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Introduction to the Command Line for Genomics
Unrestricted Use
CC BY
Introduction to the Command Line for Genomics
Rating
0.0 stars

Data Carpentry lesson to learn to navigate your file system, create, copy, move, and remove files and directories, and automate repetitive tasks using scripts and wildcards with genomics data. Command line interface (OS shell) and graphic user interface (GUI) are different ways of interacting with a computer’s operating system. The shell is a program that presents a command line interface which allows you to control your computer using commands entered with a keyboard instead of controlling graphical user interfaces (GUIs) with a mouse/keyboard combination. There are quite a few reasons to start learning about the shell: For most bioinformatics tools, you have to use the shell. There is no graphical interface. If you want to work in metagenomics or genomics you’re going to need to use the shell. The shell gives you power. The command line gives you the power to do your work more efficiently and more quickly. When you need to do things tens to hundreds of times, knowing how to use the shell is transformative. To use remote computers or cloud computing, you need to use the shell.

Subject:
Applied Science
Computer Science
Genetics
Information Science
Life Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Amanda Charbonneau
Amy E. Hodge
Anita Schürch
Bastian Greshake Tzovaras
Bérénice Batut
Colin Davenport
Diya Das
Erin Alison Becker
François Michonneau
Giulio Valentino Dalla Riva
Jessica Elizabeth Mizzi
Karen Cranston
Kari L Jordan
Mattias de Hollander
Mike Lee
Niclas Jareborg
Omar Julio Sosa
Rayna Michelle Harris
Ross Cunning
Russell Neches
Sarah Stevens
Shannon EK Joslin
Sheldon John McKay
Siva Chudalayandi
Taylor Reiter
Tobi
Tracy Teal
Tristan De Buysscher
Date Added:
08/07/2020
MoreLess
Programming with R
Unrestricted Use
CC BY
Programming with R
Rating
0.0 stars

The best way to learn how to program is to do something useful, so this introduction to R is built around a common scientific task: data analysis. Our real goal isn’t to teach you R, but to teach you the basic concepts that all programming depends on. We use R in our lessons because: we have to use something for examples; it’s free, well-documented, and runs almost everywhere; it has a large (and growing) user base among scientists; and it has a large library of external packages available for performing diverse tasks. But the two most important things are to use whatever language your colleagues are using, so you can share your work with them easily, and to use that language well. We are studying inflammation in patients who have been given a new treatment for arthritis, and need to analyze the first dozen data sets of their daily inflammation. The data sets are stored in CSV format (comma-separated values): each row holds information for a single patient, and the columns represent successive days. The first few rows of our first file look like this: 0,0,1,3,1,2,4,7,8,3,3,3,10,5,7,4,7,7,12,18,6,13,11,11,7,7,4,6,8,8,4,4,5,7,3,4,2,3,0,0 0,1,2,1,2,1,3,2,2,6,10,11,5,9,4,4,7,16,8,6,18,4,12,5,12,7,11,5,11,3,3,5,4,4,5,5,1,1,0,1 0,1,1,3,3,2,6,2,5,9,5,7,4,5,4,15,5,11,9,10,19,14,12,17,7,12,11,7,4,2,10,5,4,2,2,3,2,2,1,1 0,0,2,0,4,2,2,1,6,7,10,7,9,13,8,8,15,10,10,7,17,4,4,7,6,15,6,4,9,11,3,5,6,3,3,4,2,3,2,1 0,1,1,3,3,1,3,5,2,4,4,7,6,5,3,10,8,10,6,17,9,14,9,7,13,9,12,6,7,7,9,6,3,2,2,4,2,0,1,1 We want to: load that data into memory, calculate the average inflammation per day across all patients, and plot the result. To do all that, we’ll have to learn a little bit about programming.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Diya Das
Katrin Leinweber
Rohit Goswami
Date Added:
03/20/2017
MoreLess