All language subtitles for 77031x_PR_Conditional_Prob_02_Prob_K_Carrier_v1-en

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These are the user uploaded subtitles that are being translated: 0 00:00:00,000 --> 00:00:01,620 PETER REDDIEN: Now, we could ask what 1 00:00:01,620 --> 00:00:05,355 the probability of individual K being a carrier is. 2 00:00:05,355 --> 00:00:07,920 3 00:00:07,920 --> 00:00:10,590 So we could say, what is the probability 4 00:00:10,590 --> 00:00:13,740 that K is a carrier? 5 00:00:13,740 --> 00:00:18,520 6 00:00:18,520 --> 00:00:27,092 By carrier, I mean a big A allele and a little a allele. 7 00:00:27,092 --> 00:00:28,630 OK. 8 00:00:28,630 --> 00:00:31,420 And this is the type of thing people might care about. 9 00:00:31,420 --> 00:00:36,190 You have some trait showing some inheritance pattern in a family 10 00:00:36,190 --> 00:00:37,160 history. 11 00:00:37,160 --> 00:00:39,370 An individual might be unaffected 12 00:00:39,370 --> 00:00:42,610 but want to know, if say they're considering having children, 13 00:00:42,610 --> 00:00:44,500 might want to know if they're a carrier. 14 00:00:44,500 --> 00:00:46,840 What are the odds of them being a carrier? 15 00:00:46,840 --> 00:00:48,640 OK. 16 00:00:48,640 --> 00:00:50,350 So what do you think? 17 00:00:50,350 --> 00:00:53,510 What is the probability that individual K is a carrier? 18 00:00:53,510 --> 00:00:54,010 Yeah. 19 00:00:54,010 --> 00:00:54,790 STUDENT: One half? 20 00:00:54,790 --> 00:00:55,790 PETER REDDIEN: One half. 21 00:00:55,790 --> 00:01:00,070 22 00:01:00,070 --> 00:01:02,013 OK? 23 00:01:02,013 --> 00:01:04,180 And that's because this individual could have been-- 24 00:01:04,180 --> 00:01:08,980 25 00:01:08,980 --> 00:01:11,230 this individual, this female, will get an x big A 26 00:01:11,230 --> 00:01:15,640 from the father but could have gotten 27 00:01:15,640 --> 00:01:20,050 an x big A from the mother or an x little a from the mother. 28 00:01:20,050 --> 00:01:22,750 29 00:01:22,750 --> 00:01:26,720 50% chance of either scenario. 30 00:01:26,720 --> 00:01:27,220 OK. 31 00:01:27,220 --> 00:01:30,070 32 00:01:30,070 --> 00:01:34,710 Now, a couple of interesting things extra to note here. 33 00:01:34,710 --> 00:01:40,120 If you have affected fathers, none of the male offspring 34 00:01:40,120 --> 00:01:44,810 will have the trait or be carriers of the trait, 35 00:01:44,810 --> 00:01:47,972 but all of the female offspring will be carriers of the trait. 36 00:01:47,972 --> 00:01:49,430 It's sort of self-explanatory, when 37 00:01:49,430 --> 00:01:51,260 you think about the genetics, but interesting to think about, 38 00:01:51,260 --> 00:01:53,960 when you think about inheritance patterns in human populations. 39 00:01:53,960 --> 00:01:54,350 Yeah? 40 00:01:54,350 --> 00:01:55,155 STUDENT: Why do you have to add the probability for two 41 00:01:55,155 --> 00:01:56,280 separate outcomes together? 42 00:01:56,280 --> 00:02:03,710 43 00:02:03,710 --> 00:02:06,710 PETER REDDIEN: So I'm saying that you could have 44 00:02:06,710 --> 00:02:08,970 this outcome or this outcome. 45 00:02:08,970 --> 00:02:11,810 So you'd have a 0.5 chance of this outcome 46 00:02:11,810 --> 00:02:13,730 or a 0.5 chance of that outcome. 47 00:02:13,730 --> 00:02:15,980 So if you want to say what is the probability of being 48 00:02:15,980 --> 00:02:20,510 a carrier, that's this outcome which is 0.5. 49 00:02:20,510 --> 00:02:22,003 OK. 50 00:02:22,003 --> 00:02:22,670 Other questions? 51 00:02:22,670 --> 00:02:24,020 Yeah. 52 00:02:24,020 --> 00:02:26,560 So the question is, could you just sequence K and know? 53 00:02:26,560 --> 00:02:29,060 And yes, absolutely-- I'm going to show you some information 54 00:02:29,060 --> 00:02:30,393 about this in the next lecture-- 55 00:02:30,393 --> 00:02:32,618 if you know what the trait is. 56 00:02:32,618 --> 00:02:34,160 You might not know what the trait is, 57 00:02:34,160 --> 00:02:38,670 but you may know something about some things are linked to it. 58 00:02:38,670 --> 00:02:41,378 And so then you might be getting more complex probabilities, 59 00:02:41,378 --> 00:02:42,920 because you have to take into account 60 00:02:42,920 --> 00:02:45,378 probability of recombination, depending on the map distance 61 00:02:45,378 --> 00:02:46,490 or what you're assessing. 62 00:02:46,490 --> 00:02:48,282 So it depends on what information you have. 63 00:02:48,282 --> 00:02:51,040 So that some of that will be next lecture. 64 00:02:51,040 --> 00:02:53,815 The probability of a child being affected, we're going to-- 65 00:02:53,815 --> 00:02:55,990 you mean, if you look at these parents? 66 00:02:55,990 --> 00:02:56,620 STUDENT: Yeah. 67 00:02:56,620 --> 00:02:57,370 PETER REDDIEN: OK. 68 00:02:57,370 --> 00:02:59,290 So we could think about it with this example. 69 00:02:59,290 --> 00:03:04,630 Let's say there's some male offspring, 70 00:03:04,630 --> 00:03:08,710 and before you know whether the child will have the trait 71 00:03:08,710 --> 00:03:11,892 or not, let's say it develops at a certain age 72 00:03:11,892 --> 00:03:12,850 or something like that. 73 00:03:12,850 --> 00:03:15,820 You know there's a male offspring, 74 00:03:15,820 --> 00:03:18,010 but now you're waiting to find out if there's 75 00:03:18,010 --> 00:03:19,610 a trait there or not. 76 00:03:19,610 --> 00:03:20,110 OK. 77 00:03:20,110 --> 00:03:22,450 So then you can just say it's basically 78 00:03:22,450 --> 00:03:25,690 what we've been doing with like the paralyzed flies and stuff. 79 00:03:25,690 --> 00:03:28,292 If you knew that you had these genotypes of the parents, 80 00:03:28,292 --> 00:03:30,250 you could say, what's the probability of a male 81 00:03:30,250 --> 00:03:31,503 being affected? 82 00:03:31,503 --> 00:03:32,920 Well, you know every male is going 83 00:03:32,920 --> 00:03:35,500 to get the Y from the father and one of these two chromosomes 84 00:03:35,500 --> 00:03:39,650 from the mother, so it's just going to be 0.5. 85 00:03:39,650 --> 00:03:43,200 So you can just look forward with the probability like that. 6013

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