MEDS 5325: Computational Genomics Practicum (2 Credits)---Spring 2016
A practical introduction to computational genomics focussing on methods for processing/analyzing
Next Generation Sequencing (NGS) data. Programming: Introduction to the Linux command line,
elements of Python and R programming. Genomics software tools for performing sequence read-alignments,
transcript-expression profiling, and robust procedures for gauging differential gene expression.
Methods for genome assembly, genome variation detection, motif-finding, and data-visualization.
Statistical topics include: probability distributions, central limit theorem, hypothesis testing,
linear models, and dimensionality reduction.
Cell & Genome Science Bldg, 400 Farmington Ave
Office: R1260 (Genetics & Genome Sciences Dept cube)
Office hrs: after class or by arrangement
860.970.2283 (txt only please, voice doesn't work)
email@example.com (please use
this rather than uchc address)
Time & Place
Cell & Genome Science Bldg, 400 Farmington Ave, Rm R1390 (conference
room adjacent to computer server room).
We will be focussing on how to process/analyze Next Generation Sequencing
(NGS) data, using real data sets (drawn from students' own projects
if possible), and learning what we need to learn as we go in order to get things done!
will be primarily devoted to discussion and working through
computational examples/case-studies, though at least part of the
will include lectures on practical probability and statistics.
We may also draw upon selected video-lectures
from Coursera/EdX, expecially for aspects relating to programming
There will be graded homework assignments and exams, and a final project.
- getting set up on our laptops (macs)
- text-editor (smultron/aquamacs)
- command line basics
- R programming
- Python programming
- file formats
- SAM, BAM
- Tuxedo tools
- bowtie, bowtie2, tophat
- cufflinks, cuffdiff
Some other topics that we could consider:
- R graphics
- gene clustering & heatmaps: Gene Cluster and TreeView
- HPC cluster accounts; maneuvering on a cluster
- how to make UCSC browser tracks
- genome assembly: Velvet, Oasis
- variant analysis: freeBayes, VCF, Variant Annotation Integrator
- structural variation: DELLY
- statistical topics
- Binomial, Normal, and Poisson distributions
- Law of Large Numbers & Central Limit Theorem
- p-values & multiple testing
- Bayes theorem, likelihood function (cufflinks revisited)
- linear models
- principle components analysis
- batch effects, SVAseq
- FPKM vs TPM
- kallisto & sleuth
- GO analysis: DAVID, FuncAssociate
- motif finding: MEME, HOMER
- CHiP-seq peak calling
- ...more topics TBD