq in R.

ANOVA

One-way ANOVA Sources One-way ANOVA variance = SS/df, where SS - sum of squares and df - degree of freedom \(SS = \displaystyle\sum_{i=1}^{n}{(x_i - \mu)^2}\), where \(\mu\) is the sample mean n is the sample size \(var(x) = \frac{1}{n}{\displaystyle\sum_{i=1}^{n}{(x_i - \mu)^2}}\) 3 groups of students with scores (1-100): a = c(82,93,61,74,69,70,53) b = c(71,62,85,94,78,66,71) c = c(64,73,87,91,56,78,87) SST = SSE + SSC = W + B, where

Determining the optimal number of clusters

Elbow method Average silhouette method Gap statistic method Using NbCLust Sources Elbow method The basic idea is to find minimal the total intra-cluster variation or total Within-cluster Sum ofSquares (WSS). Plot number of clusters ~ WSS show how WSS is reduced with increase of number of clusters. The optimal number of clusters is when adding another cluster doesn’t improve much better the total WSS. The optimal number of clusters can be defined as follow:

Differential expression analysis

Here you can find a beautiful example of differential expression analysis using standard R packages.

Exploratory analysis in R

Exploratory analysis in R.

Compare Models And Select The Best Using The Caret R Package

Compare Models And Select The Best Using The Caret R Package.

Gradient Boosting Machine

Gradient Boosting Machine

k-means

Here you can find how to work with k-means cluster analysis.

Learning Vector Quantization

Learning Vector Quantization using R

Naive Bayes

Naive Bayes