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Fundamental Skills in Bioinformatics · LearnSpace
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Fundamental Skills in Bioinformatics

Курс от King Abdullah University of Science and Technology
Начальный≈ 24.5 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

The course provides a broad and mainly practical overview of fundamental skills for bioinformatics (and, in general, data analysis). The aim is to support the simultaneous development of quantitative and programming skills for biological and biomedical students with little or no background in programming or quantitative analysis. Through the course, the student will develop the necessary practical skills to conduct basic data analysis. Most importantly, participants will learn long-term skills in programming (and data analysis) and the guidelines for improving their knowledge on it. The course will include Programming in R, programming in Python, Unix server, and reviewing basic concepts of statistics.

Навыки, которые вы освоите

R ProgrammingPython ProgrammingPandas (Python Package)BioinformaticsStatistical AnalysisData QualityExploratory Data AnalysisStatistical Hypothesis TestingData AnalysisR (Software)RmarkdownScientific VisualizationStatistical MethodsStatistical VisualizationUnix ShellLinux ServersUnixUnix CommandsStatistical ProgrammingProgramming Principles

Программа курса

4 модулей · 109 учебных материалов

01Module 1: Introduction to Programming (using R)23 материалов

Welcome to the course

Brief introduction to the courseВидео

Introduction to R and RStudio

Lecture: Programming and RВидеоLecture: Introduction to RStudioВидеоSetting up RЧтение

Учитесь у экспертов

Jesper Tegner

Преподаватель курса

Zafer Ali

Digital Learning Specialist

Vincenzo Lagani

Преподаватель курса

David Gomez-Cabrero

Associate Professor

Robert Lehman

Research Scientist

Fundamental Skills in Bioinformatics
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Обучение на Coursera

≈ 24.5 ч

4 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Испанский, Японский

Часть программы вашего университета
Introduction to R QuizЗадание
Coding Lecture: First contact with RStudioВидео

Data Types

IntroductionВидеоLecture: Data types in RВидеоLecture: Data structures in RВидеоData Types in R QuizЗаданиеCoding Lecture: Data types in R - atomic and vectors ВидеоCoding Lecture: Data types in R - lists and matricesВидеоCoding Lecture: Data types in R - data framesВидео

Control Flow in R

Lecture: Introduction to Control FlowВидеоLecture: LoopsВидеоControl Flow in R QuizЗаданиеCoding Lecture: If statementsВидеоCoding Lecture: loop statementsВидео

Loading and Writting

Lecture: Loading and WritingВидеоLoading and Writing in R QuizЗаданиеCoding Lecture: Loading and WritingВидео

RMarkDown

Basics + where to learn moreВидеоAvailable data sets to be used in the course.Чтение
02Module 2: Introduction to Programming II (using R)29 материалов

Introduction to Module 2

Introduction to Module 2Видео

Logical Vectors

Lecture: Logical values, logical vectors and operations with them.ВидеоCoding Lecture: Logical Vectors, part 1.ВидеоCoding Lecture: Logical Vectors, part 2.ВидеоHow do R programming assignments work?ЧтениеProgramming Assignment Basics QuizЗаданиеOperating with logical values and matricesПрограммирование

Quality control on data

Lecture: Data Quality Control.ВидеоCoding Lecture: Quality Control.ВидеоQuality control of the data Программирование

Exploratory Data Analysis & Data Visualization with R

Lecture: Exploratory Data Analysis.ВидеоCoding Lecture: EDA part 1.ВидеоCoding Lecture: EDA part 2.ВидеоExploratory Data Analysis and Visualization in RЗадание

Correlation analysis

Lecture: CorrelationВидеоCoding Lecture: correlation in RВидеоCorrelation analysisПрограммирование

Linear Models

Lecture: Linear ModelsВидеоCoding Lecture: example of a linear modelВидеоCoding Lecture: evaluation of a linear model in RВидеоLinear modelsПрограммирование

t-test and ANOVA

Lecture: t-test & ANOVAВидеоCoding Lecture: t-test.ВидеоCoding Lecture: ANOVAВидеоt-test and ANOVAПрограммирование

Data analysis hands-on

Introduction to the dataset: Data set 4.ВидеоGuided analysis.ВидеоFirst analysis of an expression dataset.Программирование

Packages in R: CRAN, Bioconductor and GitHub

Lecture: R packagesВидео
03Module 3: Programming in Python29 материалов

Overview

Introduction to the moduleВидеоLecture: Python and RВидео

Setting up Python

The Python ecosystemВидеоPython installation and environmentsВидеоJupyter LabВидео

Python primitive values and data structures

Lecture: Python native data structuresВидеоCoding Lecture: Fundamentals in data typesВидеоCoding Lecture: Lists and Tuples ВидеоCoding Lecture: Sets and DictionariesВидеоPython primitive values and data structuresЗаданиеPython data structuresПрограммирование

Python syntax: for, if statements and functions

Lecture: flow control and functions.ВидеоCoding Lecture: if conditions, for and while loops.ВидеоCoding Lecture: declare and using functions in PythonВидеоPython syntax: for, if statements and functionsЗаданиеPython control flowПрограммирование

Modules in Python

Lecture: overview of modules in PythonВидеоLecture: numpyВидеоCoding Lecture: numpyВидеоThe numpy packageЗаданиеThe NumPy packageПрограммированиеLecture: pandasВидеоCoding Lecture: pandas

Reference material

Free online Python resourcesЧтение
04Module 4: Bioinformatics case study - RNA-seq bulk and single-cell data analysis28 материалов

Overview of the Module

Overview of the weekВидеоLecture: Introduction to the case studyВидео

Case study: bulk RNA-seq in R

Lecture: RNA-seq technology and data normalisationВидеоRelevant material for Week 4ЧтениеCoding Lecture: Loading and normalizing RNA-seq dataВидеоLecture: Principal Component AnalysisВидеоCoding Lecture: PCA analysis in R for RNA-seq dataВидеоLecture: Finding differentially expressed genesВидеоCoding Lecture: Differential expression analysis in RВидеоAnalysis of bulk RNAseq CD4+ T-cell dataПрограммирование

Case study: single-cell RNA-seq in Python

Lecture: From RNA-seq to scRNA-seqВидеоLecture: Representing scRNA-seq experiments in PythonВидеоCoding Lecture: Loading a scRNA-seq experiment in PythonВидеоLecture: Representing scRNA-seq experiments in PythonЗаданиеThe anndata package: managing scRNA-seq data in PythonПрограммированиеLecture: Preprocessing scRNA-seq dataВидео

How to progress in bioinformatics

Lecture: bioAIВидео

Final video

Thanks (for all the fish)Видео
Видео
Coding lecture: pandas for data explorationВидео
The pandas packageЗадание
The pandas packageПрограммирование
Coding Lecture: VisualizationВидео
Visualization with the pandas packageЛабораторная
Coding Lecture: scRNA-seq preprocessingВидео
scRNA-seq preprocessingЗадание
scRNA-seq preprocessing with the scanpy packageПрограммирование
Lecture: UMAP and dimensionality reduction in single-cell studiesВидео
Lecture: Cell type identificationВидео
Coding Lecture: Clustering and cell type identification with PythonВидео
Clustering and cell type indentification with PythonЗадание
Cell type identificationПрограммирование
Reference resources for single-cell analysis in PythonЧтение
Coding Lecture: scRNA-seq analysis in RВидео