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-4549/UKB-b-4549_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4549/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:27 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4549/UKB-b-4549_data.vcf.gz ...
Read summary statistics for 9851866 SNPs.
Dropped 14738 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, 1289166 SNPs remain.
After merging with regression SNP LD, 1289166 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0572 (0.0023)
Lambda GC: 1.4085
Mean Chi^2: 1.502
Intercept: 1.0381 (0.0083)
Ratio: 0.0758 (0.0165)
Analysis finished at Thu Oct 17 14:46:10 2019
Total time elapsed: 1.0m:42.55s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.3107,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 25,
    "n_p_sig": 3640,
    "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": 184849,
    "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": 1289166,
    "ldsc_nsnp_merge_regression_ld": 1289166,
    "ldsc_observed_scale_h2_beta": 0.0572,
    "ldsc_observed_scale_h2_se": 0.0023,
    "ldsc_intercept_beta": 1.0381,
    "ldsc_intercept_se": 0.0083,
    "ldsc_lambda_gc": 1.4085,
    "ldsc_mean_chisq": 1.502,
    "ldsc_ratio": 0.0759
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
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 9837196 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 9851866 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 8.622825e+00 5.748290e+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 7.886027e+07 5.628334e+07 828.0000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -8.430000e-05 8.642900e-03 -0.1297170 -2.898100e-03 -3.260000e-05 2.801300e-03 1.269950e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.978600e-03 5.665800e-03 0.0016724 2.046800e-03 3.432400e-03 7.920200e-03 8.770860e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.591726e-01 2.998727e-01 0.0000000 1.900002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.591735e-01 2.998502e-01 0.0000000 1.891517e-01 4.444590e-01 7.189224e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035067e-01 2.568676e-01 0.0009450 1.316600e-02 7.789900e-02 3.164360e-01 9.990480e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.0000000 1.198080e-02 9.984030e-02 3.202880e-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 -0.0008131 0.0030758 0.7899998 0.7915190 0.623804 0.7821490 NA
1 54676 rs2462492 C T -0.0010689 0.0030466 0.7300002 0.7257141 0.400349 NA NA
1 86028 rs114608975 T C 0.0048426 0.0048744 0.3200000 0.3204820 0.103520 0.0277556 NA
1 91536 rs6702460 G T 0.0020662 0.0030020 0.4899999 0.4912794 0.456770 0.4207270 NA
1 234313 rs8179466 C T -0.0075197 0.0059133 0.2000000 0.2034909 0.074495 NA NA
1 534192 rs6680723 C T 0.0053904 0.0034286 0.1199999 0.1159085 0.240889 NA NA
1 546697 rs12025928 A G -0.0099628 0.0042751 0.0200000 0.0197832 0.913449 NA NA
1 693731 rs12238997 A G -0.0027274 0.0028741 0.3400001 0.3426469 0.116183 0.1417730 NA
1 705882 rs72631875 G A 0.0057584 0.0042068 0.1700000 0.1710452 0.067300 0.0315495 NA
1 706368 rs55727773 A G -0.0005119 0.0021286 0.8100000 0.8099490 0.515813 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0008013 0.0044761 0.8600001 0.8579306 0.041820 0.0473243 NA
22 51219766 rs182321900 C T -0.0042518 0.0209346 0.8400000 0.8390590 0.001922 NA NA
22 51220146 rs868950473 C T -0.0018209 0.0207110 0.9299999 0.9299407 0.001975 NA NA
22 51221190 rs369304721 G A 0.0027794 0.0044621 0.5300002 0.5333666 0.049636 NA NA
22 51221731 rs115055839 T C 0.0030589 0.0033383 0.3599996 0.3595089 0.073086 0.0625000 NA
22 51222100 rs114553188 G T 0.0023433 0.0039242 0.5500004 0.5504103 0.054515 0.0880591 NA
22 51223637 rs375798137 G A 0.0024125 0.0039429 0.5400003 0.5406350 0.054153 0.0788738 NA
22 51229805 rs9616985 T C 0.0028885 0.0033506 0.3900004 0.3886340 0.072920 0.0730831 NA
22 51232488 rs376461333 A G 0.0010289 0.0078754 0.9000000 0.8960553 0.020080 NA NA
22 51237063 rs3896457 T C 0.0000588 0.0020474 0.9800000 0.9771031 0.297844 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623804 ES:SE:LP:AF:ID  -0.000813058:0.00307582:0.102373:0.623804:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400349 ES:SE:LP:AF:ID  -0.00106886:0.00304664:0.136677:0.400349:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10352  ES:SE:LP:AF:ID  0.00484257:0.00487441:0.49485:0.10352:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.45677  ES:SE:LP:AF:ID  0.00206623:0.00300204:0.309804:0.45677:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074495 ES:SE:LP:AF:ID  -0.00751972:0.00591327:0.69897:0.074495:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240889 ES:SE:LP:AF:ID  0.00539035:0.00342858:0.920819:0.240889:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913449 ES:SE:LP:AF:ID  -0.00996284:0.0042751:1.69897:0.913449:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116183 ES:SE:LP:AF:ID  -0.00272742:0.00287415:0.468521:0.116183:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.0673   ES:SE:LP:AF:ID  0.00575845:0.00420677:0.769551:0.0673:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515813 ES:SE:LP:AF:ID  -0.000511918:0.00212863:0.091515:0.515813:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033023 ES:SE:LP:AF:ID  -0.0110486:0.00536151:1.40894:0.033023:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036638 ES:SE:LP:AF:ID  -0.00882443:0.00487053:1.1549:0.036638:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036749 ES:SE:LP:AF:ID  -0.00906042:0.00485257:1.20761:0.036749:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036459 ES:SE:LP:AF:ID  -0.00914225:0.00488665:1.21467:0.036459:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016421 ES:SE:LP:AF:ID  0.00316664:0.00752186:0.173925:0.016421:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036994 ES:SE:LP:AF:ID  -0.00869481:0.0048329:1.14267:0.036994:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037093 ES:SE:LP:AF:ID  -0.00809334:0.00481621:1.03152:0.037093:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101185 ES:SE:LP:AF:ID  -0.000222382:0.00351103:0.0222764:0.101185:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959085 ES:SE:LP:AF:ID  0.010123:0.00464592:1.5376:0.959085:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031492 ES:SE:LP:AF:ID  0.00262694:0.00842925:0.119186:0.031492:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053248 ES:SE:LP:AF:ID  0.00244112:0.00671119:0.142668:0.053248:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036609 ES:SE:LP:AF:ID  -0.00832594:0.0048477:1.0655:0.036609:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036925 ES:SE:LP:AF:ID  -0.00796263:0.0048033:1.01323:0.036925:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843302 ES:SE:LP:AF:ID  0.00429336:0.00248997:1.07058:0.843302:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.0558   ES:SE:LP:AF:ID  0.00220417:0.00403322:0.236572:0.0558:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122186 ES:SE:LP:AF:ID  -0.00214231:0.00272585:0.366532:0.122186:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025775 ES:SE:LP:AF:ID  -0.0032788:0.00668979:0.207608:0.025775:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121425 ES:SE:LP:AF:ID  -0.00228356:0.00272697:0.39794:0.121425:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132233 ES:SE:LP:AF:ID  -0.00460629:0.00268749:1.06048:0.132233:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01114  ES:SE:LP:AF:ID  0.000633793:0.00976709:0.0222764:0.01114:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005713 ES:SE:LP:AF:ID  -0.0138319:0.0125922:0.568636:0.005713:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002268 ES:SE:LP:AF:ID  -0.0373191:0.0212024:1.10791:0.002268:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001025 ES:SE:LP:AF:ID  0.0430086:0.0347617:0.657577:0.001025:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036823 ES:SE:LP:AF:ID  -0.00779661:0.00475584:1:0.036823:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839037 ES:SE:LP:AF:ID  0.00431296:0.00241143:1.13077:0.839037:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83867  ES:SE:LP:AF:ID  0.00442659:0.00240889:1.18046:0.83867:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869883 ES:SE:LP:AF:ID  0.00306747:0.00258469:0.619789:0.869883:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12977  ES:SE:LP:AF:ID  -0.00262707:0.00258994:0.508638:0.12977:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03734  ES:SE:LP:AF:ID  -0.00898344:0.0046746:1.25964:0.03734:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03758  ES:SE:LP:AF:ID  -0.00880718:0.0046453:1.23657:0.03758:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869224 ES:SE:LP:AF:ID  0.00319324:0.00257955:0.657577:0.869224:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86932  ES:SE:LP:AF:ID  0.00317312:0.00258052:0.657577:0.86932:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037535 ES:SE:LP:AF:ID  -0.00899336:0.00466573:1.26761:0.037535:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869228 ES:SE:LP:AF:ID  0.00320177:0.00257951:0.677781:0.869228:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005121 ES:SE:LP:AF:ID  -0.0254758:0.0132374:1.26761:0.005121:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005087 ES:SE:LP:AF:ID  -0.0247191:0.0132726:1.20066:0.005087:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838115 ES:SE:LP:AF:ID  0.0045216:0.00240212:1.22185:0.838115:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037552 ES:SE:LP:AF:ID  -0.00892903:0.00467203:1.25181:0.037552:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83874  ES:SE:LP:AF:ID  0.0044834:0.00240885:1.20066:0.83874:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013832 ES:SE:LP:AF:ID  0.00772297:0.00838608:0.443698:0.013832:rs181660517