Difference between revisions of "BCB410"

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In this year's course you will define a useful tool for the analysis of biological data, write an R package to support it, review and critique other packages, and improve and document your work. 
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=== Phases ===
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We will work in five phases:
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* You will define a tool for data analysis and pitch it to the class for feedback in a one-minute presentation;
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* You will develop an R package for the analysis;
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* The class will work through your package and we will review your code;
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* You will respond to the review, improve the material and add code to support an interactive webpage for data exploration with your tool based on the '''''shiny''''' package;
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* You will finalize your package with a vignette with examples, and documentation.
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<table>
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<tr class="sh">
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<td><b>Week</b></td>
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<td><b>Date</b></td>
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<td><b>Topic</b></td>
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</tr>
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<tr><td colspan="3" class="sp">&nbsp;</td></tr>
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<tr class="s1">
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<td>1</td>
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<td>September 12</td>
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<td>Introduction, organization</td>
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</tr>
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<tr class="s2">
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<td>2</td>
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<td>September 19</td>
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<td>Initial idea, one-minute pitch</td>
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</tr>
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<tr class="s1">
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<td>3</td>
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<td>September 26</td>
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<td>R packages</td>
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</tr>
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<tr class="s2">
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<td>4</td>
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<td>October 3</td>
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<td>Tests</td>
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</tr>
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<tr class="s1">
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<td>5</td>
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<td>October 8</td>
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<td>All packages to be completed by Monday, October 8.</td>
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</tr>
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<tr class="s2">
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<td>5</td>
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<td>October 10</td>
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<td>Code Review I</td>
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</tr>
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<tr class="s1">
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<td>6</td>
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<td>October 17</td>
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<td>Code Review II</td>
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</tr>
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<tr class="s2">
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<td>7</td>
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<td>October 24</td>
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<td>Code Review III</td>
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</tr>
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<tr class="s1">
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<td>8</td>
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<td>October 31</td>
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<td>Code Review IV</td>
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</tr>
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<tr class="s2">
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<td>-</td>
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<td>November 7</td>
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<td>No class meeting, Fall Reading Week</td>
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</tr>
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<tr class="s1">
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<td>9</td>
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<td>November 14</td>
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<td>R Shiny</td>
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</tr>
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<tr class="s2">
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<td>10</td>
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<td>November 21</td>
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<td>Best practice, reproducible research</td>
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</tr>
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<tr class="s1">
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<td>11</td>
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<td>November 28</td>
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<td>Vignettes, examples, documentation</td>
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</tr>
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<tr class="s2">
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<td>12</td>
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<td>December 5</td>
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<td>No class meeting, all material due.</td>
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</tr>
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</table>
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=== Details ===
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{{Smallvspace}}
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==== 1. Define your tool ====
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{{Smallvspace}}
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Requirements
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Ideas
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Pitch
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{{Vspace}}
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==== 2. Develop your package ====
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{{Smallvspace}}
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...
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{{Vspace}}
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==== 3. Code reviews ====
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{{Smallvspace}}
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...
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{{Vspace}}
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==== 4. Improvements and extensions ====
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{{Smallvspace}}
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...
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{{Vspace}}
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==== 5. Examples and documentation ====
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{{Smallvspace}}
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...
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Contents details will be updated closer to the beginning of the term.
 
  
 
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=== Phases ===
 
 
We will work in four phases:
 
 
* You will design a learning unit and draft its contents;
 
* The class will work through the unit;
 
* We will go through "Code reviews" of the material;
 
* You will respond to the review and improve the material.
 
 
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Revision as of 10:12, 12 September 2018

BCB410H1F - 2018



Objectives and Participants

The "Applied Bioinformatics" course is offered as a part of the BCB Program curriculum to ensure that our students know enough about application issues in the field to be able to put their knowledge into practice in a research lab setting. This is to support the Specialist Program goal: to prepare students for graduate studies in the discipline.

As a required course in the BCB curriculum, BCB410 assumes the prerequisites and goals of fourth-year students in the BCB Specialist Program. Other students may be permitted to enrol on a case by case basis, but they may need to catch up on prerequisites in computer science or life-science courses that BCB students have taken at this point. Generally speaking, this is an advanced course that presupposes familiarity with programming principles, algorithm analysis, and methods of modern systems biology, as well as introductory knowledge of linear algebra, graph theory, information theory, statistics, as well as molecular–, structural– and cellular biology. The varying topics will be discussed at a highly technical level that is likely only useful for students who plan to integrate much of this material into their actual practice.


 

In this year's course you will define a useful tool for the analysis of biological data, write an R package to support it, review and critique other packages, and improve and document your work.


 

Phases

We will work in five phases:

  • You will define a tool for data analysis and pitch it to the class for feedback in a one-minute presentation;
  • You will develop an R package for the analysis;
  • The class will work through your package and we will review your code;
  • You will respond to the review, improve the material and add code to support an interactive webpage for data exploration with your tool based on the shiny package;
  • You will finalize your package with a vignette with examples, and documentation.


 


Week Date Topic
 
1 September 12 Introduction, organization
2 September 19 Initial idea, one-minute pitch
3 September 26 R packages
4 October 3 Tests
5 October 8 All packages to be completed by Monday, October 8.
5 October 10 Code Review I
6 October 17 Code Review II
7 October 24 Code Review III
8 October 31 Code Review IV
- November 7 No class meeting, Fall Reading Week
9 November 14 R Shiny
10 November 21 Best practice, reproducible research
11 November 28 Vignettes, examples, documentation
12 December 5 No class meeting, all material due.


 


Details

 


1. Define your tool

 

Requirements

Ideas

Pitch


 


2. Develop your package

 

...


 


3. Code reviews

 

...


 

4. Improvements and extensions

 

...


 

5. Examples and documentation

 

...


 




Organization

Due to unforeseen technical issues, these pages are unlikely to be updated for the 2018 Fall Term before our first class.

It is imperative that you attend the first class. Do not enrol in this course if you cannot be present in person on Wednesday, September 12 at 10:00 in SS1080 for the first class session.


 


Further details to be announced here.


Coordinator

Boris Steipe


 



Office hours

(Virtual) face to face meetings are by appointment, if required. However, we will be able to resolve almost all issues by e-mail. You will find that discussions by e-mail are both more efficient and effective than meetings. Moreover e-mail discussions leave you with a document trail of what was discussed, can contain links to information sources, and we can share points of general interest more easily with the class.


 








Notes