Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std plot

beta_std_plot

beta_std_plot

Metadata

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}

LDSC

*********************************************************************
* LD Score Regression (LDSC)
* Version 1.0.1
* (C) 2014-2019 Brendan Bulik-Sullivan and Hilary Finucane
* Broad Institute of MIT and Harvard / MIT Department of Mathematics
* GNU General Public License v3
*********************************************************************
Call: 
./ldsc.py \
--h2 /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15085/UKB-b-15085_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15085/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:59 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15085/UKB-b-15085_data.vcf.gz ...
Read summary statistics for 3891448 SNPs.
Dropped 701 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 932024 SNPs remain.
After merging with regression SNP LD, 932024 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.006 (0.0013)
Lambda GC: 1.0432
Mean Chi^2: 1.0526
Intercept: 0.9928 (0.0088)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:44:50 2019
Total time elapsed: 50.53s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8709,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -1.2104e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 31658,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 932024,
    "ldsc_nsnp_merge_regression_ld": 932024,
    "ldsc_observed_scale_h2_beta": 0.006,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 0.9928,
    "ldsc_intercept_se": 0.0088,
    "ldsc_lambda_gc": 1.0432,
    "ldsc_mean_chisq": 1.0526,
    "ldsc_ratio": -0.1369
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq FALSE
n_p_sig FALSE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio FALSE
ldsc_intercept_beta FALSE
n_clumped_hits FALSE
r2_sum1 FALSE
r2_sum2 FALSE
r2_sum3 FALSE
r2_sum4 FALSE

Definitions

General metrics

  • af_correlation: Correlation coefficient between AF and AF_reference.
  • inflation_factor (lambda): Genomic inflation factor.
  • mean_EFFECT: Mean of EFFECT size.
  • n: Maximum value of reported sample size across all SNPs, \(n\).
  • n_clumped_hits: Number of clumped hits.
  • n_snps: Number of SNPs
  • n_p_sig: Number of SNPs with pvalue below 5e-8.
  • n_mono: Number of monomorphic (MAF == 1 or MAF == 0) SNPs.
  • n_ns: Number of SNPs with nonsense values:
    • alleles other than A, C, G or T.
    • P-values < 0 or > 1.
    • negative or infinite standard errors (<= 0 or = Infinity).
    • infinite beta estimates or allele frequencies < 0 or > 1.
  • n_mac: Number of cases where MAC (\(2 \times N \times MAF\)) is less than 6.
  • is_snpid_unique: true if the combination of ID REF ALT is unique and therefore no duplication in snpid.
  • n_miss_<*>: Number of NA observations for <*> column.

se_n metrics

  • n_est: Estimated sample size value, \(\widehat{n}\).
  • ratio_se_n: \(\texttt{ratio_se_n} = \frac{\sqrt{\widehat{n}}}{\sqrt{n}}\). We expect ratio_se_n to be 1. When it is not 1, it implies that the trait did not have a variance of 1, the reported sample size is wrong, or that the SNP-level effective sample sizes differ markedly from the reported sample size.
  • mean_diff: \(\texttt{mean_diff} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta_j}{\texttt{n_snps}}\), mean difference between the standardised beta, predicted from P-values, and the observed beta. The difference should be very close to zero if trait has a variance of 1.
    • \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
    • \({z}_j = \frac{\beta_j}{{se}_j}\),
    • and \(\beta_j\) is the reported effect size.
  • ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean of diff and the mean of diff2 (expected difference between the standardised beta predicted from P-values, and the standardised beta derived from the observed beta divided by the predicted SD; NOT reported). The ratio should be close to 1. If different from 1, then implies that the betas are not in a standard deviation scale.
    • \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
    • \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
  • sd_y_est1: The standard deviation for the trait inferred from the reported sample size, median standard errors for the SNP-trait assocations and SNP variances.
    • \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
    • \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
    • and \({se}_j\) is the reported standard error.
  • sd_y_est2: The standard deviation for the trait inferred from the reported sample size, Z statistics for the SNP-trait effects (beta/se) and allele frequency.
    • \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
    • \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),

r2 metrics

Sum of variance explained, calculated from the clumped top hits sample.

  • r2_sum<*>: r2 statistics under various assumptions
    • 1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).
    • 2: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var2}}}\), \(\texttt{var2} = {\widehat{\texttt{sd1}}_{y}}^2\),
    • 3: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var3}}}\), \(\texttt{var3} = {\widehat{\texttt{sd2}}_{y}}^2\),
    • 4: \(r^2 = \sum_j{\frac{F_j}{F_j + n - 2}}\), \(F = \frac{\beta_j^2}{{se}_j^2}\).

LDSC metrics

Metrics from LD regression

  • ldsc_nsnp_merge_refpanel_ld: Number of remaining SNPs after merging with reference panel LD.
  • ldsc_nsnp_merge_regression_ld: Number of remaining SNPs after merging with regression SNP LD.
  • ldsc_observed_scale_h2_{beta,se} Coefficient value and SE for total observed scale h2.
  • ldsc_intercept_{beta,se}: Coefficient value and SE for intercept. Intercept is expected to be 1.
  • ldsc_lambda_gc: Lambda GC statistics.
  • ldsc_mean_chisq: Mean \(\chi^2\) statistics.
  • ldsc_ratio: \(\frac{\texttt{ldsc_intercept_beta} - 1}{\texttt{ldsc_mean_chisq} - 1}\), the proportion of the inflation in the mean \(\chi^2\) that the LD Score regression intercepts ascribes to causes other than polygenic heritability. The value of ratio should be close to zero, though in practice values of 0.1-0.2 are not uncommon, probably due to sample/reference LD Score mismatch or model misspecification (e.g., low LD variants have slightly higher \(h^2\) per SNP).

Flags

When a metric needs attention, the flag should return TRUE.

  • af_correlation: abs(af_correlation) < 0.7.
  • inflation_factor: inflation_factor > 1.2.
  • n: n (max reported sample size) < 10000.
  • is_snpid_non_unique: NOT is_snpid_unique.
  • mean_EFFECT_nonfinite: mean(EFFECT) is NA, NaN, or Inf.
  • mean_EFFECT_05: abs(mean(EFFECT)) > 0.5.
  • mean_EFFECT_01: abs(mean(EFFECT)) > 0.1.
  • mean_chisq: ldsc_mean_chisq > 1.3 or ldsc_mean_chisq < 0.7.
  • n_p_sig: n_p_sig > 1000.
  • miss_<*>: n_miss_<*> / n_snps > 0.01.
  • ldsc_ratio: ldsc_ratio > 0.5
  • ldsc_intercept_beta: ldsc_intercept_beta > 1.5
  • n_clumped_hits: n_clumped_hits > 1000
  • r2_sum<*>: r2_sum<*> > 0.5

Plots

  • Manhattan plot
    • Red line: \(-log_{10}^{5 \times 10^{-8}}\)
    • Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
  • QQ plot
  • AF plot
  • P-Z plot
  • beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)

Diagnostics

Details

Summary stats

skim_type skim_variable n_missing complete_rate character.min character.max character.empty character.n_unique character.whitespace logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 3890750 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 3891448 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.660834e+00 5.767610e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.856653e+07 5.675512e+07 828.0000000 3.161318e+07 6.890847e+07 1.147119e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.200000e-06 1.943000e-04 -0.0011184 -1.292000e-04 -2.100000e-06 1.269000e-04 1.156700e-03 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.878000e-04 2.430000e-05 0.0001562 1.667000e-04 1.799000e-04 2.046000e-04 5.713000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.922455e-01 2.909644e-01 0.0000001 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.922488e-01 2.909384e-01 0.0000001 2.387078e-01 4.900008e-01 7.441141e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.987102e-01 2.092728e-01 0.1249560 2.161940e-01 3.529020e-01 5.547015e-01 8.750440e-01 ▇▅▃▃▂
numeric AF_reference 31658 0.9918647 NA NA NA NA NA NA NA 3.871324e-01 2.144558e-01 0.0000000 2.108630e-01 3.488420e-01 5.423320e-01 1.000000e+00 ▅▇▅▃▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C -0.0000844 0.0002874 0.7700005 0.7691082 0.623777 0.782149 NA
1 54676 rs2462492 C T -0.0002040 0.0002848 0.4700002 0.4737032 0.400406 NA NA
1 91536 rs6702460 G T -0.0003020 0.0002804 0.2800000 0.2813710 0.456863 0.420727 NA
1 534192 rs6680723 C T 0.0005857 0.0003203 0.0669993 0.0674502 0.240945 NA NA
1 706368 rs55727773 A G 0.0001582 0.0001988 0.4299995 0.4261381 0.515671 0.275160 NA
1 729679 rs4951859 C G 0.0002177 0.0002326 0.3500000 0.3492043 0.843191 0.639976 NA
1 736289 rs79010578 T A -0.0003262 0.0002510 0.1900002 0.1937883 0.132341 0.139577 NA
1 752566 rs3094315 G A 0.0003154 0.0002253 0.1600000 0.1614524 0.838932 0.718251 NA
1 752721 rs3131972 A G 0.0003311 0.0002250 0.1400000 0.1411886 0.838559 0.653355 NA
1 753405 rs3115860 C A 0.0002773 0.0002414 0.2500000 0.2508067 0.869770 0.751797 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51197266 rs61290853 A G -0.0001692 0.0001751 0.3300000 0.3341226 0.386342 0.4229230 NA
22 51198027 rs34939255 A G 0.0005705 0.0001983 0.0040000 0.0040074 0.254585 0.0984425 NA
22 51210289 rs112565862 C T -0.0001538 0.0002640 0.5600000 0.5601528 0.129929 0.1018370 NA
22 51211106 rs9628250 T C 0.0004897 0.0001966 0.0129999 0.0127307 0.271583 0.1671330 NA
22 51211392 rs3888396 T C -0.0001726 0.0002616 0.5099998 0.5093533 0.132612 0.1641370 NA
22 51212875 rs2238837 A C -0.0000848 0.0001868 0.6499995 0.6499126 0.331442 0.3724040 NA
22 51213613 rs34726907 C T -0.0002438 0.0002461 0.3200000 0.3217676 0.127807 0.1727240 NA
22 51216564 rs9616970 T C -0.0002701 0.0002450 0.2700001 0.2702702 0.128318 0.1563500 NA
22 51219006 rs28729663 G A -0.0002667 0.0002398 0.2700001 0.2661606 0.137941 0.2052720 NA
22 51237063 rs3896457 T C -0.0001081 0.0001912 0.5700002 0.5717453 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623777 ES:SE:LP:AF:ID  -8.43621e-05:0.000287394:0.113509:0.623777:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400406 ES:SE:LP:AF:ID  -0.000204039:0.000284785:0.327902:0.400406:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456863 ES:SE:LP:AF:ID  -0.000302012:0.000280356:0.552842:0.456863:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240945 ES:SE:LP:AF:ID  0.000585651:0.000320262:1.17393:0.240945:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.515671 ES:SE:LP:AF:ID  0.00015823:0.000198827:0.366532:0.515671:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.843191 ES:SE:LP:AF:ID  0.000217741:0.000232596:0.455932:0.843191:rs4951859
1   736289  rs79010578  T   A   .   PASS    AF=0.132341 ES:SE:LP:AF:ID  -0.00032622:0.000251044:0.721246:0.132341:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838932 ES:SE:LP:AF:ID  0.0003154:0.000225253:0.79588:0.838932:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838559 ES:SE:LP:AF:ID  0.000331075:0.00022501:0.853872:0.838559:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86977  ES:SE:LP:AF:ID  0.000277277:0.000241448:0.60206:0.86977:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129883 ES:SE:LP:AF:ID  -0.000290617:0.000241937:0.638272:0.129883:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.86911  ES:SE:LP:AF:ID  0.00029095:0.000240973:0.638272:0.86911:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869208 ES:SE:LP:AF:ID  0.000286018:0.000241068:0.619789:0.869208:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869114 ES:SE:LP:AF:ID  0.000291313:0.000240968:0.638272:0.869114:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838012 ES:SE:LP:AF:ID  0.000330069:0.000224385:0.853872:0.838012:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838643 ES:SE:LP:AF:ID  0.000338585:0.000225016:0.886057:0.838643:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839758 ES:SE:LP:AF:ID  0.00034163:0.000228061:0.886057:0.839758:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869395 ES:SE:LP:AF:ID  0.000289903:0.000240692:0.638272:0.869395:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868945 ES:SE:LP:AF:ID  0.000280528:0.000240088:0.619789:0.868945:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867894 ES:SE:LP:AF:ID  0.0003079:0.000239625:0.69897:0.867894:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869087 ES:SE:LP:AF:ID  0.000289567:0.000240284:0.638272:0.869087:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869095 ES:SE:LP:AF:ID  0.000289298:0.000240302:0.638272:0.869095:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869103 ES:SE:LP:AF:ID  0.000289239:0.000240308:0.638272:0.869103:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869579 ES:SE:LP:AF:ID  0.000289875:0.000240966:0.638272:0.869579:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838292 ES:SE:LP:AF:ID  0.000309903:0.000223958:0.769551:0.838292:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838413 ES:SE:LP:AF:ID  0.000307035:0.000224117:0.769551:0.838413:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.86225  ES:SE:LP:AF:ID  0.000291351:0.000239436:0.657577:0.86225:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706751 ES:SE:LP:AF:ID  0.000118908:0.000233093:0.21467:0.706751:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761328 ES:SE:LP:AF:ID  0.000270542:0.00019026:0.79588:0.761328:rs2977608
1   769223  rs60320384  C   G   .   PASS    AF=0.129581 ES:SE:LP:AF:ID  -0.00027035:0.000241799:0.585027:0.129581:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868906 ES:SE:LP:AF:ID  0.000261191:0.000240509:0.552842:0.868906:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129682 ES:SE:LP:AF:ID  -0.000263886:0.000241642:0.568636:0.129682:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868916 ES:SE:LP:AF:ID  0.000256014:0.000240514:0.537602:0.868916:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265365 ES:SE:LP:AF:ID  0.000267736:0.000212506:0.677781:0.265365:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870036 ES:SE:LP:AF:ID  0.000236263:0.000241003:0.481486:0.870036:rs2980319
1   778745  rs1055606   A   G   .   PASS    AF=0.128582 ES:SE:LP:AF:ID  -0.00024536:0.000241952:0.508638:0.128582:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.12888  ES:SE:LP:AF:ID  -0.000232563:0.000241541:0.468521:0.12888:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868776 ES:SE:LP:AF:ID  0.000258128:0.000240359:0.552842:0.868776:rs2977612
1   782981  rs6594026   C   T   .   PASS    AF=0.129522 ES:SE:LP:AF:ID  -0.000255188:0.000241463:0.537602:0.129522:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.86853  ES:SE:LP:AF:ID  0.000265072:0.000240306:0.568636:0.86853:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.868471 ES:SE:LP:AF:ID  0.00026843:0.000240456:0.585027:0.868471:rs2980300
1   787399  rs2905055   G   T   .   PASS    AF=0.860775 ES:SE:LP:AF:ID  0.000310406:0.000240293:0.69897:0.860775:rs2905055
1   787606  rs3863622   G   T   .   PASS    AF=0.128468 ES:SE:LP:AF:ID  -0.000222273:0.000242769:0.443698:0.128468:rs3863622
1   787685  rs2905054   G   T   .   PASS    AF=0.861486 ES:SE:LP:AF:ID  0.000267552:0.000240448:0.568636:0.861486:rs2905054
1   787844  rs2905053   C   T   .   PASS    AF=0.869222 ES:SE:LP:AF:ID  0.000253889:0.000241337:0.537602:0.869222:rs2905053
1   791191  rs111818025 G   A   .   PASS    AF=0.12789  ES:SE:LP:AF:ID  -0.000228438:0.00024432:0.455932:0.12789:rs111818025
1   795988  rs59380221  C   T   .   PASS    AF=0.143047 ES:SE:LP:AF:ID  -6.72436e-05:0.000249229:0.102373:0.143047:rs59380221
1   798400  rs10900604  A   G   .   PASS    AF=0.206557 ES:SE:LP:AF:ID  -0.000211165:0.000202953:0.522879:0.206557:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.206387 ES:SE:LP:AF:ID  -0.000219727:0.000203039:0.552842:0.206387:rs11240777
1   808631  rs11240779  G   A   .   PASS    AF=0.772655 ES:SE:LP:AF:ID  0.000157914:0.000193148:0.387216:0.772655:rs11240779