From Novice to Expert in Bioinformatics
Preface
I Linux
1 Why Linux?
- 1.1 What is Linux
- 1.2 Linux for bioinformatics
2 Connecting to Linux
- 2.1 User interfaces
- 2.2 How to connect
  - 2.2.1 Alternative ways to gain access to a Linux Server
3 Navigating in Linux file system
4 File content filtering
5 Achiving and compressing files
- 5.1 Common compressed file format
- 5.2 How to work with different format
6 Process management in Linux
7 File transfer
- 7.1 Transferring files between local computer and Linux server
  - 7.1.1 Use command line tools
  - 7.1.2 Download files
8 Install Bioinformatics software in Linux
- 8.1 Installation from source code
- 8.2 Installing a precompiled binary (executable)
9 Text editor in Linux
II Python
10 First Python Program
11 Varibles in Python
- 11.1 Variable names
- 11.2 Data types in Python
12 Functions in Python
- 12.1 Create a function to determine the GC-content of DNA sequence
- 12.2 Reverse complement
III Statistics and R
13 R introduction
14 ggplot2
- 14.1 ggplot2
- 14.2 ggplot2 practical
15 Heatmap Tutorial
16 Preparation of figures for manuscript
- 16.1 test1
IV Omics data
17 Introduction to NGS
18 Start a project
- 18.1 Experimetal design
19 Capstone project:
20 Useful measurements in Bioinformatics
21 data.table
- 21.1 Split data.table into chunks in a list
  - 21.1.1 nested list using flatten arguments
  - 21.1.2 Example
22 Good resouces to learn Bioinformatics
- 22.1 References:
23 Basic statistics - Descriptive Statistics
- 23.1 Probability distribution
24 Inferential Statistics
V Perl
25 First Perl Program
- 25.1 First Program
26 Varible in Perl
27 Linear regression
- 27.1 Interpreting regression parameters in a basic model
  - 27.1.1 R-squared and correlation
- 27.2 Reference
28 Control structure
29 String manipulation
30 Input and output in Perl
31 Practical Perl program
- 31.1 Add annotation information to DESeq2 results
- 31.2 Merge overlap genomic regions
32 Perl modules
33 Perl one-liner
34 Famouse people and/or blogs to follow
References
Published with bookdown

All things considered for Bioinformatics

Chapter 20 Useful measurements in Bioinformatics

20.1 K-mer

A “k-mer” is a piece of k bps long DNA sequence:

ACCG - 4-mer
ACCG - 6-mer

20.2 Shannon Entropy

20.3 Gini index