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Thread: Striking Genetic Diversity Among Populations of West Africa Uncovers the Mystery of a

  1. #11
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    Sorry but I don't get if you're questioning or affirming the presence of uniparental lineages of North African origin amongst the Fulanis

  2. #12
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    Quote Originally Posted by Gentica277282 View Post
    I can't remember in the shum laka paper did they model modern west Africans as mostly shum laka?
    Not really, it's Shum Laka that received Basal West African admixture
    41586_2020_1929_Fig4_HTML.png 41586_2020_1929_Fig9_ESM.jpg

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     Gentica277282 (11-23-2022)

  4. #13
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    Quote Originally Posted by Ronalawe View Post
    Not really, it's Shum Laka that received Basal West African admixture
    41586_2020_1929_Fig4_HTML.png 41586_2020_1929_Fig9_ESM.jpg
    Thanks was just asking because it seems to be acceptable in qpadm for my west African part. Just another question do you have any clue about COG_MatangaiTuru_IA I couldn't find a paper on it
    With high coverage Guanche sample 011
    SUCCESS p=.985
    55 Guanche.SG_11
    32 Canaanite_MLBA
    13 COG_MatangaiTuru_IA

    SUCCESS p=.978
    50 Guanche.SG_11
    40 BedouinB.DG
    11 COG_MatangaiTuru_IA

    G25 results

    Target: Me
    Distance: 1.4691% / 0.01469064 | R5P
    52.8 Berber_MAR_TIZ
    21.2 Yemenite_Mahra
    17.8 Greek_Cyclades_Amorgos
    5.4 Yoruba
    2.8 Bulala





    R11109 MALE 1 CE 1749.5 400 CE ARCHAEOLOGY Isola_Sacra Y-DNA: J-Y15222 mtDNA: X2m'n

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     Ronalawe (11-24-2022)

  6. #14
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    Quote Originally Posted by Gentica277282 View Post
    Thanks was just asking because it seems to be acceptable in qpadm for my west African part. Just another question do you have any clue about COG_MatangaiTuru_IA I couldn't find a paper on it
    The COG_MatangaiTuru_IA samples are from this paper and depending on the sample in question could either be modeled as majority Tanzanian Pastoral Neolithic + minority Mbuti, or majority Mota-related and minority Tanzanian PN



    https://www.science.org/doi/10.1126/sciadv.aaz0183
    Attached Images Attached Images
    Last edited by Dehlisandwich; 11-24-2022 at 10:57 PM.

  7. The Following 4 Users Say Thank You to Dehlisandwich For This Useful Post:

     drobbah (11-24-2022),  Gentica277282 (11-24-2022),  Lenny Nero (11-24-2022),  Ronalawe (11-25-2022)

  8. #15
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    Quote Originally Posted by Dehlisandwich View Post
    The COG_MatangaiTuru_IA samples are from this paper and depending on the sample in question could either be modeled as majority Tanzanian Pastoral Neolithic + minority Mbuti, or majority Mota-related and majority Tanzanian PN


    https://www.science.org/doi/10.1126/sciadv.aaz01833
    Had no idea this sample existed.I hope it’s possible to get it on G25
    Code:
    Target: Drobbah_FTDNA_scaled
    Distance: 1.7004% / 0.01700450 | ADC: 0.25x RC
    93.2	Cushitic
    6.8	Yemeni_Amran
    
    
    Target: Drobbah_FTDNA_scaled
    Distance: 5.1818% / 0.05181792
    51.6	South_Sudanese
    40.0	Levant_Natufian_EpiP
    3.0	Ethiopia_4500BP
    3.0	MAR_Taforalt
    1.6	IRQ_Nemrik9_PPN
    0.8	Levant_PPNB

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     Dehlisandwich (11-24-2022),  Gentica277282 (11-24-2022)

  10. #16
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    Quote Originally Posted by drobbah View Post
    Had no idea this sample existed.I hope it’s possible to get it on G25
    It's dated to AD 1184 but its coverage is extremely low (4%).

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     Gentica277282 (11-24-2022)

  12. #17
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    Deleted
    With high coverage Guanche sample 011
    SUCCESS p=.985
    55 Guanche.SG_11
    32 Canaanite_MLBA
    13 COG_MatangaiTuru_IA

    SUCCESS p=.978
    50 Guanche.SG_11
    40 BedouinB.DG
    11 COG_MatangaiTuru_IA

    G25 results

    Target: Me
    Distance: 1.4691% / 0.01469064 | R5P
    52.8 Berber_MAR_TIZ
    21.2 Yemenite_Mahra
    17.8 Greek_Cyclades_Amorgos
    5.4 Yoruba
    2.8 Bulala





    R11109 MALE 1 CE 1749.5 400 CE ARCHAEOLOGY Isola_Sacra Y-DNA: J-Y15222 mtDNA: X2m'n

  13. #18
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    Austria_Wels:R10667
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    Algeria_Necropole_Orientale:R10770
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    Guanche:gun008
    Y-DNA (P)
    E-FT458078
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    African Union
    we would be able to finally fully model berbers in the iron age if its possible to get this samples g25
    Distance to: abceff
    0.01873718 23.40% Tunisian_Jew:TunisianJew1511 + 76.60% Moroccan:MCA16

    Target: abceff
    Distance: 3.0158% / 0.03015844
    28.2 Levant_PPNB
    26.4 Anatolia_Barcin_N
    18.6 MAR_Taforalt
    9.6 Yamnaya_RUS_Samara
    8.0 COG_NgongoMbata_220BP
    5.4 IRN_Wezmeh_N
    3.6 Dinka
    0.2 WHG

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     Gentica277282 (11-24-2022)

  15. #19
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    Quote Originally Posted by Abceff View Post
    we would be able to finally fully model berbers in the iron age if its possible to get this samples g25
    You already can in qpadm


    Quote Originally Posted by Gentica277282 View Post
    COG_MatangaiTuru_IA anyone have any information on this sample?

    it's not on g25 from what I can see, does anyone have access to the paper and genotype data thanks

    simple qpadm model i ran myself with

    Code:
     > qp$weights
    # A tibble: 3 × 5
      target     left                weight     se     z
      <chr>      <chr>                <dbl>  <dbl> <dbl>
    1 GenticaAnc Guanche.SG           0.599 0.0648  9.25
    2 GenticaAnc COG_MatangaiTuru_IA  0.120 0.0193  6.19
    3 GenticaAnc LBN_IA               0.282 0.0545  5.16
    > qp$popdrop
    # A tibble: 7 × 14
      pat      wt   dof  chisq         p f4rank Guanche.SG COG_MatangaiTuru_IA  LBN_IA feasible best  dofdiff chisqdiff p_nested
      <chr> <dbl> <dbl>  <dbl>     <dbl>  <dbl>      <dbl>               <dbl>   <dbl> <lgl>    <lgl>   <dbl>     <dbl>    <dbl>
    1 000       0     9   6.51 6.88e-  1      2      0.599              0.120   0.282  TRUE     NA         NA     NA          NA
    2 001       1    10  47.4  8.10e-  7      1      0.912              0.0877 NA      TRUE     TRUE        0     -3.35        1
    3 010       1    10  50.7  1.97e-  7      1      0.917             NA       0.0830 TRUE     TRUE        0    -49.5         1
    4 100       1    10 100.   4.98e- 17      1     NA                  0.280   0.720  TRUE     TRUE       NA     NA          NA
    5 011       2    11  99.5  2.22e- 16      0      1                 NA      NA      TRUE     NA         NA     NA          NA
    6 101       2    11 329.   7.19e- 64      0     NA                  1      NA      TRUE     NA         NA     NA          NA
    7 110       2    11 755.   9.12e-155      0     NA                 NA       1      TRUE     NA         NA     NA          NA
    > 
    > `|`=`%>%`
    > p=""
    > o=""
    > rm(t)
    > #t=qp$popdrop|dplyr::filter(f4rank!=0&feasible)|arrange(desc(p),chisq)
    > t=qp$popdrop|dplyr::filter(f4rank!=0&feasible)|arrange(desc(p),chisq)
    > 
    > p=t|select(7:last_col(5))|apply(1,\(x)na.omit(100*x)|sort(T)|sprintf("%.0f %s",.,names(.))|paste(collapse=" "))
    > o=sub("^0","",sprintf(ifelse(t$p<.001,"%.0g","%.3f"),t$p))|paste0((ifelse(t$p > 0.05,"SUCCESS ","FAILED  ")),"p=",.," ",p,collapse="\n")
    > paste0("Target: ",target,"\nLeft: ",paste(sort(left),collapse=", "),"\nRight: ",paste(right,collapse=", "),"\nFeasible Results:","\n",o)|writeLines
    Target: GenticaAnc
    Left: COG_MatangaiTuru_IA, Guanche.SG, LBN_IA
    Right: Mbuti.DG, TUR_C_Boncuklu_PPN, CHG, Natufian, IRN_N.SG, ITA_Mesolithic.SG, RUS_Karasuk, RUS_DevilsCave_N, KAZ_Botai, PER_RioUncallane_1800BP, Indian_GreatAndaman_100BP.SG, MAR_Taforalt_EpiP
    Feasible Results:
    SUCCESS p=.688 60 Guanche.SG 28 LBN_IA 12 COG_MatangaiTuru_IA
    FAILED  p=8e-07 91 Guanche.SG 9 COG_MatangaiTuru_IA
    FAILED  p=2e-07 92 Guanche.SG 8 LBN_IA
    FAILED  p=5e-17 72 LBN_IA 28 COG_MatangaiTuru_IA

    Results
    SUCCESS p=.688
    60 Guanche.SG
    28 LBN_IA
    12 COG_MatangaiTuru_IA

    With high coverage Guanche sample 011

    Code:
    > qp$weights
    # A tibble: 3 × 5
      target     left                weight     se     z
      <chr>      <chr>                <dbl>  <dbl> <dbl>
    1 GenticaAnc Guanche.SG_11        0.563 0.0627  8.98
    2 GenticaAnc COG_MatangaiTuru_IA  0.125 0.0188  6.64
    3 GenticaAnc LBN_IA               0.312 0.0537  5.81
    > qp$popdrop
    # A tibble: 7 × 14
      pat      wt   dof  chisq         p f4rank Guanche.SG_11 COG_MatangaiTuru_IA  LBN_IA feasible best  dofdiff chisqdiff p_nested
      <chr> <dbl> <dbl>  <dbl>     <dbl>  <dbl>         <dbl>               <dbl>   <dbl> <lgl>    <lgl>   <dbl>     <dbl>    <dbl>
    1 000       0     9   3.09 9.61e-  1      2         0.563              0.125   0.312  TRUE     NA         NA     NA          NA
    2 001       1    10  44.7  2.51e-  6      1         0.914              0.0859 NA      TRUE     TRUE        0     -4.20        1
    3 010       1    10  48.8  4.35e-  7      1         0.924             NA       0.0759 TRUE     TRUE        0    -42.2         1
    4 100       1    10  91.0  3.34e- 15      1        NA                  0.267   0.733  TRUE     TRUE       NA     NA          NA
    5 011       2    11  79.0  2.31e- 12      0         1                 NA      NA      TRUE     NA         NA     NA          NA
    6 101       2    11 341.   2.32e- 66      0        NA                  1      NA      TRUE     NA         NA     NA          NA
    7 110       2    11 654.   3.24e-133      0        NA                 NA       1      TRUE     NA         NA     NA          NA
    > 
    > `|`=`%>%`
    > p=""
    > o=""
    > rm(t)
    > #t=qp$popdrop|dplyr::filter(f4rank!=0&feasible)|arrange(desc(p),chisq)
    > t=qp$popdrop|dplyr::filter(f4rank!=0&feasible)|arrange(desc(p),chisq)
    > 
    > p=t|select(7:last_col(5))|apply(1,\(x)na.omit(100*x)|sort(T)|sprintf("%.0f %s",.,names(.))|paste(collapse=" "))
    > o=sub("^0","",sprintf(ifelse(t$p<.001,"%.0g","%.3f"),t$p))|paste0((ifelse(t$p > 0.05,"SUCCESS ","FAILED  ")),"p=",.," ",p,collapse="\n")
    > paste0("Target: ",target,"\nLeft: ",paste(sort(left),collapse=", "),"\nRight: ",paste(right,collapse=", "),"\nFeasible Results:","\n",o)|writeLines
    Target: GenticaAnc
    Left: COG_MatangaiTuru_IA, Guanche.SG_11, LBN_IA
    Right: Mbuti.DG, TUR_C_Boncuklu_PPN, CHG, Natufian, IRN_N.SG, ITA_Mesolithic.SG, RUS_Karasuk, RUS_DevilsCave_N, KAZ_Botai, PER_RioUncallane_1800BP, Indian_GreatAndaman_100BP.SG, MAR_Taforalt_EpiP
    Feasible Results:
    SUCCESS p=.961 56 Guanche.SG_11 31 LBN_IA 13 COG_MatangaiTuru_IA
    FAILED  p=3e-06 91 Guanche.SG_11 9 COG_MatangaiTuru_IA
    FAILED  p=4e-07 92 Guanche.SG_11 8 LBN_IA
    FAILED  p=3e-15 73 LBN_IA 27 COG_MatangaiTuru_IA
    SUCCESS p=.961
    56 Guanche.SG_11
    31 LBN_IA
    13 COG_MatangaiTuru_IA
    With high coverage Guanche sample 011
    SUCCESS p=.985
    55 Guanche.SG_11
    32 Canaanite_MLBA
    13 COG_MatangaiTuru_IA

    SUCCESS p=.978
    50 Guanche.SG_11
    40 BedouinB.DG
    11 COG_MatangaiTuru_IA

    G25 results

    Target: Me
    Distance: 1.4691% / 0.01469064 | R5P
    52.8 Berber_MAR_TIZ
    21.2 Yemenite_Mahra
    17.8 Greek_Cyclades_Amorgos
    5.4 Yoruba
    2.8 Bulala





    R11109 MALE 1 CE 1749.5 400 CE ARCHAEOLOGY Isola_Sacra Y-DNA: J-Y15222 mtDNA: X2m'n

  16. #20
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    Y-DNA (P)
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    mtDNA (M)
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    Y-DNA (M)
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    mtDNA (P)
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    Somaliland Yemen Ethiopia
    Quote Originally Posted by Abceff View Post
    we would be able to finally fully model berbers in the iron age if its possible to get this samples g25
    There are saying this sample has Cushitic pastoralist ancestry, don’t think that is relevant to Berbers
    Code:
    Target: Drobbah_FTDNA_scaled
    Distance: 1.7004% / 0.01700450 | ADC: 0.25x RC
    93.2	Cushitic
    6.8	Yemeni_Amran
    
    
    Target: Drobbah_FTDNA_scaled
    Distance: 5.1818% / 0.05181792
    51.6	South_Sudanese
    40.0	Levant_Natufian_EpiP
    3.0	Ethiopia_4500BP
    3.0	MAR_Taforalt
    1.6	IRQ_Nemrik9_PPN
    0.8	Levant_PPNB

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