230 likes | 315 Vues
Welcome! Week of February 16, 2009. Reminders : Save ALL graded docs & see p.11 Exam THIS Thurs Due NEXT week: Pre-lab quiz Section assignment #2 M&M Lab template Problem Set. Lab Topics Replica Plating Meiosis Problem Solving Meiosis Binomial Probability Chi-Square
E N D
Welcome!Week of February 16, 2009 • Reminders: • Save ALL graded docs & see p.11 • Exam THIS Thurs • Due NEXT week: • Pre-lab quiz • Section assignment #2 • M&M Lab template • Problem Set Lab Topics Replica Plating Meiosis Problem Solving Meiosis Binomial Probability Chi-Square Conditional Probability
Quiz & Revisit Last Week • Quiz • 2:10-2:13 • Revisit • Assignment 1, #2c
GDP Disorders Sign Up Sheets for: • Achondroplasia • Batten Disease • Polycystic Kidney Disease 1 • Hemophilia A • Check the 1B website for resources for your disorder • Use the OMIM # on the 1B website for your disease • Ernst Mayer Library (26 Oxford St—near MCZ) • VERY eager to teach you how to use PubMed, OMIM, etc • 5 citation minimum. Must be peer-reviewed journal articles! • See manual p.13-15, 20-22 for Pre-Draft 1 directions • Start EARLY!
Mutant Analysis, week 2 • What are we doing this week? • Why are we doing this? • Specifically, what is the experimental procedure for the lab? • Hypothesize: What results do you expect the plates to look like next week?
Remember… • Keep hair/sleeves out of flame • Sterile technique • Dishes closed, when not actively working • Bunsen burner—creates updraft • Use each toothpick ONE time • Do NOT flick lint off velvet • After you clean up, work on, review meiosis problems (#1-7) in last week’s packet
Meiosis • For the top diagram: • n=_____, 2n=_____ • What separates in anaphase I? • What separates in anaphase II? Mendel’s Laws & Meiosis • Segregation—2 alleles of a gene segregate into different meiotic products • Independent Assortment—unlinked genes are inherited (sorted) independently from each other Crossing Over occurs in M1, forming tetrads
Lily Anther Lab--Meiosis • Photos • Be selective • Only upload one photo of each stage of M1 or M2 • Label photos • ie “JoeS1”, “JoeM2Meta”, etc • Delete photos • From the desktop, iPhoto, and camera once uploaded • Preparing lily anthers • Prepare several (3+) at a time, to ensure you’ll find all stages of meiosis • Divide & conquer • Left side focus on M1 • Right side focus on M2 • Scopes • Do NOT use 100x--squish! • Once focused, do NOT use coarse adjustment • Snap pictures of all stages • Upload AND name each picture
Discussion • Questions about the exam? • Cheat Sheet Suggestions • Pattern of inheritance for diseases (PKU= autosomal recessive) • M & M figures from lecture / textbook • Formulas • You do NOT need Chi Square table (p.141)
Elements of Probability • Events: • A & A’ are complements • P{A} + P{A’} = 1 • 1- P{A’} = P{A} • Compound Event • Union: P {A OR B} • P{A+B} • Probability is bigger than the probability of just A or just B • Intersection: P{A & B} • P{AB} • Probability is smaller; both A and B are less likely to occur • P for snow = need both cold weather AND precipitation • #8-10 in packet
Binomial Distribution • The binomial formula gives us a shorthand way to find the probability of a group of mutually exclusive independent events (lots of coin tosses or lots of offspring). • Where A&B are mutually exclusive events (ex boys vs girls) • p = probability of A occurring in any one trial • 1-p = probability of event B occurring in any one trial • n = total # trials (eg, # offspring examined) • r = # of “event A”s we are interested in • n-r = # of “event B”s we are interested in • Key phrase= “exactly n of x and m of y” • #11-14 in packet
Chi-Square Tests (#18-24) • Goodness of fit test • Determines how well observed results “fit” or agree with expected results • Obs: 651 A_ : 207 aa vs Exp : 3 A_:1 aa • Homogeneity (Association) test • Determines how homogeneous (similar) two observed (experimental) results are • Observe: 651 A_ : 207 aa and 787 A_ : 277 aa
Using Goodness of Fit(p.139 in text) • State the null hyp (no difference between O and E) • Use rules of probability to predict the types and proportions of progeny expected if hypothesis is true (Aa x Aa) • Convert proportions and % to numbers • Use the formula
Interpreting the x2 Value • Closer the x2 value is to 0 = closer O matches E • Calculate df: # classes data -1 • Use graph (p.141) to determine P value • Assuming the null hyp is true, probability that a worse or equally bad fit (as large/larger X2 value) would be obtained by chance • If p>0.05, results are non-significant (small difference btn E & O), and we fail to reject the null hyp • If p<0.05, results are significant (big diff btn E & O) & we reject the null hyp
Test of Homogeneity • State null hyp: both sets of data come from the same distribution • Solve--I highly recommend the “plug and chug” method • df always 1; comparing 2 groups of data (df = 2-1) • Interpret p value • If p>0.05, results are non-significant (small difference btn E & O), and we fail to reject the null hyp • If p<0.05, results are significant (big diff btn E & O) & we reject the null hyp
Event A = Event B = There are 2 bowls Bowl #1 10 choc chip cookies 30 plain cookies Bowl #2 20 choc chip cookies 20 plain cookies You pick a bowl at random & then a cookie at random. The cookie is plain. How probable is it that you picked from bowl #1, given it is plain? Conditional Probability,Cookie Style
Conditional Probability What we’ve been calculating: • We already know how to predict genetic ratios about future generations, given present info. • Aa x Aa = • Conditional probability allows us: • To infer genetic information about the past, given present info.
Event A = You pick bowl #1 Event B = You picked a plain cookie. There are 2 bowls Bowl #1 10 choc chip cookies 30 plain cookies Bowl #2 20 choc chip cookies 20 plain cookies You pick a bowl at random & then a cookie at random. The cookie is plain. How probable is it that you picked it out of bowl #1, given it is plain? Conditional Probability,Cookie Style
Event A = You pick bowl #1 Event B = You picked a plain cookie. To compute P(A|B), we first need to know: P(A),the probability that you picked bowl #1 (regardless of any other information) P(B), the probability of getting a plain cookie (regardless of any other information) P(B|A), the probability of getting a plain cookie given you picked bowl #1. There are 2 bowls Bowl #1 10 choc chip cookies 30 plain cookies Bowl #2 20 choc chip cookies 20 plain cookies You pick a bowl at random & then a cookie at random. The cookie is plain. How probably is it that you picked it out of bowl #1, given it is plain? Conditional Probability,Cookie Style
Event A = You pick bowl #1 Event B = You picked a plain cookie. To compute P(A|B), we first need to know: P(A) = 1/2 (only 2 bowls) P(B) = 80 cookies, 50 plain =.625 P(B|A) = 40 cookies in bowl #1 and 30 of them are plain = 30/40 = .75 There are 2 bowls Bowl #1 10 choc chip cookies 30 plain cookies Bowl #2 20 choc chip cookies 20 plain cookies You pick a bowl at random & then a cookie at random. The cookie is plain. How probably is it that you picked it out of bowl #1, given it is plain? Conditional Probability,Cookie Style
Event A = You pick bowl #1 Event B = You picked a plain cookie. To compute P(A|B), we first need to know: P(A) = .5 (only 2 bowls) P(B) = 80 cookies, 50 plain = .625 P(B|A) = 40 cookies in bowl #1 and 30 of them are plain = 30/40 = 0.75 Plug & Chug! There are 2 bowls Bowl #1 10 choc chip cookies 30 plain cookies Bowl #2 20 choc chip cookies 20 plain cookies You pick a bowl at random & then a cookie at random. The cookie is plain. How probably is it that you picked it out of bowl #1, given it is plain? Conditional Probability,Cookie Style
Event A = You pick bowl #1 Event B = You picked a plain cookie. To compute P(A|B), we first need to know: P(A) = ½ = .5 (only 2 bowls) P(B) = 80 cookies, 50 plain = .625 P(B|A) = 40 cookies in bowl #1 and 30 of them are plain = 30/40 = 0.75 Plug & Chug! There are 2 bowls Bowl #1 10 choc chip cookies 30 plain cookies Bowl #2 20 choc chip cookies 20 plain cookies You pick a bowl at random & then a cookie at random. The cookie is plain. How probable is it that you picked it out of bowl #1, given it is plain? Conditional Probability,Cookie Style
#10, 11 in packet Problems to Try