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-8882/UKB-b-8882_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8882/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:07 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8882/UKB-b-8882_data.vcf.gz ...
Read summary statistics for 9022059 SNPs.
Dropped 8796 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, 1287270 SNPs remain.
After merging with regression SNP LD, 1287270 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0195 (0.0047)
Lambda GC: 1.0458
Mean Chi^2: 1.0503
Intercept: 1.0125 (0.006)
Ratio: 0.2479 (0.119)
Analysis finished at Thu Oct 17 14:43:49 2019
Total time elapsed: 1.0m:42.08s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9479,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 2,
    "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": 94053,
    "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": 1287270,
    "ldsc_nsnp_merge_regression_ld": 1287270,
    "ldsc_observed_scale_h2_beta": 0.0195,
    "ldsc_observed_scale_h2_se": 0.0047,
    "ldsc_intercept_beta": 1.0125,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0458,
    "ldsc_mean_chisq": 1.0503,
    "ldsc_ratio": 0.2485
}

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 9013303 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 9022059 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 8.643024e+00 5.758175e+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 7.878407e+07 5.633858e+07 828.0000000 3.242955e+07 6.934521e+07 1.145363e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -2.030000e-05 1.476730e-02 -0.1715700 -5.786600e-03 -2.110000e-05 5.747800e-03 2.149850e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.183680e-02 8.699800e-03 0.0042879 5.112600e-03 7.840000e-03 1.624000e-02 9.914350e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.951642e-01 2.900862e-01 0.0000000 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.951634e-01 2.900617e-01 0.0000000 2.428054e-01 4.932533e-01 7.463441e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.198991e-01 2.585027e-01 0.0035220 2.035600e-02 1.010910e-01 3.467070e-01 9.964780e-01 ▇▂▁▁▁
numeric AF_reference 94053 0.9895752 NA NA NA NA NA NA NA 2.202378e-01 2.504037e-01 0.0000000 1.777160e-02 1.186100e-01 3.452480e-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 -0.0040476 0.0079167 0.6100002 0.6091626 0.623633 0.7821490 NA
1 54676 rs2462492 C T 0.0030328 0.0078662 0.6999999 0.6998345 0.398783 NA NA
1 86028 rs114608975 T C -0.0085630 0.0124756 0.4899999 0.4924731 0.104060 0.0277556 NA
1 91536 rs6702460 G T -0.0073087 0.0077332 0.3400001 0.3446055 0.455520 0.4207270 NA
1 234313 rs8179466 C T -0.0121005 0.0151437 0.4199997 0.4242642 0.074819 NA NA
1 534192 rs6680723 C T 0.0000379 0.0088462 1.0000000 0.9965859 0.240535 NA NA
1 546697 rs12025928 A G 0.0000600 0.0109622 1.0000000 0.9956300 0.912839 NA NA
1 693731 rs12238997 A G 0.0016678 0.0073597 0.8200001 0.8207296 0.117660 0.1417730 NA
1 705882 rs72631875 G A 0.0093858 0.0107645 0.3800004 0.3832512 0.067625 0.0315495 NA
1 706368 rs55727773 A G 0.0061522 0.0054536 0.2599998 0.2592806 0.514166 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0089854 0.0066000 0.1700000 0.1733811 0.137184 0.2052720 NA
22 51219387 rs9616832 T C 0.0060633 0.0086036 0.4799997 0.4809707 0.072570 0.0654952 NA
22 51219704 rs147475742 G A 0.0126785 0.0114375 0.2700001 0.2676448 0.041839 0.0473243 NA
22 51221190 rs369304721 G A 0.0063298 0.0115129 0.5800000 0.5824567 0.049067 NA NA
22 51221731 rs115055839 T C 0.0050741 0.0086062 0.5600000 0.5554654 0.072098 0.0625000 NA
22 51222100 rs114553188 G T 0.0127801 0.0100564 0.2000000 0.2037847 0.054522 0.0880591 NA
22 51223637 rs375798137 G A 0.0122805 0.0101090 0.2200002 0.2244391 0.054135 0.0788738 NA
22 51229805 rs9616985 T C 0.0052890 0.0086375 0.5400003 0.5403145 0.071960 0.0730831 NA
22 51232488 rs376461333 A G 0.0175237 0.0203368 0.3900004 0.3888667 0.020058 NA NA
22 51237063 rs3896457 T C -0.0063941 0.0052487 0.2200002 0.2231417 0.298287 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623633 ES:SE:LP:AF:ID  -0.00404758:0.00791673:0.21467:0.623633:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.398783 ES:SE:LP:AF:ID  0.00303275:0.00786616:0.154902:0.398783:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10406  ES:SE:LP:AF:ID  -0.00856301:0.0124756:0.309804:0.10406:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.45552  ES:SE:LP:AF:ID  -0.00730873:0.00773325:0.468521:0.45552:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074819 ES:SE:LP:AF:ID  -0.0121005:0.0151437:0.376751:0.074819:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240535 ES:SE:LP:AF:ID  3.78522e-05:0.00884617:-0:0.240535:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912839 ES:SE:LP:AF:ID  6.00396e-05:0.0109622:-0:0.912839:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11766  ES:SE:LP:AF:ID  0.00166775:0.00735967:0.0861861:0.11766:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067625 ES:SE:LP:AF:ID  0.0093858:0.0107645:0.420216:0.067625:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514166 ES:SE:LP:AF:ID  0.00615218:0.00545361:0.585027:0.514166:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033703 ES:SE:LP:AF:ID  0.0155848:0.0136022:0.60206:0.033703:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037357 ES:SE:LP:AF:ID  0.0126104:0.0123734:0.508638:0.037357:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037443 ES:SE:LP:AF:ID  0.0144934:0.0123329:0.619789:0.037443:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037141 ES:SE:LP:AF:ID  0.0125379:0.0124171:0.508638:0.037141:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.01673  ES:SE:LP:AF:ID  0.00987687:0.0191574:0.21467:0.01673:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037704 ES:SE:LP:AF:ID  0.0126558:0.0122798:0.522879:0.037704:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037793 ES:SE:LP:AF:ID  0.0131987:0.0122415:0.552842:0.037793:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101386 ES:SE:LP:AF:ID  -0.0109195:0.00901344:0.638272:0.101386:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958003 ES:SE:LP:AF:ID  -0.014163:0.011776:0.638272:0.958003:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031821 ES:SE:LP:AF:ID  0.0188104:0.021538:0.420216:0.031821:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052577 ES:SE:LP:AF:ID  0.0267219:0.0174023:0.920819:0.052577:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037251 ES:SE:LP:AF:ID  0.0107594:0.0123277:0.420216:0.037251:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037567 ES:SE:LP:AF:ID  0.00976199:0.0122233:0.376751:0.037567:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84101  ES:SE:LP:AF:ID  -0.00583133:0.00637297:0.443698:0.84101:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056088 ES:SE:LP:AF:ID  -0.00924145:0.0103733:0.431798:0.056088:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123562 ES:SE:LP:AF:ID  0.00300179:0.00698731:0.173925:0.123562:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025857 ES:SE:LP:AF:ID  0.00166576:0.0171568:0.0362122:0.025857:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122759 ES:SE:LP:AF:ID  0.00271031:0.00699087:0.154902:0.122759:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133585 ES:SE:LP:AF:ID  0.00479061:0.00688866:0.309804:0.133585:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011246 ES:SE:LP:AF:ID  -0.0378983:0.0249208:0.886057:0.011246:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006015 ES:SE:LP:AF:ID  0.0445965:0.0313812:0.79588:0.006015:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.03754  ES:SE:LP:AF:ID  0.00987388:0.0120872:0.387216:0.03754:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.836798 ES:SE:LP:AF:ID  -0.00275651:0.00616688:0.187087:0.836798:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83637  ES:SE:LP:AF:ID  -0.00305313:0.00615988:0.207608:0.83637:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868134 ES:SE:LP:AF:ID  0.000220458:0.00660959:0.0132283:0.868134:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131522 ES:SE:LP:AF:ID  0.000866656:0.00662387:0.0457575:0.131522:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037983 ES:SE:LP:AF:ID  0.0112695:0.0118971:0.468521:0.037983:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038232 ES:SE:LP:AF:ID  0.0104154:0.0118231:0.420216:0.038232:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867441 ES:SE:LP:AF:ID  -0.000226537:0.00659629:0.0132283:0.867441:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867546 ES:SE:LP:AF:ID  0.000161433:0.00659944:0.00877392:0.867546:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038181 ES:SE:LP:AF:ID  0.0110025:0.0118709:0.455932:0.038181:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86744  ES:SE:LP:AF:ID  -0.000242882:0.00659588:0.0132283:0.86744:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00508  ES:SE:LP:AF:ID  -0.0131004:0.0341817:0.154902:0.00508:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005048 ES:SE:LP:AF:ID  -0.0130138:0.0342768:0.154902:0.005048:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.835914 ES:SE:LP:AF:ID  -0.00328978:0.00614669:0.229148:0.835914:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038198 ES:SE:LP:AF:ID  0.0102338:0.0118867:0.408935:0.038198:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836519 ES:SE:LP:AF:ID  -0.00301523:0.00616323:0.207608:0.836519:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013186 ES:SE:LP:AF:ID  0.0535032:0.0221011:1.82391:0.013186:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005526 ES:SE:LP:AF:ID  -0.0650087:0.0333581:1.29243:0.005526:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.837809 ES:SE:LP:AF:ID  -0.00315571:0.00624769:0.21467:0.837809:rs3131965