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-2346/UKB-b-2346_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2346/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:29 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2346/UKB-b-2346_data.vcf.gz ...
Read summary statistics for 9841859 SNPs.
Dropped 14604 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, 1289145 SNPs remain.
After merging with regression SNP LD, 1289145 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0315 (0.0019)
Lambda GC: 1.2029
Mean Chi^2: 1.2313
Intercept: 1.019 (0.0075)
Ratio: 0.0822 (0.0325)
Analysis finished at Thu Oct 17 14:44:08 2019
Total time elapsed: 1.0m:39.26s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.1474,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 6,
    "n_p_sig": 108,
    "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": 184375,
    "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": 1289145,
    "ldsc_nsnp_merge_regression_ld": 1289145,
    "ldsc_observed_scale_h2_beta": 0.0315,
    "ldsc_observed_scale_h2_se": 0.0019,
    "ldsc_intercept_beta": 1.019,
    "ldsc_intercept_se": 0.0075,
    "ldsc_lambda_gc": 1.2029,
    "ldsc_mean_chisq": 1.2313,
    "ldsc_ratio": 0.0821
}

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 9827323 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 9841859 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 8.622768e+00 5.748251e+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 7.885739e+07 5.628221e+07 828.0000000 3.258854e+07 6.948442e+07 1.145885e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.140000e-05 9.765500e-03 -0.1935510 -3.064600e-03 1.460000e-05 3.092900e-03 1.392600e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.950300e-03 6.556600e-03 0.0019519 2.388600e-03 4.001100e-03 9.220500e-03 1.032290e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.784369e-01 2.945480e-01 0.0000000 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.784370e-01 2.945226e-01 0.0000000 2.180893e-01 4.711643e-01 7.336913e-01 1.000000e+00 ▇▇▇▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.036653e-01 2.568621e-01 0.0010180 1.323200e-02 7.816300e-02 3.167860e-01 9.989820e-01 ▇▂▁▁▁
numeric AF_reference 184375 0.9812662 NA NA NA NA NA NA NA 2.069574e-01 2.483164e-01 0.0000000 1.198080e-02 1.000400e-01 3.204870e-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 -0.0004892 0.0035938 0.8900000 0.8917302 0.623721 0.7821490 NA
1 54676 rs2462492 C T 0.0047003 0.0035598 0.1900002 0.1867083 0.400251 NA NA
1 86028 rs114608975 T C 0.0027414 0.0056870 0.6300007 0.6297715 0.103746 0.0277556 NA
1 91536 rs6702460 G T 0.0092512 0.0035066 0.0083000 0.0083350 0.456553 0.4207270 NA
1 234313 rs8179466 C T -0.0023316 0.0069107 0.7400005 0.7358278 0.074499 NA NA
1 534192 rs6680723 C T 0.0025276 0.0040053 0.5300002 0.5279964 0.240966 NA NA
1 546697 rs12025928 A G -0.0027436 0.0049864 0.5800000 0.5821739 0.913387 NA NA
1 693731 rs12238997 A G 0.0001223 0.0033509 0.9699999 0.9708823 0.116443 0.1417730 NA
1 705882 rs72631875 G A 0.0002987 0.0049044 0.9500000 0.9514381 0.067468 0.0315495 NA
1 706368 rs55727773 A G 0.0012854 0.0024820 0.5999997 0.6045417 0.515951 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0028559 0.0052213 0.5800000 0.5843973 0.041796 0.0473243 NA
22 51219766 rs182321900 C T 0.0143696 0.0243372 0.5500004 0.5548973 0.001932 NA NA
22 51220146 rs868950473 C T 0.0089927 0.0241290 0.7099994 0.7093775 0.001979 NA NA
22 51221190 rs369304721 G A 0.0012619 0.0052114 0.8100000 0.8086732 0.049538 NA NA
22 51221731 rs115055839 T C -0.0004154 0.0038998 0.9199999 0.9151664 0.072919 0.0625000 NA
22 51222100 rs114553188 G T -0.0009875 0.0045879 0.8300000 0.8295806 0.054280 0.0880591 NA
22 51223637 rs375798137 G A -0.0009910 0.0046103 0.8300000 0.8298087 0.053903 0.0788738 NA
22 51229805 rs9616985 T C -0.0004384 0.0039133 0.9100000 0.9108075 0.072772 0.0730831 NA
22 51232488 rs376461333 A G -0.0009795 0.0092033 0.9199999 0.9152393 0.020022 NA NA
22 51237063 rs3896457 T C 0.0003331 0.0023911 0.8900000 0.8892196 0.297645 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623721 ES:SE:LP:AF:ID  -0.000489172:0.00359381:0.05061:0.623721:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400251 ES:SE:LP:AF:ID  0.00470034:0.00355984:0.721246:0.400251:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103746 ES:SE:LP:AF:ID  0.0027414:0.00568698:0.200659:0.103746:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456553 ES:SE:LP:AF:ID  0.00925118:0.00350664:2.08092:0.456553:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074499 ES:SE:LP:AF:ID  -0.00233157:0.00691074:0.130768:0.074499:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240966 ES:SE:LP:AF:ID  0.00252764:0.00400534:0.275724:0.240966:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913387 ES:SE:LP:AF:ID  -0.00274355:0.00498635:0.236572:0.913387:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116443 ES:SE:LP:AF:ID  0.000122313:0.00335088:0.0132283:0.116443:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067468 ES:SE:LP:AF:ID  0.000298683:0.00490441:0.0222764:0.067468:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515951 ES:SE:LP:AF:ID  0.0012854:0.00248204:0.221849:0.515951:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032867 ES:SE:LP:AF:ID  0.00322113:0.00627657:0.21467:0.032867:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036501 ES:SE:LP:AF:ID  0.00303067:0.00569782:0.229148:0.036501:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036614 ES:SE:LP:AF:ID  0.00284168:0.00567671:0.207608:0.036614:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036304 ES:SE:LP:AF:ID  0.00228464:0.00571805:0.161151:0.036304:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.01639  ES:SE:LP:AF:ID  0.00696801:0.00879071:0.366532:0.01639:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036856 ES:SE:LP:AF:ID  0.00258635:0.00565406:0.187087:0.036856:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036961 ES:SE:LP:AF:ID  0.00193764:0.00563363:0.136677:0.036961:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101183 ES:SE:LP:AF:ID  0.00134168:0.00409764:0.130768:0.101183:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959155 ES:SE:LP:AF:ID  -0.00470084:0.00542918:0.408935:0.959155:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031512 ES:SE:LP:AF:ID  -0.00885028:0.0098411:0.431798:0.031512:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05328  ES:SE:LP:AF:ID  0.00591714:0.00782342:0.346787:0.05328:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03649  ES:SE:LP:AF:ID  0.00275242:0.00566891:0.200659:0.03649:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.0368   ES:SE:LP:AF:ID  0.00319518:0.00561791:0.244125:0.0368:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843166 ES:SE:LP:AF:ID  -0.00169107:0.0029042:0.251812:0.843166:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056084 ES:SE:LP:AF:ID  -0.00277366:0.00469293:0.259637:0.056084:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122427 ES:SE:LP:AF:ID  -0.000213412:0.00317871:0.0222764:0.122427:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025538 ES:SE:LP:AF:ID  -0.00102413:0.00785726:0.0457575:0.025538:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121671 ES:SE:LP:AF:ID  4.03496e-05:0.00317998:0.00436481:0.121671:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132342 ES:SE:LP:AF:ID  0.000209179:0.00313491:0.0222764:0.132342:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011086 ES:SE:LP:AF:ID  -0.0177538:0.0114282:0.920819:0.011086:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005714 ES:SE:LP:AF:ID  0.00700291:0.0146838:0.200659:0.005714:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002281 ES:SE:LP:AF:ID  0.0196273:0.024602:0.376751:0.002281:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001033 ES:SE:LP:AF:ID  -0.0211686:0.0403165:0.221849:0.001033:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036708 ES:SE:LP:AF:ID  0.00189537:0.00556125:0.136677:0.036708:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838881 ES:SE:LP:AF:ID  -0.000829465:0.00281306:0.113509:0.838881:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838502 ES:SE:LP:AF:ID  -0.00112751:0.00281008:0.161151:0.838502:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869604 ES:SE:LP:AF:ID  0.000146292:0.00301442:0.0177288:0.869604:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130037 ES:SE:LP:AF:ID  -0.000118349:0.00302081:0.0132283:0.130037:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037205 ES:SE:LP:AF:ID  0.00219212:0.00546757:0.161151:0.037205:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037444 ES:SE:LP:AF:ID  0.0018742:0.00543318:0.136677:0.037444:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868946 ES:SE:LP:AF:ID  -0.000168321:0.00300864:0.0177288:0.868946:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869041 ES:SE:LP:AF:ID  -0.000179943:0.00300981:0.0222764:0.869041:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037401 ES:SE:LP:AF:ID  0.00210365:0.005457:0.154902:0.037401:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868951 ES:SE:LP:AF:ID  -0.000215942:0.00300863:0.0268721:0.868951:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005151 ES:SE:LP:AF:ID  -0.0201319:0.0154245:0.721246:0.005151:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005119 ES:SE:LP:AF:ID  -0.0196578:0.0154607:0.69897:0.005119:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837983 ES:SE:LP:AF:ID  -0.00127619:0.00280284:0.187087:0.837983:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037418 ES:SE:LP:AF:ID  0.00216251:0.00546421:0.161151:0.037418:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838616 ES:SE:LP:AF:ID  -0.00115672:0.00281072:0.167491:0.838616:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013698 ES:SE:LP:AF:ID  -0.0138128:0.00984567:0.79588:0.013698:rs181660517