Turning Biologists into Bioinformaticists - A practical approach

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We are grateful to Microsoft Corporation and Microsoft Research for their generous support of our educational activities.

Contents 1 Introduction 2 Theory - Core Bioinformatics Concepts 2.1 Sequence alignment 2.2 The structure of genomics data 2.3 Homology, similarity and evolution 3 Molecules 3.1 DNA 3.2 RNA 3.3 Protein 3.4 Metabolites 4 Tools - A Basic Bioinformatics Toolkit 4.1 Getting more out of Microsoft Excel 4.2 Introduction to Unix 4.3 Bioinformatics Applications of Unix 4.4 Alignments and Mappers 4.5 Unix Utilities 4.6 Relational databases 4.7 Programming 4.8 Statistics with R 5 Tasks - Bioinformatics Methods 5.1 Analysis and visualization of genomic data 5.1.1 UCSC Genome Bioinformatics (Website) 5.2 Multiple Sequence Alignment 5.3 Phylogenetic analysis 5.4 Protein Domains and Motifs 5.5 Functional Annotation of Gene Lists 5.6 Microarray data processing with R/Bioconductor

Introduction

This page is under development.

The purpose of the material is to help the KI-BCC members teach KI researchers the skills they need to effectively use bioinformatics in their projects. We intend the instruction to be practical and modular so that people can quickly learn easily applicable methods. We also hope that the teaching materials will serve as effective and readily accessible reference material.

It is not our intent to create a link-dump that regurgitates internet search results.

The overall organization is difficult to perfect. However, getting it right at the start is not important because the underlying information is small modules that can be organized and re-packaged in any way that works.

The material has been organized with general headers followed by more specific sections and subsections. The general headers are basically Theory, Tools, Tasks.

The sections under the headers should highlight general topics and the sub-sections beneath them are the actual modules of instruction. It is perfectly acceptable for the same module of instruction to be placed in different parts of the structure.

There is a lot of room for improvement with this organization and suggestions or comments are welcome (send them to charliew@mit.edu).

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Theory - Core Bioinformatics Concepts

Sequence alignment

The structure of genomics data

Homology, similarity and evolution

Molecules

DNA

Large Genomes

Small Genomes

RNA

mRNA

miRNA

Protein

Metabolites

Tools - A Basic Bioinformatics Toolkit

Getting more out of Microsoft Excel

Worksheet Navigation Tips

Selection Summarization Tools

Warning: Gene Symbols Auto-formatted to Dates

Filtering

Autofiltering - Mac-Specific

Advanced Filtering

Formulas

Using Conditional Tests to Summarize Gene Expression Data

Pivot Table Reports

Conditional Formatting - from visual support to heatmaps

Miscellaneous

Introduction to Unix

Introduction to Unix

Connecting to rous

Connecting to rous.mit.edu from a PC using SecureCRT

Shell functionality on PCs - PuTTY/XMing and Cygwin

Connecting to rous.mit.edu from Mac OS X

Transferring data from rous.mit.edu to local computers

Instructions for changing your passwords on rous.mit.edu

The Terminal and the Shell

The Unix Tree: files and directories

Anatomy of a Unix Command

Basic Unix Commands

Manual Pages

Tab completion and History

Output Redirection and Piping

Access rights

Unix text editors

editing files with emacs

editing files with nano

editing files with vi

editing files with nedit

Shell scripts

Bioinformatics Applications of Unix

Unix commands applied to bioinformatics

Manipulate NGS files using UNIX commands

Manipulate alignment files using UNIX commands

Alignments and Mappers

Unix Utilities

Using grep

Using awk

Using sort and uniq

Using find

Running command-line applications under unix

SGE Instructions and Tips

Relational databases

Running Joins on Galaxy

Connecting to the rous MySQL server

Creating a MySQL table

Executing MySQL queries

Programming

Perl

Using a perl script to process genomics data

Perl_One-liners

Statistics with R

Conditional Selection in R

Tasks - Bioinformatics Methods

Analysis and visualization of genomic data

UCSC Genome Bioinformatics (Website)

Interacting with the UCSC Genome Browser

Obtaining DNA sequence from the UCSC Database

Obtaining genomic data from the UCSC database using table browser queries

Filtering table browser queries

Performing a blat search

Creating Custom Tracks

UCSC Intersection Queries

Viewing cross-species alignments

More Table Browser Queries

Galaxy (Website)

Introduction to Galaxy

QC of Illumina data

Mapping of Single End Illumina reads

Analysis of SNP interval data

Comparing genomic intervals using Galaxy

Ensembl (Website)

NCBI Entrez Gene (Website)

JGI (Website)

Editing and annotation gene structures with Argo (Website)

IGB (Website)

Multiple Sequence Alignment

Clustalw2

Phylogenetic analysis

Neighbor Joining method in Clustal

Neighbor Joining method in Phylip

Protein Domains and Motifs

Functional Annotation of Gene Lists

Gather (Website)

GO tree machine GOTM (Website)

David (Website)

Biobase BioKnowledge Library (BKL) (Website)

Microarray data processing with R/Bioconductor