Bioinformatics Workbook

[Bessie Murrillo]

The bioinformatics workbook has guides and tutorials focused on the genomics and bioinformatics communities, although researchers of all backgrounds can use the workbook for UNIX command line basics, HPC info, project management tips, and data visualization tutorials. For bioinformatics researchers there is also information on experimental design, genome assembly and annotation, RNA sequencing, variant discovery, and more.

A geospatial research workbook is currently in development and is planning to offer tutorials and guides similar to the bioinformatics workbook, except focused on geospatial research communities such as ecology, hydrology, and remote sensing sciences.

I have been asked to recommend introductory books and resources to R and Bioconductor. My problem is just, I never read a book to learn R or Bioconductor, so I have no experience with this and cannot recommend one. I am interested in mainly introductory books, possibly targeting various groups of readers (computer scientists, molecular biologists, (bio-)statisticians), any recommendation appreciated.

I co-wrote an O'Reilly Short Cut, "Data Mashups in R", that is designed to be a little more fun than some of the scientific stuff out there while still exploring data manipulation in R, using packages, XML, web services, rudimentary plotting, and even some statistics. It costs $5 if you are not a Safari subscriber.

I have R in a Nutshell on my desk and I use it at least weekly if not daily. Its well indexed with a lot of great examples and helps me save time by not searching online. The BioC chapter is decent, but quite short. I also bought Data mashups in R which I found to be a great purchase and a fun way to learn about GIS capabilities and the Yahoo API in addition to R.

I have to give a shout out for the "R Graph Gallery". When learning to make graphs/visualizations, this resource is indispensable. Sometimes when I'm trying to think of a way to visualize some data, I just browse through the gallery for inspiration. Then, if you find something you like, all the code to get you started is right there.

I just got a copy of Draghici's book and I found it to be FANTASTIC.I will possibly buy a copy soon and look for his upcoming title "An Introduction to Statistics and Data Analysis for Bioinformatics using R" to be released in Sep 15, 2012

A comment, not answering your question but which may help a lot people using R:If you are very annoyed that it is impossible to make a google search for R, use rseek.org. It is basicly R-specific google.

This is really cool and helpful in any way. Yes, I was annoyed searching for one character languages "C, R". Had the authors of the languages anticipated google, they might have used something like R++ ;)

Introductory Statistics with R by Peter Dalgaard is a wonderful, brief introduction to basic statistical practice using R. If you want to know how to perform survival analysis, specify linear models, build plots, etc. it is a very clear guide. It is not bioinformatics-specific, and does not mention Bioconductor.

In general I've found the quality of the Springer books to be very high. If you're affiliated with a large university (e.g. UCSF), you may be able to browse their texts for free from your desk through SpringerLink.

I upvoted David Quigley's recommendation of the Dalgaard book. I'd also recommend Modern Applied Statistics with S by Venables & Ripley. Despite the title, it's totally relevant to R. From the first page of the Introduction, "An Open Source system called R has emerged that provides an independent implentation of the S language. It is similar enough that almost all the examples in this book can be run under R." This book is pretty much the standard reference for R in book form.

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Guides through assembling critical information for genes, disorders, and key variants to ensure clinical validity. Includes considerations on identifying problem regions, correlating those with clinical requirements, and provides a decision matrix for ensuring coverage of all critical regions. Also contains an approach and resources for selecting adequate reference materials for analytical validation.

Translates test design requirements into an initial assay design, including defining the coverage over the target regions, capture and sequencing methodologies, as well as any supplementary assays, as needed.

Describes analytical performance metrics in addition to associated formulas, suggested reference materials, and calculators. Also included are example worksheets on validation study design and subsequent data analysis.

Provides an overview on the critical considerations for the computational infrastructure as well as selection and validation of informatics approaches for tertiary processing of samples (NOTE: the initial aspects of bioinformatics are covered in previous sections).

Contains considerations and requirements for interpretation and reporting of variants identified using germline NGS testing (including filtration approaches, tools and strategies for challenging scenarios, considerations for variant reclassification, reanalysis strategies for exome/genome testing, and a list of databases and software tools)

The Biostar Handbook introduces readers to bioinformatics, the scientific discipline at the intersection of biology, computer science, and statistical data analytics dedicated to the digital processing of genomic information.

The Biostar Handbook has been developed, improved and refined over more than a half decade in a research university setting while used in an accredited Ph.D. level training program. The contents of this book have provided the analytical foundation to thousands of students, many of whom have become full-time bioinformaticians and work at the most innovative companies in the world.

We recommend reading and accessing the book via the website! The web version will always contain the most recent additions and most up-to-date content. A few times a year we send out emails that describe the new additions.

The book now includes shell casts to demonstrate command line usage. The shell casts are not videos! These animations are textual, captured from a terminal exactly as typed, with sharp visibility, will zoom with your screenfont sizes, may be paused at any time, and may be selected for copy-paste from the screen! Here is an example:

Shell casts are only visible via the web. PDF and ebooks do not have these animations embedded in them. Animations are a new feature in 2020. Aswe re-work the book we will be adding shell casts into each chapter.

We have been teaching bioinformatics and programming courses to life scientists for many years now. We are also the developers and maintainers of Biostars: Bioinformatics Question and Answer website the leading resource for helping bioinformatics scientists with their data analysis questions.

These workshops are made for online and unplugged experiences you can do at home. Originally part of our after school program in Omaha middle and elementary schools, we've adapted the lessons so you can easily use them at home.

Programming with Scratch
Introduce your classroom to programming with this simple and free tool. This presentation will walk your classroom through a simple exercise that will help you understand computational thinking, practice your programming skills and set you up to learn more complicated programs.

Bioinformatics is a new and exciting field that combines information technology and biology. Learn how to extract DNA from a strawberry, how diseases spread and how to help public health in this presentation and workbook.

Werner: How a Transportation Company Uses Technology

You might know Werner, they're a transportation company that helps the globe move things from A to B. But did you know they also have a bunch of technology that helps them run their business? Learn from their technology teams about how they're able to put their passion for tech to work.

IS&T Alumni: Where a Degree in IT Can Take You

IS&T Alumni from around the world will be joining in to share with you the cool things they've done in technology! Our alumni go on to work for some of the world's biggest companies and start-ups alike. Ask these panelists what it's like graduating college, how they picked their current careers, if they'd do anything different in college, and what they like the most about working in tech!

Watch a recording of the panel here.

NIDAP is an innovative, cloud-based, collaborative data aggregation and analysis platform that hosts user-friendly bioinformatics workflows and component analysis and visualization tools developed by the NCI developer community based on open source tools and makes them immediately available to biologist end-users across NIH.

As with any other tool, NIDAP may (or may not be) the best tool for your data analysis needs. We encourage you to check it out, to see if it fits your requirements. If you regularly use the same scripts or have a team collaborating on the same project, creating/customizing a pipeline on NIDAP can help you streamline the process.

To create a new Code Workbook, once again use the now-familiar green + New button, but this time please choose Code Workbook option. You may have to scroll down a little to see it. Feel free to Import Dataset (if you already have it uploaded) or click Skip this step grey text below the button.

Logic shows the code (or GUI), Inputs lists other datasets linked to this block, Preview will display your dataset (usually as a table, or as a container with files), Visualization shows images generated during the run, and Logs contains text output, as well as errors and warnings.

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