Introduction to Biostatistics and Bioinformatics Fall 2015 (BMSC-GA
4451) - 2 Credits
Lecturers:
Stuart Brown (Stuart.Brown@nyumc.org)
David Fenyö (David@FenyoLab.org)
Huilin Li (Huilin.Li@nyumc.org)
Tutorial Instructors:
Pamela Wu (Pamela.Wu@nyumc.org)
Amanda Ernlund (Amanda.Ernlund@nyumc.org)
Course Overview
The goal for the Introduction to Biostatistics and Bioinformatics course is to
provide an introduction to statistics and informatics methods for the analysis of
data generated in biomedical research. Practical examples covering both smallscale lab experiments and high-throughput assays will be explored. The course
covers a wide range of topics in a short time so the focus will be on the basic
concepts, and in the practical programming exercises the students explore these
basic concept and common pitfalls. An introduction of basic Python and R
programming will be given throughout the course and many exercises will
involve programming.
Learning objectives
The student will be introduced to entry-level methods in the biostatistics and
bioinformatics.
Course Assessment
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Readings and participation (10%): Students are required to attend class,
to complete reading assignments and to participate in discussions and
engage in healthy exchange of ideas. Each student is required to lead at
least one reading from the assigned weekly readings. This discussion lead
will be graded.
Assignments (40%): Programming assignment will be given at the end of
each class, and the solutions to these assignments should be e-mailed to
Assignments@FenyoLab.org within a week.
Exam (40%): There will be one exam in this class and it will cover the
entire course material.
Missed Exams and Grade Appeals
Make-up examinations (for final only) will be given under special circumstances.
Documentation will be required to verify a student’s claim. If a make-up exam is
permitted, a different exam will be written for that student and may have a
different format than the regular examination.
The assignments must be turned in on time and no late assignments will be
accepted.
If there is a time that you believe that there is a mistake in grading of an
assignment/exam, you will have a chance to appeal your exam grade within a
week after you receive your grade. If you think this is the case, you must write a
note describing the error, attach it to the original exam, and give it to me within
a week of the return of your exam. I will review your argument and my initial
grading, and then return your exam with a decision to you in a timely manner.
General Policies
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Late/missed work: You must adhere to the due dates for all required
submissions. If you miss a deadline, then you will not get credit for that
assignment/post. Try to avoid last minute submissions.
Incompletes: No “Incompletes” will be assigned for this course unless we
are at the very end of the course and you have an emergency.
Responding to Messages: I will check e-mails daily during the week, and I
will respond to course related questions within 48 hours.
Announcements: I will make announcements throughout the semester by
e-mail. Make sure that your email address is updated; otherwise you may
miss important emails from me.
Safeguards: Always back up your work on a safe place (electronic file with
a backup is recommended) and make a hard copy. Do not wait for the last
minute to do your work. Allow time for deadlines.
Plagiarism: Plagiarism, the presentation of someone else's words or ideas
as your own, is a serious offense and will not be tolerated in this class.
The first time you plagiarize someone else's work, you will receive a zero
for that assignment. The second time you plagiarize, you will fail the
course with a notation of academic dishonesty on your official record.
Recommended Readings
Python for Biologists: A complete programming course for beginners by Martin
Jones
Think Stats by Allen B. Downey
Lectures
Lecture 1 Assessment (August 20, 2015 Smilow 1st Floor Seminar Room 1pm)
Lecture 2 Introduction to Biological Data (September 1, 2015 Skirball 3rd Floor
Seminar Room 2pm)
Lecturer: Brown
Lecture 3 Introduction to Python I (September 3, 2015 Skirball 4th Floor
Seminar Room 2pm)
Lecturer: Brown
Reading List
• Python for Biologists Chapter 1
• Python Basics for Bioinformatics by Stuart Brown
Lecture 4 Introduction to Python II (September 10, 2015 Skirball 4th Floor Seminar Room 2pm)
Lecturer: Brown
Reading List
• Python for Biologists Chapters 2 & 3
Lecture 5 Introduction to Python III (September 15, 2015 Skirball 3rd Floor Seminar Room 2pm)
Lecturer: Brown
Reading List
• Python for Biologists Chapters 4 & 5
Lecture 6 Introduction to Python IV (September 17, 2015 Skirball 4th Floor Seminar Room 2pm)
Lecturer: Fenyo
Reading List
• Python for Biologists Chapters 6 & 7
Lecture 7 Exploring Data & Descriptive Statistics (September 22, 2015 Skirball 3rd Floor Seminar Room
2pm)
Lecturer: Fenyo
Reading List
• Think Stats Chapters 1 & 2
• Data visualization: A view of every Points of View column
Additional Reading
• Let's Give Statistics the Attention it Deserves
• Statistics for Biologists
Lecture 8 Sequence Alignment Concepts (September 24, 2015 TRB 120 2pm)
Lecturer: Brown
Reading List
• Understanding Bioinformatics Chapters 4.1-4.5 and 5.1-5.4
• Smith Waterman
• FASTA
• Emboss dotmatcher
Lecture 9 Sequence Database Searching (September 29, 2015 Smilow 1st Floor Seminar Room 2pm)
Lecturer: Brown
Reading List
• BLAST Chapter 4
• Altshul-BLAST
• The BLAST Sequence Analysis Tool
Lecture 10 Probability & Distributions (October 1, 2015 Skirball 4th Floor Seminar Room 2pm)
Lecturer: Li
Reading List
• Think Stats Chapters 3, 4, 5 & 6
Lecture 11 Estimation (October 6, 2015 Skirball 3rd Floor Seminar Room 2pm)
Lecturer: Li
Reading List
• Think Stats Chapters 8
Lecture 12 Hypothesis Testing (October 8, 2015 Skirball 4th Floor Seminar Room 2pm)
Lecturer: Li
Reading List
• Think Stats Chapters 9
Lecture 13 Analysis of Variance (October 13, 2015 Smilow 1st Floor Seminar Room 2pm)
Lecturer: Li
Lecture 14 Non-parametric Methods (October 15, 2015 Skirball 3rd Floor Seminar Room 2pm)
Lecturer: Li
Lecture 15 Regression & Correlation (October 20, 2015 Skirball 3rd Floor Seminar Room 2pm)
Lecturer: Fenyo
Reading List
• Think Stats Chapters 7, 10 & 11
Lecture 16 Experimental Design & Analysis (October 22, 2015 Skirball 3rd Floor Seminar Room 2pm)
Lecturer: Fenyo
Reading List
• Designing comparative experiments
• Analysis of variance and blocking
• Replication
• Bias as a threat to the validity of cancer molecular-marker research by David F. Ransohoff, Nat Rev
Cancer 5 (2005) 142-149