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-4982/UKB-b-4982_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4982/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:58 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4982/UKB-b-4982_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: 0.0409 (0.0019)
Lambda GC: 1.323
Mean Chi^2: 1.3868
Intercept: 1.0298 (0.0084)
Ratio: 0.0769 (0.0217)
Analysis finished at Thu Oct 17 14:46:44 2019
Total time elapsed: 1.0m:46.8s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.1999,
    "mean_EFFECT": -0.0004,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 13,
    "n_p_sig": 897,
    "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": 0.0409,
    "ldsc_observed_scale_h2_se": 0.0019,
    "ldsc_intercept_beta": 1.0298,
    "ldsc_intercept_se": 0.0084,
    "ldsc_lambda_gc": 1.323,
    "ldsc_mean_chisq": 1.3868,
    "ldsc_ratio": 0.077
}

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 TRUE
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 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 1.000000 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+07 828.000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -4.055000e-04 1.933070e-02 -0.276237 -6.441600e-03 -1.071000e-04 6.098600e-03 2.691830e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.360520e-02 1.288770e-02 0.003805 4.658700e-03 7.812300e-03 1.802710e-02 1.997900e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.680060e-01 2.974318e-01 0.000000 2.000000e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.680072e-01 2.974064e-01 0.000000 2.024605e-01 4.571213e-01 7.255510e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035070e-01 2.568667e-01 0.000973 1.316600e-02 7.790500e-02 3.164540e-01 9.990270e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.000000 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 -0.0012881 0.0070013 0.8499999 0.8540248 0.623782 0.7821490 NA
1 54676 rs2462492 C T 0.0102000 0.0069359 0.1400000 0.1413950 0.400455 NA NA
1 86028 rs114608975 T C -0.0185534 0.0110854 0.0940005 0.0941937 0.103568 0.0277556 NA
1 91536 rs6702460 G T 0.0187073 0.0068276 0.0061000 0.0061447 0.456885 0.4207270 NA
1 234313 rs8179466 C T -0.0103231 0.0134663 0.4400003 0.4433267 0.074506 NA NA
1 534192 rs6680723 C T 0.0057361 0.0077988 0.4600002 0.4620309 0.241049 NA NA
1 546697 rs12025928 A G -0.0045264 0.0097303 0.6400000 0.6418014 0.913450 NA NA
1 693731 rs12238997 A G -0.0065101 0.0065356 0.3200000 0.3191957 0.116329 0.1417730 NA
1 705882 rs72631875 G A -0.0158939 0.0095802 0.0969996 0.0971088 0.067290 0.0315495 NA
1 706368 rs55727773 A G 0.0062061 0.0048423 0.2000000 0.1999754 0.515791 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0252592 0.0101656 0.0129999 0.0129634 0.041949 0.0473243 NA
22 51219766 rs182321900 C T -0.0370886 0.0475225 0.4400003 0.4351302 0.001928 NA NA
22 51220146 rs868950473 C T -0.0468300 0.0470587 0.3200000 0.3196681 0.001978 NA NA
22 51221190 rs369304721 G A 0.0272664 0.0101528 0.0072000 0.0072399 0.049692 NA NA
22 51221731 rs115055839 T C 0.0188064 0.0075928 0.0129999 0.0132539 0.073197 0.0625000 NA
22 51222100 rs114553188 G T -0.0099926 0.0089365 0.2599998 0.2634903 0.054469 0.0880591 NA
22 51223637 rs375798137 G A -0.0096331 0.0089797 0.2800000 0.2833771 0.054099 0.0788738 NA
22 51229805 rs9616985 T C 0.0193511 0.0076202 0.0109999 0.0111027 0.073035 0.0730831 NA
22 51232488 rs376461333 A G -0.0079667 0.0179402 0.6600001 0.6569922 0.020047 NA NA
22 51237063 rs3896457 T C -0.0081146 0.0046601 0.0819993 0.0816325 0.298004 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623782 ES:SE:LP:AF:ID  -0.00128814:0.00700131:0.0705811:0.623782:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400455 ES:SE:LP:AF:ID  0.0102:0.00693587:0.853872:0.400455:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103568 ES:SE:LP:AF:ID  -0.0185534:0.0110854:1.02687:0.103568:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456885 ES:SE:LP:AF:ID  0.0187073:0.00682759:2.21467:0.456885:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074506 ES:SE:LP:AF:ID  -0.0103231:0.0134663:0.356547:0.074506:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241049 ES:SE:LP:AF:ID  0.00573607:0.0077988:0.337242:0.241049:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91345  ES:SE:LP:AF:ID  -0.00452637:0.00973033:0.19382:0.91345:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116329 ES:SE:LP:AF:ID  -0.00651014:0.00653555:0.49485:0.116329:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06729  ES:SE:LP:AF:ID  -0.0158939:0.00958021:1.01323:0.06729:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515791 ES:SE:LP:AF:ID  0.00620606:0.00484235:0.69897:0.515791:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032972 ES:SE:LP:AF:ID  -0.0147035:0.0122141:0.638272:0.032972:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036596 ES:SE:LP:AF:ID  -0.0101762:0.0110925:0.443698:0.036596:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.03671  ES:SE:LP:AF:ID  -0.00929093:0.0110508:0.39794:0.03671:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036409 ES:SE:LP:AF:ID  -0.0105592:0.0111308:0.468521:0.036409:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016389 ES:SE:LP:AF:ID  -0.0270611:0.0171394:0.958607:0.016389:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036952 ES:SE:LP:AF:ID  -0.00905037:0.0110065:0.387216:0.036952:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037046 ES:SE:LP:AF:ID  -0.00877028:0.0109693:0.376751:0.037046:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101183 ES:SE:LP:AF:ID  0.00470434:0.00799017:0.251812:0.101183:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959151 ES:SE:LP:AF:ID  0.0104709:0.0105829:0.49485:0.959151:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031448 ES:SE:LP:AF:ID  -0.0106319:0.0192034:0.236572:0.031448:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053279 ES:SE:LP:AF:ID  0.00386346:0.0152672:0.09691:0.053279:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036565 ES:SE:LP:AF:ID  -0.00769975:0.0110405:0.309804:0.036565:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03688  ES:SE:LP:AF:ID  -0.00796223:0.0109395:0.327902:0.03688:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843285 ES:SE:LP:AF:ID  0.00808382:0.0056652:0.823909:0.843285:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055945 ES:SE:LP:AF:ID  -0.00554927:0.00916871:0.259637:0.055945:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122284 ES:SE:LP:AF:ID  -0.00713412:0.00620042:0.60206:0.122284:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025727 ES:SE:LP:AF:ID  -0.00976525:0.0152427:0.283997:0.025727:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121526 ES:SE:LP:AF:ID  -0.00689283:0.00620308:0.568636:0.121526:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132316 ES:SE:LP:AF:ID  -0.00402507:0.0061134:0.29243:0.132316:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011142 ES:SE:LP:AF:ID  -0.0214027:0.0222189:0.468521:0.011142:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005695 ES:SE:LP:AF:ID  -0.00334724:0.0287083:0.0409586:0.005695:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002241 ES:SE:LP:AF:ID  -0.0375151:0.0485962:0.356547:0.002241:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.001028 ES:SE:LP:AF:ID  -0.0967247:0.0789337:0.657577:0.001028:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036793 ES:SE:LP:AF:ID  -0.00820761:0.0108294:0.346787:0.036793:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839046 ES:SE:LP:AF:ID  0.00702548:0.00548671:0.69897:0.839046:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838676 ES:SE:LP:AF:ID  0.00757022:0.00548087:0.769551:0.838676:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869846 ES:SE:LP:AF:ID  0.00702723:0.0058813:0.638272:0.869846:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129811 ES:SE:LP:AF:ID  -0.00761681:0.00589323:0.69897:0.129811:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037301 ES:SE:LP:AF:ID  -0.00804987:0.0106463:0.346787:0.037301:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037544 ES:SE:LP:AF:ID  -0.00812862:0.0105793:0.356547:0.037544:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869192 ES:SE:LP:AF:ID  0.00751908:0.00586986:0.69897:0.869192:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869289 ES:SE:LP:AF:ID  0.0079353:0.00587222:0.744727:0.869289:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037502 ES:SE:LP:AF:ID  -0.00752775:0.010625:0.318759:0.037502:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869194 ES:SE:LP:AF:ID  0.00755338:0.00586975:0.69897:0.869194:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005099 ES:SE:LP:AF:ID  0.0294354:0.0301987:0.481486:0.005099:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005065 ES:SE:LP:AF:ID  0.0285896:0.0302773:0.455932:0.005065:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838126 ES:SE:LP:AF:ID  0.00780854:0.00546563:0.823909:0.838126:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037514 ES:SE:LP:AF:ID  -0.00770743:0.0106402:0.327902:0.037514:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838754 ES:SE:LP:AF:ID  0.00770837:0.00548092:0.79588:0.838754:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013766 ES:SE:LP:AF:ID  0.0268459:0.0191325:0.79588:0.013766:rs181660517