Assignment for Friday's class:
Assignments for Monday's class:
- If you have not done so, read through file on frequently used formats here
- Read the general Wikipedia entry on substitution matrices and on PAM and Blosum matrices - which one would you use for closely related, which ones for divergent sequences (here)?
- Optional: Dayhoff recoding is an elegant approach to avoid compositional bias in phylogenetic reconstruction. The PAM250 matrix with highlighting of the groups that are collapsed in the recoding is here.
- Read through the powerpoint slides from using BLAST to teach E-value-tionary concepts.
- Optional: Dan Graur wrote an introduction to his new textbook "Intro to Molecular and Genome Evolution" (here) in which he argues that all of evolution boils down to changing allele frequencies. At least after a first reading this appears to embrace the modern synthesis, and does not consider symbiosis, holobionts and hologenomes (maybe one could argue that picking up a symbiont with new properties is equal to a mutation?). If you submit by next Wednesday a 1-2 page* (12pt font, line spacing 1.5, 1 inch margins) essay discussing/critiquing Dan Graur's introduction, it will be graded and may take the place of one of the takehome exams.
* Bibliography and figures to not count towards the page limit.
Assignments for Today
Types of Error in a Databank search
False positives: The number of false positives are estimated in the E-value. The P-value or significance value gives the probability that a positive identification is made in error (same as with drug tests).
Danger: avoid fishing expeditions. If you do 100 tests on random data, you expect one to be positive at the 1% significance level.
You could apply the Bonferroni correction:
The significance level for the individual test is calculated through dividing the overall desired significance level by the number of parallel tests. The null-hypothesis of the overall test that is to be be rejected is that None of the individual tests is significantly different from chance. (The opposite of none being "at least one")
False negatives: Homologous sequences in the databank that are not recognized as such. If there are only 12000 different protein families, on average a sequence should have (size of the databank)/12000 matches. In other words, the number of false negatives is probably very large.
Decay of significance. Can this be corrected?
[ Carry over from class 8:
Meaning of phylogeny.
Another example of databank errors: Even species names are often wrongly assigned (slides)
Discuss exponential functions. (see here)]
Powerpoint slides on blast
Goals class 9:
- Understand the meaning of phylogeny
- Understand that neutral evolution can lead to an irreversible increase in complexity.
- Distinguish false positives and false negatives, especially with respect to databank searches
- Understand the impact of E-value cutoff in blast
- Understand the impact of the low complexity filter in blast