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-6092/UKB-b-6092_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6092/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:46 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6092/UKB-b-6092_data.vcf.gz ...
Read summary statistics for 8754662 SNPs.
Dropped 7745 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, 1286110 SNPs remain.
After merging with regression SNP LD, 1286110 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0004 (0.0057)
Lambda GC: 1.0152
Mean Chi^2: 1.0121
Intercept: 1.0115 (0.0056)
Ratio: 0.9474 (0.4605)
Analysis finished at Thu Oct 17 14:47:09 2019
Total time elapsed: 1.0m:23.41s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9466,
    "inflation_factor": 1,
    "mean_EFFECT": -0.0001,
    "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": 85913,
    "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": 1286110,
    "ldsc_nsnp_merge_regression_ld": 1286110,
    "ldsc_observed_scale_h2_beta": 0.0004,
    "ldsc_observed_scale_h2_se": 0.0057,
    "ldsc_intercept_beta": 1.0115,
    "ldsc_intercept_se": 0.0056,
    "ldsc_lambda_gc": 1.0152,
    "ldsc_mean_chisq": 1.0121,
    "ldsc_ratio": 0.9504
}

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 TRUE
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 8746953 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 8754662 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 8.649526e+00 5.760725e+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 7.876969e+07 5.635519e+07 828.0000000 3.239934e+07 6.930809e+07 1.145517e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -5.310000e-05 1.539620e-02 -0.2042810 -6.295300e-03 -6.230000e-05 6.197900e-03 1.716260e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.255980e-02 8.775000e-03 0.0048384 5.724800e-03 8.551700e-03 1.707530e-02 8.188610e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.981024e-01 2.894420e-01 0.0000002 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.981017e-01 2.894175e-01 0.0000002 2.469195e-01 4.968761e-01 7.490552e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.259564e-01 2.591979e-01 0.0047800 2.347700e-02 1.094210e-01 3.571357e-01 9.952200e-01 ▇▂▁▁▁
numeric AF_reference 85913 0.9901866 NA NA NA NA NA NA NA 2.258214e-01 2.511493e-01 0.0000000 2.096650e-02 1.263980e-01 3.546330e-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 0.0058875 0.0088947 0.5099998 0.5080268 0.624261 0.7821490 NA
1 54676 rs2462492 C T -0.0008661 0.0088097 0.9199999 0.9216834 0.399908 NA NA
1 86028 rs114608975 T C -0.0059192 0.0140447 0.6700003 0.6734213 0.103915 0.0277556 NA
1 91536 rs6702460 G T 0.0011003 0.0086299 0.9000000 0.8985444 0.457149 0.4207270 NA
1 234313 rs8179466 C T -0.0374343 0.0170996 0.0290001 0.0285829 0.074414 NA NA
1 534192 rs6680723 C T 0.0183289 0.0099174 0.0649995 0.0645798 0.241286 NA NA
1 546697 rs12025928 A G 0.0008625 0.0123445 0.9400001 0.9442997 0.913388 NA NA
1 693731 rs12238997 A G 0.0038399 0.0082843 0.6400000 0.6429941 0.117164 0.1417730 NA
1 705882 rs72631875 G A -0.0035710 0.0121819 0.7700005 0.7694121 0.067078 0.0315495 NA
1 706368 rs55727773 A G 0.0037388 0.0061488 0.5400003 0.5431530 0.515208 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0015388 0.0074454 0.8400000 0.8362654 0.137020 0.2052720 NA
22 51219387 rs9616832 T C 0.0012862 0.0096271 0.8900000 0.8937180 0.073707 0.0654952 NA
22 51219704 rs147475742 G A 0.0014279 0.0128876 0.9100000 0.9117790 0.042224 0.0473243 NA
22 51221190 rs369304721 G A -0.0013013 0.0128973 0.9199999 0.9196328 0.049611 NA NA
22 51221731 rs115055839 T C 0.0014889 0.0096350 0.8800001 0.8771886 0.073214 0.0625000 NA
22 51222100 rs114553188 G T -0.0079231 0.0114125 0.4899999 0.4875253 0.053916 0.0880591 NA
22 51223637 rs375798137 G A -0.0082736 0.0114759 0.4700002 0.4709371 0.053497 0.0788738 NA
22 51229805 rs9616985 T C 0.0019378 0.0096686 0.8400000 0.8411519 0.073070 0.0730831 NA
22 51232488 rs376461333 A G -0.0092990 0.0231292 0.6899999 0.6876490 0.019531 NA NA
22 51237063 rs3896457 T C -0.0026042 0.0059155 0.6600001 0.6597720 0.299484 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.624261 ES:SE:LP:AF:ID  0.00588752:0.0088947:0.29243:0.624261:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399908 ES:SE:LP:AF:ID  -0.000866113:0.00880971:0.0362122:0.399908:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103915 ES:SE:LP:AF:ID  -0.00591924:0.0140447:0.173925:0.103915:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457149 ES:SE:LP:AF:ID  0.00110031:0.00862986:0.0457575:0.457149:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074414 ES:SE:LP:AF:ID  -0.0374343:0.0170996:1.5376:0.074414:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241286 ES:SE:LP:AF:ID  0.0183289:0.0099174:1.18709:0.241286:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913388 ES:SE:LP:AF:ID  0.000862471:0.0123445:0.0268721:0.913388:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117164 ES:SE:LP:AF:ID  0.00383992:0.00828432:0.19382:0.117164:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067078 ES:SE:LP:AF:ID  -0.00357105:0.0121819:0.113509:0.067078:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515208 ES:SE:LP:AF:ID  0.00373876:0.00614875:0.267606:0.515208:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032053 ES:SE:LP:AF:ID  0.0164132:0.0157267:0.522879:0.032053:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.035608 ES:SE:LP:AF:ID  0.013036:0.0142838:0.443698:0.035608:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.035739 ES:SE:LP:AF:ID  0.0135597:0.0142274:0.468521:0.035739:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.035424 ES:SE:LP:AF:ID  0.0144835:0.014337:0.508638:0.035424:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016368 ES:SE:LP:AF:ID  0.015675:0.0218402:0.327902:0.016368:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.035919 ES:SE:LP:AF:ID  0.00973855:0.0141837:0.309804:0.035919:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036036 ES:SE:LP:AF:ID  0.011056:0.0141332:0.366532:0.036036:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101325 ES:SE:LP:AF:ID  -0.00324279:0.0101689:0.124939:0.101325:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.960254 ES:SE:LP:AF:ID  -0.0165955:0.0136412:0.657577:0.960254:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031052 ES:SE:LP:AF:ID  -0.0417868:0.0246499:1.04576:0.031052:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053807 ES:SE:LP:AF:ID  -0.00866294:0.0190804:0.187087:0.053807:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.035554 ES:SE:LP:AF:ID  0.0136394:0.0142229:0.468521:0.035554:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.035962 ES:SE:LP:AF:ID  0.0141032:0.0140636:0.49485:0.035962:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843365 ES:SE:LP:AF:ID  -0.00786361:0.00719854:0.568636:0.843365:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056313 ES:SE:LP:AF:ID  0.00342694:0.0116121:0.113509:0.056313:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123409 ES:SE:LP:AF:ID  0.00263055:0.00785493:0.130768:0.123409:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.02571  ES:SE:LP:AF:ID  0.00205156:0.0193512:0.0362122:0.02571:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122664 ES:SE:LP:AF:ID  0.00343186:0.00785956:0.180456:0.122664:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132394 ES:SE:LP:AF:ID  0.00553666:0.00776134:0.318759:0.132394:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011083 ES:SE:LP:AF:ID  -0.0326284:0.0281971:0.60206:0.011083:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006032 ES:SE:LP:AF:ID  0.0160104:0.0354482:0.187087:0.006032:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.035759 ES:SE:LP:AF:ID  0.0124818:0.0139541:0.431798:0.035759:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839185 ES:SE:LP:AF:ID  -0.00316861:0.00697659:0.187087:0.839185:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838814 ES:SE:LP:AF:ID  -0.00314416:0.00696828:0.187087:0.838814:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868946 ES:SE:LP:AF:ID  -0.00033108:0.00746249:0.0177288:0.868946:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130699 ES:SE:LP:AF:ID  -0.000731313:0.00747412:0.0362122:0.130699:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.036219 ES:SE:LP:AF:ID  0.0138088:0.0137266:0.508638:0.036219:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03644  ES:SE:LP:AF:ID  0.0138705:0.0136451:0.508638:0.03644:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868295 ES:SE:LP:AF:ID  0.000129238:0.00744717:0.00436481:0.868295:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868408 ES:SE:LP:AF:ID  0.000178293:0.00745082:0.00877392:0.868408:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.036447 ES:SE:LP:AF:ID  0.014083:0.013694:0.522879:0.036447:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868306 ES:SE:LP:AF:ID  7.42769e-05:0.00744748:0.00436481:0.868306:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005144 ES:SE:LP:AF:ID  -0.0436905:0.0382818:0.60206:0.005144:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005115 ES:SE:LP:AF:ID  -0.0459239:0.0383746:0.638272:0.005115:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838379 ES:SE:LP:AF:ID  -0.00347989:0.00695335:0.207608:0.838379:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03646  ES:SE:LP:AF:ID  0.0145569:0.0137138:0.537602:0.03646:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838976 ES:SE:LP:AF:ID  -0.0034075:0.00697219:0.200659:0.838976:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013942 ES:SE:LP:AF:ID  -0.00294966:0.0240659:0.0457575:0.013942:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.00565  ES:SE:LP:AF:ID  0.0882404:0.0370317:1.76955:0.00565:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839984 ES:SE:LP:AF:ID  -0.0027701:0.00706441:0.161151:0.839984:rs3131965