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Thread: Narasimhan values

  1. #21
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    Ethogenesis in several regions of south Asia is baffling., Some steppe alpha males went on sexual rampage and produced heap of children. In consequence, a skewed y-haplo and autosomal ancestry ratio is prevalent.
    Last edited by prashantvaidwan; 08-08-2019 at 03:01 PM.

  2. #22
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    Quote Originally Posted by DMXX View Post
    Reza's correct. I don't understand the basis of your objection (Sapporo).

    Higher socioeconomic classes are heavily over-represented in consumer genomics testing, and there are all sorts of implicit selection biases when it comes to recruiting participants for studies in the field (non-medical human studies seem to be worse in controlling for these variables).

    It looks like you've also misread Reza regarding the extent of AASI in Punjabi Jatts - His contention is that the current average should not be taken as representative with absolute certainty. Qualifying an outcome as being less secure isn't the same as arguing that reality is contrary to said outcomes. I'm also unsure if he was even discussing them.

    Using uniparentals to justify a particular autosomal trend is also a very weak argument. We're all aware of the Y-DNA to mtDNA to autosome asymmetry in the Subcontinent. Per that reasoning, we'd expect the Kyrgyz and certain northern Indian populations to be massively MLBA steppe-derived given the predominance of Y-DNA R1a1a among them. Isn't so. Founder effect.

    Regarding how "representative" the current roster of Punjabi Jatts are when it comes to AASI - A type 2 error calculation will tell you that.
    Going through Narasimhan's results there are some other results that don't make sense. Either our sampling is not diverse enough, or some folks are mixed/ or don't know their backgrounds well enough when giving academic samples. It is not just Punjabi Jatts. Just taking a quick look at the top the list pandits seem very high, baniyas who are AASI/ IVC mixed traders (often have more AASI than South Indian mid castes) are hanging above UP Brahmins and next to Jatt Sikh. Agarwal and Jain are hanging out near Gujarati D even though they are Baniyas. There are numerous others if I go through the list.

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  4. #23
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    Quote Originally Posted by DMXX View Post
    Reza's correct. I don't understand the basis of your objection (Sapporo).
    Reza didn't quote agent_lime or myself. His post could have easily been partially construed as potential criticism to my point toward Lollybolly about potential mislabeling/inaccurate sampling. He clarified that it was not.

    Higher socioeconomic classes are heavily over-represented in consumer genomics testing, and there are all sorts of implicit selection biases when it comes to recruiting participants for studies in the field (non-medical human studies seem to be worse in controlling for these variables).
    I do not disagree here. However, what would be the implication of an over-representation of higher socioeconomic Jatts to begin with? That they are somehow autosomally different than their lower socioeconomic counterparts? If so, in what way? An example of a potential implicit bias in the Narasimhan samples could be perhaps be "collecting all the samples from 1 city or hospital or having multiple sets of relatives?"

    It looks like you've also misread Reza regarding the extent of AASI in Punjabi Jatts - His contention is that the current average should not be taken as representative with absolute certainty. Qualifying an outcome as being less secure isn't the same as arguing that reality is contrary to said outcomes. I'm also unsure if he was even discussing them.
    Fair enough. I think the Global 25 data is fairly representative based on my large collection of mostly unrelated GEDMatch kits but it is fair to say I can't say that with absolute certainty. Anyways, it would have been easier if he just quoted agent_lime directly (as he suggests he wasn't discussing them and was responding to him instead).

    Using uniparentals to justify a particular autosomal trend is also a very weak argument. We're all aware of the Y-DNA to mtDNA to autosome asymmetry in the Subcontinent. Per that reasoning, we'd expect the Kyrgyz and certain northern Indian populations to be massively MLBA steppe-derived given the predominance of Y-DNA R1a1a among them. Isn't so. Founder effect.

    Regarding how "representative" the current roster of Punjabi Jatts are when it comes to AASI - A type 2 error calculation will tell you that.
    So is using diverse uniparental markers to suggest diverse autosomal trends fair game? As you stated, we're all aware of South Asia's founder effects but do diverse uniparental markers necessarily mean diverse autosomal DNA? My point was the autosomal DNA (publicly available via Global 25 + GEDMatch) isn't that diverse and neither are the "gathered" uniparental markers when looking at my 23andMe data + the 2017 Mahal study. I would never use uniparental markers to seriously suggest the levels of autosomal ancestry/admixture in a population.

    How would we go about incorporating the type 2 error calculation to incorporate my 100 GEDMatch kits on top of the 11-12 Punjabi Jatts on poi's Global 25 tool? I know there are statistical tools geneticists use when collecting representative sample size data (for populations numbering in the millions) for haplogroup studies. How could we apply that here? I ask that since I believe you are much more educated in formal statistics than myself.
    Last edited by Sapporo; 08-08-2019 at 04:22 PM.
    pegasus modeling:

    sample": "Punjabi_Jat:Sapporo_AGUser",
    "fit": 1.1506,
    "IRN_Shahr_I_Sokhta_BA3": 43.33,
    "TKM_Gonur1_BA": 31.67,
    "RUS_Sintashta_MLBA": 25,
    "closestDistances": [

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  6. #24
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    Quote Originally Posted by Reza View Post

    Anyhow, my point still stands as a general principle that in the West, the migrant populations are skewed towards middle class backgrounds. I didn't say wealthy or upper middle class. But generally speaking, migrants don't come from the bottom of society ie the scheduled castes, the labourers or tribal populations. And in my experience of Punjabis in the UK from both Pakistan and India, I think that holds. People migrate for a number of reasons. And economic opportunities are one of them.
    Well, I agree on that point. That the Western diaspora would be unrepresentative (due to sample availability) of data regarding lower social groups such as scheduled castes, the labourers or tribal populations

    Gedmatch samples are great in terms of numbers, but will be full of selection bias. Relatives of relatives as well as socioeconomic implications (you have to be well off enough to undertake a commercial dna test). They cannot be extrapolated to represent a population of millions unless you apply vigorous filters.
    Even if you were to suggest they have selection bias, in what way? Would upper and lower socioeconomic classes of the same sub-group score differently? What would you even define a relative of a relative as? How many generational gaps? The vast majority of my the kits I've collected don't seem to be recently related and the closest actual relative (other than my maternal 1st cousin who I tested) I have on there is a 4th cousin from Ancestry DNA (shown as 4.9 generations on GEDMatch). I usually don't see many South Asian kits that have matches (from the same sub-group) going below 5 unless there is an actual relation and even then, it's usually pretty distant.
    Last edited by Sapporo; 08-08-2019 at 04:25 PM.
    pegasus modeling:

    sample": "Punjabi_Jat:Sapporo_AGUser",
    "fit": 1.1506,
    "IRN_Shahr_I_Sokhta_BA3": 43.33,
    "TKM_Gonur1_BA": 31.67,
    "RUS_Sintashta_MLBA": 25,
    "closestDistances": [

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  8. #25
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    Quote Originally Posted by agent_lime View Post
    There are also communities that accept marriage outside, for example Tamil Brahmins were trying to import Brahmin brides from Uttar Pradesh. Many city dwelling folks have mixed caste marriages
    Damn is this true? UP kya ab se toh seedha kashmir se hi mangwaynge sgpt wali*


    Bolo hum bhi kya karein, jab steppe wale humari kanya le jayein**
    Quote Originally Posted by prashantvaidwan View Post
    Ethogenesis in several regions of south Asia is baffling., Some steppe alpha males went on sexual rampage and produced heap of children. In consequence, a skewed y-haplo and autosomal ancestry ratio is prevalent.
    https://m.economictimes.com/jat-groo...ow/2311302.cms


    * "Henceforth we shall be ordering brides from Kashmir, instead of UP"
    ** "Now what else are we supposed to do, when Steppe-folk take our women"

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  10. #26
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    Quote Originally Posted by client View Post
    Damn is this true? UP kya ab se toh seedha kashmir se hi mangwaynge sgpt wali*


    Bolo hum bhi kya karein, jab steppe wale humari kanya le jayein**


    https://m.economictimes.com/jat-groo...ow/2311302.cms


    * "Henceforth we shall be ordering brides from Kashmir, instead of UP"
    ** "Now what else are we supposed to do, when Steppe-folk take our women"
    Round and round we go in circles.

    https://english.mathrubhumi.com/news...lakh-1.3988771

    https://timesofindia.indiatimes.com/...w/64811836.cms

    https://timesofindia.indiatimes.com/...w/70562595.cms

    The Bengali thing is pretty common in other North Indian states as well. NE women marry outside in bigger cities too.

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  12. #27
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    Quote Originally Posted by Sapporo View Post
    I do not disagree here. However, what would be the implication of an over-representation of higher socioeconomic Jatts to begin with? That they are somehow autosomally different than their lower socioeconomic counterparts? If so, in what way? An example of a potential implicit bias in the Narasimhan samples could be perhaps be "collecting all the samples from 1 city or hospital or having multiple sets of relatives?"
    That isn't something anyone can answer with quantifiable data because we (obviously) don't have that data.


    So is using diverse uniparental markers to suggest diverse autosomal trends fair game? As you stated, we're all aware of South Asia's founder effects but do diverse uniparental markers necessarily mean diverse autosomal DNA?
    Potentially, actually. Depends on your level of granularity.

    How would we go about incorporating the type 2 error calculation to incorporate my 100 GEDMatch kits on top of the 11-12 Punjabi Jatts on poi's Global 25 tool? I know there are statistical tools geneticists use when collecting representative sample size data (for populations numbering in the millions) for haplogroup studies. How could we apply that here? I ask that since I believe you are much more educated in formal statistics than myself.
    You'd need to start with a testable hypothesis. In this case, we're querying whether the AASI levels seen in Jatts in GEDmatch etc. are likely to be representative of the actual population, or whether there's some sort of complex substructure that we're not accounting for, which would suggest substantial heterogeneity.

    For type 1 and 2 error calculations, you need a comparison group. A straightforward approach is to take Punjabi Jatts vs. Haryana Jatts (assuming their AASI-related levels are comparable). Alternatively, you could assess for substructure within the one group. Type 1 error calculations test for false positives, type 2 for false negatives. Both rely on the establishment of a null hypothesis (which is dependent on the approach you choose to take). From that, you can also calculate the power of your sample size (and can estimate whether it's sufficiently representative in ruling out the null hypothesis).

    Another useful calculation is variance, which describes the spread about the mean. You can also calculate that within-group as well.

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  14. #28
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    Quote Originally Posted by Lollybolly View Post
    The data is very strange. I'd highly doubt that Lohanas are the least "Onge" shifted amongst all other Indic groups. Plus, how are Lohanas scoring more steppe than Jatts and twice as low "Onge" than Jatts?
    AASI is not just in the onge category but also the made up “IVCp” or Indus-diaspora component which is 25-30% AASI and the rest Iran_N. This has already been said before but it’s a poor model, it contains no sink for excess ANF, WSHG, or East Asian ancestry. And they’re using Onge(not the true ancestral source). I only put these values here so people can refer back to them if they want to but they shouldn’t be taken at face value.

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  16. #29
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    My first conclusion is wow this sampling is laughably bad.

    And then, the model is even worse. Imagine being dumb enough to thin you can model a country of 1 billion people with 3 simple components, ignoring relevant pulls at the fringes of the subcontinent.

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    Quote Originally Posted by 26284729292 View Post
    My first conclusion is wow this sampling is laughably bad.

    And then, the model is even worse. Imagine being dumb enough to thin you can model a country of 1 billion people with 3 simple components, ignoring relevant pulls at the fringes of the subcontinent.
    It's still a step up from the two components we used to have in the past "ANI and ASI". AASI as an idea hasnt even caught on outside this site.

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