Part 2 - Lecture 5/6 - Substitution Scoring Matrices

Question 1

What gives us an alignment and a score for similarity for an entire sequence?

Answer 1

global pairwise alignment

Question 2

What gives us the alignment and score for parts of sequences?

Answer 2

local pairwise alignment

Question 3

What can precisely indicate interesting residues of nucleotides and amino acids?

Answer 3

Multiple sequence alignment MSA

Question 4

What does MSA depend on?

Answer 4

accuracy in pairwise alignment - which depends on scoring

Question 5

What are the desirable features of a scoring matrix?

Answer 5

-we can think in terms of mutation and selection
-should we think about these differently - nucleotides and amino acids and what properties matter the most

Question 6

If you start with a high confidence alignment what do you get?

Answer 6

-have no gaps or spaces
-hopefully see very few mismatches
-can call these sequences related sequences

Question 7

How do you calculate the ways to choose k elements from a set of n elements?

Answer 7

nCk = (n!)/k!(n-k)!

Question 8

How do you move from substitution counts to probabilities?

Answer 8

take the number of pairs of nucleotides in column, and multiple by the number of columns and divide the counts by that calculated product

Question 9

Which exons are important?

Answer 9

the first and last exons

Question 10

What happens to the part of a gene after a stop codon?

Answer 10

it will be part of the mRNA post splicing but will not be expressed

Question 11

Why make a substitution scoring matrix?

Answer 11

had to do this because there was not way to make databases of genes to a single nucelotide of DNA position

Question 12

Why could you have a long untranslated part of a gene?

Answer 12

tRNA polymerase not starting at some position

Question 13

What happens more frequently and has less of an effect on function and is less penalized in a scoring matrix than translation?

Answer 13

transition

Question 14

In a real scoring matrix why are values scaled so that the highest entry is 100?

Answer 14

makes things easier to calculate

Question 15

How do amino acids affect protein structure?

Answer 15

hydrophobic residues go inside and hydrophilic outside which affects shape and not all parts of the protein are important; need to pay attention to H bonding, acidic, basic, polar, nonpolar; will amino acids be able to same role in chemical sense

Question 16

If you have two unreleated sequences if they are i.i.d than the pN is what which means the expected number of matches is what?

Answer 16

pN=0.25; 1/4 of the sequences is matches

Question 17

What is the null hypothesis for two sequences S1 and S2?

Answer 17

S1 and S2 have no more similarity than expected by chance

Question 18

What is the alternative hypothesis for two sequences S1 and S2?

Answer 18

S1 and S2 seem related more than similar than expected by chance

Question 19

What is testing hypotheses equivalent to?

Answer 19

comparing models; allows us to compare two models which describe relationships between two factors

Question 20

What is the probability for twp sequences by chance under Ho?

Answer 20

Question 21

What is the probability for twp sequences by chance under H1 or alternative hypothesis?

Answer 21

Question 22

What is the likelihood ratio and what does its value represent?

Answer 22

that the sequence is 5X more likely to have arisen from our related model than our unrelated model

Question 23

What does it mean if our starting data is symmetric?

Answer 23

-no species are ancestors of others
-substitutions are not all symmetric in their biological rates - dinucleotides are not in equilibrium

Question 24

How did we use our original scoring scheme?

Answer 24

-add scores corresponding to different alignment positions

Question 25

In the original scoring scheme what score were good and bad positions given?

Answer 25

good positions - positive score
bad positions - negative score

Question 26

What is mu or u in the original scoring scheme?

Answer 26

the relative weight of matches and mismatches

Question 27

How do you factor the likelihood ratio to emphasize individual positions?

Answer 27

Question 28

Is any information lost by taking the log of likelihood ratios?

Answer 28

No information is lost by taking the log of likelihood ratios

Question 29

Why is it better to add logs than multiply ratios of prababilities?

Answer 29

it is easier computationally for computer and humans

Question 30

What is the log likelihood scoring scheme?

Answer 30

just take the log of each term in the matrix

Question 31

What does a score of more than zero mean for the log value?

Answer 31

is a high confidence alignment

Question 32

Should match scores always be equal?

Answer 32

no they do not have to be

Question 33

Should there only be on scoring matrix?

Answer 33

no because it depends on if we have different species and the rates and types of changes vary between different species over generations due to evolution

Question 34

Can we make different scoring matrices for different situations?

Answer 34

yes you can begin with a high confidence alignment which corresponds to different time periods

Question 35

What can we use a scoring matrix to get?

Answer 35

pairwise alignment

Question 36

What can we use a pairwise alignment to get?

Answer 36

a MSA or multiple sequence alignment

Question 37

What do we use out MSA or multiple sequence alignment as the basis of?

Answer 37

a scoring matrix

Question 38

What is the function inference using sequence similarity?

Answer 38

(1)it works very well and (2) we can have a problem of drift in biases and (3) if it is recognized and persists it maybe inherent to genomics