You are here: Home / Resources / Teaching Materials / Computational Biology using R / Description
Resource Image

Computational Biology using R

Author(s): Hong Qin

University of Tennessee Chattanooga

1677 total view(s), 515 download(s)

0 comment(s) (Post a comment)

Download

Adapt 0
Summary:
This is an introductory level course on computational biology.

Licensed under CC Attribution-NonCommercial-ShareAlike 4.0 International according to these terms

Version 1.0 - published on 30 Oct 2018 doi:10.25334/Q4Q14Q - cite this

Keywords

  1. simulation
  2. module
  3. R
  4. course
  5. project
  6. solutions

Alignments

  1. Resource Type
  2. Activity Length
Contents:
view all files

Description

Following is the detailed information about the course. Supporting files could be found in https://github.com/hongqin/RCompBio

Instructor: Hong Qin
https://tinyurl.com/UTC-compgenomics 
2016-present, U of Tennessee Chattanooga
2009-2016, Spelman College.

1. Convert excel file to csv, read into R and plot
2. Hierarchical Clustering by hclust in R on a distance matrix between four cities
3. Retrieve and analyze a gene expression data set from NCBI GEO in R
4. How to use R match() function to merge different data sets
5. Install R packages in Windows
6. How to change R working directory in Windows
7. how to use 'match' function in R
8. Partial regression demo in R
9. How to install bioconducor packages in R
10. How to use Youtube to live-record a Powerpoint presentation
11. combine two vectors and output to csv file in R
12. A quick introdution to basic R usage (in RStudio)
13. genome-wide-association test (Fisher's exact test) on yeast strains
14. Output results from R
15. key to bio320 hw on factorial calculation using function and loop in R
16. Loops, if usage in R, 2012 Sep 17, review for exam
17. Using a generic function to do permutation tests on interacting gene pairs
18. Multiple regression demo, using R, causal analysis
19. reliability simulation 2012March20
20. nucleotide content and random sequence, using table(), sample(), for loop, write.csv()
21. Rules of using match() to transfer values between dataframes in R
22. Tradeoff between initial mortality rate and Gompertz coefficient in aging.
23. dataframe in R
24. Compare interaction degrees in protein and genetic interaction networks.
25. SBIO386, permutation analysis of genetic interaction network
26. Redo Figure 1 in Fraser et al 2002 Science paper in R
27. Coefficient of variation and robustness
28. SBIO386, 2012 Oct 8, intro to cellular aging in yeast
29. Hints for assignment for analyzing genetic interaction data, 2012Oct1
30. Genome wide association study on lifespan in yeast
31. Molar solution exercise, review for exam, 2012 Sep17
32. SBIO386 exercise on DNA sequence, random sequence generation.
33. SBIO386, compare protein interaction degree and genetic interaction degree
34. bio386, 20150922Tue salary exampe
35. R bioconductor, heatmap
36. Exponential growth function exercise
37. Molar solution R function demo, SBIO386 20150929
38. Spelman BIO386, 2012 Sep 26, redo figure 1 in Fraser02 paper
39. Redo Fraser figure 3B, 2012 Oct 8. SBIO386 (unlisted)
40. SBIO386, 2012 Oct 3, part 2
41. Project on robustness and aging
42. 2015 August 20, day 1, SBIO386, overview of class
43. BIO386, 2012 Sep 17, revie for exam 1, part 1
44. Permutate pairs, powerpoint illustration, SBIO386, 2012 Oct 8
45. BIO386, 2012 Sep 17, revie for exam 1, part 2
46. BIO320 class project: Introduction.
47. BIO386, 2012 Oct 1, part 2
48. 20120313130650
49. sbio386, 20150924Thu, Github usage
50. 20120313132654
51. BIO386 2012 Sep 17, review for exam 1, part 3
52. BIO386, 2012 Oct 1, part 1
53. 20120320142929
54. 20120320131613 SBIO320, realibility simulation of lifespan
55. sbio386 20150827Thu
56. SBIO386, 2012 Oct 3, part 1

Cite this work

Researchers should cite this work as follows:

Close

Home

Search