Difference between revisions of "BCH394P BCH364C 2021"

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* [http://www.marcottelab.org/users/BCH394P_364C_2021/NBTPrimer-MicroarrayClustering.pdf Primer on clustering]
 
* [http://www.marcottelab.org/users/BCH394P_364C_2021/NBTPrimer-MicroarrayClustering.pdf Primer on clustering]
 
* [http://www.marcottelab.org/users/BCH394P_364C_2021/K-means-Example.ppt K-means example (.ppt)]
 
* [http://www.marcottelab.org/users/BCH394P_364C_2021/K-means-Example.ppt K-means example (.ppt)]
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* Here's [https://towardsdatascience.com/9-distance-measures-in-data-science-918109d069fa a nice explanation] of some of the various distance measures used for clustering
 
* [http://www.marcottelab.org/users/BCH394P_364C_2021/Bcelllymphoma.pdf B cell lymphomas]
 
* [http://www.marcottelab.org/users/BCH394P_364C_2021/Bcelllymphoma.pdf B cell lymphomas]
 
* [http://www.marcottelab.org/users/BCH394P_364C_2021/nature_review_2000.pdf Review of phylogenetic profiles]
 
* [http://www.marcottelab.org/users/BCH394P_364C_2021/nature_review_2000.pdf Review of phylogenetic profiles]
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* From last time, some definitions of [https://en.wikipedia.org/wiki/Sensitivity_and_specificity sensitivity/specificity] & [https://en.wikipedia.org/wiki/Precision_and_recall precision/recall]. Note that the gene finding community settled early on to a different definition of specificity that corresponds to the precision or PPV in other fields. Other fields define specificity as the true negative rate.
 
* From last time, some definitions of [https://en.wikipedia.org/wiki/Sensitivity_and_specificity sensitivity/specificity] & [https://en.wikipedia.org/wiki/Precision_and_recall precision/recall]. Note that the gene finding community settled early on to a different definition of specificity that corresponds to the precision or PPV in other fields. Other fields define specificity as the true negative rate.
  
 
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'''Feb 23, 2021 - Gene finding II'''
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'''Mar 4, 2021 - Gene finding II'''
 
* We're finishing up the slides from last time.
 
* We're finishing up the slides from last time.
  
  
'''Feb 18, 2021 - Gene finding'''
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'''Mar 2, 2021 - Gene finding'''
* Science news of the day: Kudos to the McLellan lab for solving the coronavirus spike protein 3D structure in 12 days (!), with a paper in the bioRxiv and now [https://science.sciencemag.org/content/early/2021/02/19/science.abb2507 Science] in record-breaking time
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* Science news of the day from one year ago: Kudos to the McLellan lab for solving the coronavirus spike protein 3D structure in 12 days (!), with a paper in [https://www.biorxiv.org/content/10.1101/2020.02.11.944462v1 bioRxiv] and [https://science.sciencemag.org/content/367/6483/1260.abstract Science] in record-breaking time, and cited nearly 4,000 times already in a single year (but what a year!)
* [https://research.utexas.edu/cbrs/classes/short-courses/spring-2021/ Short classes at UT] in genome sequencing, proteomics, and bioinformatics
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* [https://research.utexas.edu/cbrs/classes/short-courses/spring-2021/ Short classes at UT] start this week in genome sequencing, proteomics, and bioinformatics
 
* We'll finish HMM slides from last time, then start [http://www.marcottelab.org/users/BCH394P_364C_2021/BCH394P-364C-GeneFinding-Spring2021.pdf today's slides on gene finding]
 
* We'll finish HMM slides from last time, then start [http://www.marcottelab.org/users/BCH394P_364C_2021/BCH394P-364C-GeneFinding-Spring2021.pdf today's slides on gene finding]
* [https://amp.economist.com/graphic-detail/2018/07/26/python-is-becoming-the-worlds-most-popular-coding-language "In the past 12 months Americans have searched for Python on Google more often than for Kim Kardashian"]
 
 
* For a few more examples of HMMs in action, here's a [http://www.marcottelab.org/users/BCH394P_364C_2021/MinionHumanGenome.pdf paper on sequencing the human genome by nanopore], which used HMMs in 3-4 different ways for polishing, contig inspection, repeat analysis and 5-methylcytosine detection.
 
* For a few more examples of HMMs in action, here's a [http://www.marcottelab.org/users/BCH394P_364C_2021/MinionHumanGenome.pdf paper on sequencing the human genome by nanopore], which used HMMs in 3-4 different ways for polishing, contig inspection, repeat analysis and 5-methylcytosine detection.
 
* [http://genome.ucsc.edu/cgi-bin/hgTracks?db=hg38&lastVirtModeType=default&lastVirtModeExtraState=&virtModeType=default&virtMode=0&nonVirtPosition=&position=chr11%3A61755389-61788517&hgsid=477602291_ccTRfcOcZIQHnMkBKGzbQLBRc6HL The UCSC genome browser]
 
* [http://genome.ucsc.edu/cgi-bin/hgTracks?db=hg38&lastVirtModeType=default&lastVirtModeExtraState=&virtModeType=default&virtMode=0&nonVirtPosition=&position=chr11%3A61755389-61788517&hgsid=477602291_ccTRfcOcZIQHnMkBKGzbQLBRc6HL The UCSC genome browser]
'''Problem Set 2, due before midnight Mar. 4, 2021''':<br>
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* A few useful links about programming: [http://www.marcottelab.org/users/BCH394P_364C_2021/GoodEnoughPracticesInScientificComputing.pdf Recommendations for "good enough" programming habits] and [https://amp.economist.com/graphic-detail/2018/07/26/python-is-becoming-the-worlds-most-popular-coding-language "In the past 12 months Americans have searched for Python on Google more often than for Kim Kardashian"]
* [http://www.marcottelab.org/users/BCH394P_364C_2021/BCH394P-364C_ProblemSet2_Spring2021.pdf '''Problem Set 2''']
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* You'll need these 3 files: [http://www.marcottelab.org/users/BCH394P_364C_2021/state_sequences State sequences], [http://www.marcottelab.org/users/BCH394P_364C_2021/soluble_sequences Soluble sequences], [http://www.marcottelab.org/users/BCH394P_364C_2021/transmembrane_sequences Transmembrane sequences]
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Reading (a couple of old classics + a review):<br>
 
Reading (a couple of old classics + a review):<br>
 
* [http://www.marcottelab.org/users/BCH394P_364C_2021/EukGeneAnnotation.pdf Eukaryotic gene finding], [http://www.marcottelab.org/users/BCH394P_364C_2021/GeneMark.hmm.pdf GeneMark.hmm], and [http://www.marcottelab.org/users/BCH394P_364C_2021/BurgeKarlin-main.pdf GENSCAN]
 
* [http://www.marcottelab.org/users/BCH394P_364C_2021/EukGeneAnnotation.pdf Eukaryotic gene finding], [http://www.marcottelab.org/users/BCH394P_364C_2021/GeneMark.hmm.pdf GeneMark.hmm], and [http://www.marcottelab.org/users/BCH394P_364C_2021/BurgeKarlin-main.pdf GENSCAN]
  
  
'''Feb 16, 2021 - HMMs II'''
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'''Feb 25, 2021 - HMMs II'''
* We're finishing up the slides from last time.  
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* We're finishing up the slides from last time. I've also [http://www.marcottelab.org/users/BCH394P_364C_2021/BCH394P-364C_Spring2021_syllabus_updatedforstormdays.pdf updated the syllabus] to account for missing 3 lectures.  Mainly, we'll go all the way to the last scheduled class day (previously, we stopped 1 day early), but we were otherwise able to accommodate most of the missing material in a way that doesn't add any additional load on you all.
 +
'''Problem Set 2, due before midnight Mar. 9, 2021''':<br>
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* [http://www.marcottelab.org/users/BCH394P_364C_2021/BCH394P-364C_ProblemSet2_Spring2021.pdf '''Problem Set 2''']. 
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* You'll need these 3 files: [http://www.marcottelab.org/users/BCH394P_364C_2021/state_sequences State sequences], [http://www.marcottelab.org/users/BCH394P_364C_2021/soluble_sequences Soluble sequences], [http://www.marcottelab.org/users/BCH394P_364C_2021/transmembrane_sequences Transmembrane sequences]
 
* Link to [http://setosa.io/blog/2014/07/26/markov-chains/ a great interactive visualization of Markov Chains], by Victor Powell & Lewis Lehe. It's worth checking out to build some intuition.
 
* Link to [http://setosa.io/blog/2014/07/26/markov-chains/ a great interactive visualization of Markov Chains], by Victor Powell & Lewis Lehe. It's worth checking out to build some intuition.
 
* A non-biological example of using log odds ratios & Bayesian stats [https://priceonomics.com/how-statistics-solved-a-175-year-old-mystery-about/ to learn the authors of the Federalist Papers]
 
* A non-biological example of using log odds ratios & Bayesian stats [https://priceonomics.com/how-statistics-solved-a-175-year-old-mystery-about/ to learn the authors of the Federalist Papers]
  
-->
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'''Feb 16,18,23, 2021 - Snowpocalypse 2021!!!!'''
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* Hope everyone managed to stay safe/warm/fed during the storm and have now had a chance to recover. As many of you already discovered, the due date on Rosalind HW #2 was advanced.  I'll leave it open long enough for everyone to finish that homework.  We'll restart tomorrow (Feb 25) by reviewing HMMs and finishing up slides from Feb 11.
 +
 
 +
 
 
'''Feb 11, 2021 - Hidden Markov Models'''
 
'''Feb 11, 2021 - Hidden Markov Models'''
 
* Happy Class-Before-Valentine's Day!
 
* Happy Class-Before-Valentine's Day!

Revision as of 10:49, 4 March 2021

BCH394P/BCH364C Systems Biology & Bioinformatics

Course unique #: 55680/55580
Lectures: Tues/Thurs 11 – 12:30 PM on Zoom (log in to Canvas for the link)
Instructor: Edward Marcotte, marcotte @ utexas.edu

  • Office hours: Fri 11 AM – 12 noon on Zoom

TA: Vy Dang, vyqtdang @ utexas.edu

  • TA Office hours: Mon 3-4/Wed 1-2 on Zoom

Class Slack channel: bch394pbch364c2021.slack.com

Lectures & Handouts

Mar 4, 2021 - Gene finding II

  • We're finishing up the slides from last time.


Mar 2, 2021 - Gene finding

Reading (a couple of old classics + a review):


Feb 25, 2021 - HMMs II

  • We're finishing up the slides from last time. I've also updated the syllabus to account for missing 3 lectures. Mainly, we'll go all the way to the last scheduled class day (previously, we stopped 1 day early), but we were otherwise able to accommodate most of the missing material in a way that doesn't add any additional load on you all.

Problem Set 2, due before midnight Mar. 9, 2021:


Feb 16,18,23, 2021 - Snowpocalypse 2021!!!!

  • Hope everyone managed to stay safe/warm/fed during the storm and have now had a chance to recover. As many of you already discovered, the due date on Rosalind HW #2 was advanced. I'll leave it open long enough for everyone to finish that homework. We'll restart tomorrow (Feb 25) by reviewing HMMs and finishing up slides from Feb 11.


Feb 11, 2021 - Hidden Markov Models

  • Happy Class-Before-Valentine's Day!
  • Don't forget: Rosalind Homework #2 (worth 10% of your final course grade) is due by 11:59PM February 17.
  • More stats for comp biologists worth checking out: Modern Statistic for Modern Biology, by Susan Holmes and Wolfgang Huber. It's currently available online and available on dead tree. (FYI, all code is in R.)
  • Today's slides

Reading:


Feb 9, 2021 - Biological databases


Feb 4, 2021 - BLAST


Feb 2, 2021 - Sequence Alignment II


Jan 28, 2021 - Sequence Alignment I

Problem Set I, due before midnight Feb. 8, 2021:

  • Problem Set 1
  • H. influenzae genome. Haemophilus influenza was the first free living organism to have its genome sequenced. NOTE: there are some additional characters in this file from ambiguous sequence calls. For simplicity's sake, when calculating your nucleotide and dinucleotide frequencies, you can just ignore anything other than A, C, T, and G.
  • T. aquaticus genome. Thermus aquaticus helped spawn the genomic revolution as the source of heat-stable Taq polymerase for PCR.
  • 3 mystery genes (for Problem 5): MysteryGene1, MysteryGene2, MysteryGene3
  • *** HEADS UP FOR THE PROBLEM SET *** If you try to use the Python string.count function to count dinucleotides, Python counts non-overlapping instances, not overlapping instances. So, AAAA is counted as 2, not 3, dinucleotides. You want overlapping dinucleotides instead, so will have to try something else, such as the python string[counter:counter+2] command, as explained in the Rosalind homework assignment on strings.

Announcements:

  • The UT Center for Biomedical Research Support is offering short (1 day) online courses in bioinformatics and biocomputing
  • For those of you who could use more tips on programming, there's a weekly peer-led open coding hour happening every Wednesday on zoom. The zoom link will be posted to Slack & Canvas. It's a very informal setting where you can work and ask questions of more experienced programmers.

Extra reading, if you're curious:


Jan 26, 2021 - Intro to Python #2

  • Reminder that today will be part 2 of the "Python boot camp" for those of you with little to no previous Python coding experience. We'll be finishing the slides from last time, plus Rosalind help & programming Q/A.
  • Statistics in Python


Jan 21, 2021 - Intro to Python

  • REMINDER: My email inbox is always fairly backlogged (e.g., my median time between non-spam emails was 11 minutes when I measured it some time ago, and it's gotten much worse since then), so please copy the TA on any emails to me to make sure they get taken care of.
  • Today's slides
  • Python primer
  • E. coli genome
  • Python 2 vs 3?. We'll use Python 3 (the latest version is 3.8), but Rosalind and some materials are only available in Python 2.7, so we'll generally try to be version agnostic for compatibility. Use whichever you wish, but be aware that support for Python 2.7 has officially been stopped. For beginners, the differences are quite minimal and are summarized in a table here. There's also a great cheat sheet here for writing code compatible with both versions.


Jan 19, 2021 - Introduction

  • Today's slides
  • We'll be conducting homework using the online environment Rosalind. Go ahead and register on the site, and enroll specifically for BCH394P/364C (Spring 2021) Systems Biology/Bioinformatics using this link. Homework #1 (worth 10% of your final course grade) has already been assigned on Rosalind and is due by 11:59PM January 27.
  • Here's a very nice online Python resource, worth checking out!
  • Some warm-up videos to get you started on Python (2 not 3, unless you pay for an upgrade): Code Academy's Python coding for beginners
  • Khan Academy has archived their videos on Python here
  • A useful online resource if you get bogged down: Python for Biologists. (& just a heads-up that some of their instructions for running code relate to a command line environment that's a bit different from the default one you install following the Rosalind instructions. It won't affect the programs, just the way they are run or how you specific where files are located.) However, if you've never programmed Python before, this also worth checking out.

Syllabus & course outline

Course syllabus

An introduction to systems biology and bioinformatics, emphasizing quantitative analysis of high-throughput biological data, and covering typical data, data analysis, and computer algorithms. Topics will include introductory probability and statistics, basics of Python programming, protein and nucleic acid sequence analysis, genome sequencing and assembly, proteomics, synthetic biology, analysis of large-scale gene expression data, data clustering, biological pattern recognition, and gene and protein networks.

Open to graduate students and upper division undergrads (with permission) in natural sciences and engineering. Prerequisites: Basic familiarity with molecular biology, statistics & computing, but realistically, it is expected that students will have extremely varied backgrounds. Undergraduates have additional prerequisites, as listed in the catalog.

Note that this is not a course on practical sequence analysis or using web-based tools. Although we will use a number of these to help illustrate points, the focus of the course will be on learning the underlying algorithms and exploratory data analyses and their applications, esp. in high-throughput biology.

Most of the lectures will be from research articles and slides posted online, with some material from the...
Optional text (for sequence analysis): Biological sequence analysis, by R. Durbin, S. Eddy, A. Krogh, G. Mitchison (Cambridge University Press),

For biologists rusty on their stats, The Cartoon Guide to Statistics (Gonick/Smith) is very good. A reasonable online resource for beginners is Statistics Done Wrong.

Some online references:
An online bioinformatics course
Online probability texts: #1, #2

No exams will be given. Grades will be based on online homework (counting 30% of the grade), 3 problem sets (given every 2-3 weeks and counting 15% each towards the final grade) and an independent course project (25% of final grade). The course project will consist of a research project on a bioinformatics topic chosen by the student (with approval by the instructor) containing an element of independent computational biology research (e.g. calculation, programming, database analysis, etc.). This will be turned in as a link to a web page. The final project is due by midnight, April 26, 2021. The last 3 classes will be spent presenting your projects to each other. (The presentation will account for 5/25 points for the project.)

In this semester of coronavirus lockdown, the entire class will be web-based. We will hold lectures by Zoom during the normally scheduled class time. Log in to the UT Canvas class page for the link, or, if you are auditing, email the TA and we will send the link by return email. Slides will be posted before class so you can follow along with the material. We'll record the lectures & post the recordings afterward on Canvas so any of you who might be in other timezones or otherwise be unable to make class will have the opportunity to watch them. Note that the recordings will only be available on Canvas and are reserved only for students in this class for educational purposes and are protected under FERPA. The recordings should not be shared outside the class in any form. Violation of this restriction by a student could lead to Student Misconduct proceedings.

Online homework will be assigned and evaluated using the free bioinformatics web resource Rosalind.

All projects and homework will be turned in electronically and time-stamped. No makeup work will be given. Instead, all students have 5 days of free “late time” (for the entire semester, NOT per project, and counting weekends/holidays). For projects turned in late, days will be deducted from the 5 day total (or what remains of it) by the number of days late (in 1 day increments, rounding up, i.e. 10 minutes late = 1 day deducted). Once the full 5 days have been used up, assignments will be penalized 10 percent per day late (rounding up), i.e., a 50 point assignment turned in 1.5 days late would be penalized 20%, or 10 points.

Homework, problem sets, and the project total to a possible 100 points. There will be no curving of grades, nor will grades be rounded up. We’ll use the plus/minus grading system, so: A= 92 and above, A-=90 to 91.99, etc. Just for clarity's sake, here are the cutoffs for the grades: 92% = A, 90% = A- < 92%, 88% = B+ < 90%, 82% = B < 88%, 80% = B- < 82%, 78% = C+ < 80%, 72% = C < 78%, 70% = C- < 72%, 68% = D+ < 70%, 62% = D < 68%, 60% = D- < 62%, F < 60%.

Students are welcome to discuss ideas and problems with each other, but all programs, Rosalind homework, problem sets, and written solutions should be performed independently . Students are expected to follow the UT honor code. Cheating, plagiarism, copying, & reuse of prior homework, projects, or programs from CourseHero, Github, or any other sources are all strictly forbidden and constitute breaches of academic integrity (UT academic integrity policy and Sec. 11–402. Academic Dishonesty) and cause for dismissal with a failing grade. In particular, any materials found online (e.g. in CourseHero) that are associated with you, or any suspected unauthorized sharing of materials, will be reported to Student Conduct and Academic Integrity in the Office of the Dean of Students. These reports can result in sanctions, including failure in the course.

The final project web site is due by midnight April 26, 2021.