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-1252/UKB-b-1252_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1252/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:04 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1252/UKB-b-1252_data.vcf.gz ...
Read summary statistics for 8625018 SNPs.
Dropped 7369 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, 1285750 SNPs remain.
After merging with regression SNP LD, 1285750 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0019 (0.0065)
Lambda GC: 1.0178
Mean Chi^2: 1.0104
Intercept: 1.0128 (0.006)
Ratio: 1.2329 (0.5794)
Analysis finished at Thu Oct 17 14:43:30 2019
Total time elapsed: 1.0m:26.56s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9462,
    "inflation_factor": 1,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 3,
    "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": 83098,
    "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": 1285750,
    "ldsc_nsnp_merge_regression_ld": 1285750,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0128,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0178,
    "ldsc_mean_chisq": 1.0104,
    "ldsc_ratio": 1.2308
}

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 8617683 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 8625018 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 8.650329e+00 5.760994e+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 7.877026e+07 5.637181e+07 828.0000000 3.238540e+07 6.929221e+07 1.145691e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.780000e-05 3.681300e-03 -0.0326235 -1.549700e-03 -1.930000e-05 1.503100e-03 4.944560e-02 ▁▇▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.026400e-03 2.065800e-03 0.0012020 1.415400e-03 2.087000e-03 4.091000e-03 2.071880e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.982110e-01 2.889979e-01 0.0000000 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 4.982135e-01 2.889719e-01 0.0000000 2.471542e-01 4.968106e-01 7.487723e-01 9.999996e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.291162e-01 2.594878e-01 0.0053900 2.518900e-02 1.138950e-01 3.626240e-01 9.946100e-01 ▇▂▁▁▁
numeric AF_reference 83098 0.9903655 NA NA NA NA NA NA NA 2.288654e-01 2.514587e-01 0.0000000 2.316290e-02 1.303910e-01 3.596250e-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 -0.0015600 0.0022152 0.4799997 0.4812789 0.623808 0.7821490 NA
1 54676 rs2462492 C T 0.0035693 0.0022087 0.1100001 0.1060964 0.399158 NA NA
1 86028 rs114608975 T C -0.0051841 0.0035168 0.1400000 0.1404611 0.103518 0.0277556 NA
1 91536 rs6702460 G T 0.0020968 0.0021726 0.3300000 0.3344916 0.455910 0.4207270 NA
1 234313 rs8179466 C T 0.0055071 0.0042960 0.2000000 0.1998765 0.074461 NA NA
1 534192 rs6680723 C T -0.0014068 0.0024742 0.5700002 0.5696558 0.242067 NA NA
1 546697 rs12025928 A G 0.0013150 0.0030699 0.6700003 0.6684069 0.912864 NA NA
1 693731 rs12238997 A G 0.0018799 0.0020630 0.3599996 0.3621852 0.117327 0.1417730 NA
1 705882 rs72631875 G A -0.0011569 0.0030072 0.6999999 0.7004498 0.067699 0.0315495 NA
1 706368 rs55727773 A G -0.0007236 0.0015314 0.6400000 0.6365429 0.513285 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0039616 0.0018626 0.0329997 0.0334282 0.136309 0.2052720 NA
22 51219387 rs9616832 T C 0.0062630 0.0024276 0.0099001 0.0098827 0.071802 0.0654952 NA
22 51219704 rs147475742 G A 0.0053128 0.0032292 0.1000000 0.0999213 0.041198 0.0473243 NA
22 51221190 rs369304721 G A 0.0083017 0.0032521 0.0109999 0.0106893 0.048381 NA NA
22 51221731 rs115055839 T C 0.0064946 0.0024281 0.0075000 0.0074792 0.071353 0.0625000 NA
22 51222100 rs114553188 G T -0.0011210 0.0028141 0.6899999 0.6903593 0.054838 0.0880591 NA
22 51223637 rs375798137 G A -0.0011214 0.0028288 0.6899999 0.6917856 0.054458 0.0788738 NA
22 51229805 rs9616985 T C 0.0065980 0.0024356 0.0068000 0.0067501 0.071258 0.0730831 NA
22 51232488 rs376461333 A G 0.0042947 0.0056099 0.4400003 0.4439341 0.020458 NA NA
22 51237063 rs3896457 T C -0.0001288 0.0014704 0.9299999 0.9302006 0.298394 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623808 ES:SE:LP:AF:ID  -0.00156002:0.00221516:0.318759:0.623808:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399158 ES:SE:LP:AF:ID  0.00356927:0.00220872:0.958607:0.399158:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103518 ES:SE:LP:AF:ID  -0.00518409:0.00351684:0.853872:0.103518:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.45591  ES:SE:LP:AF:ID  0.00209679:0.0021726:0.481486:0.45591:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074461 ES:SE:LP:AF:ID  0.00550707:0.00429601:0.69897:0.074461:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242067 ES:SE:LP:AF:ID  -0.00140675:0.00247424:0.244125:0.242067:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912864 ES:SE:LP:AF:ID  0.00131496:0.00306993:0.173925:0.912864:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117327 ES:SE:LP:AF:ID  0.00187987:0.00206305:0.443698:0.117327:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067699 ES:SE:LP:AF:ID  -0.00115691:0.0030072:0.154902:0.067699:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513285 ES:SE:LP:AF:ID  -0.000723635:0.00153138:0.19382:0.513285:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03367  ES:SE:LP:AF:ID  -0.00526986:0.0038175:0.769551:0.03367:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03745  ES:SE:LP:AF:ID  -0.00450622:0.00346228:0.721246:0.03745:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037636 ES:SE:LP:AF:ID  -0.00460592:0.00344417:0.744727:0.037636:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037213 ES:SE:LP:AF:ID  -0.00448648:0.00347563:0.69897:0.037213:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016279 ES:SE:LP:AF:ID  -0.00558994:0.0054517:0.508638:0.016279:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037853 ES:SE:LP:AF:ID  -0.00408158:0.0034324:0.638272:0.037853:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037947 ES:SE:LP:AF:ID  -0.00410335:0.0034215:0.638272:0.037947:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.102752 ES:SE:LP:AF:ID  0.00117716:0.00249892:0.19382:0.102752:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958097 ES:SE:LP:AF:ID  0.000997137:0.00330464:0.119186:0.958097:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031684 ES:SE:LP:AF:ID  -0.00180733:0.00605222:0.113509:0.031684:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052728 ES:SE:LP:AF:ID  0.00270929:0.00487337:0.236572:0.052728:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03744  ES:SE:LP:AF:ID  -0.00396424:0.00344401:0.60206:0.03744:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037709 ES:SE:LP:AF:ID  -0.00402289:0.00341547:0.619789:0.037709:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841429 ES:SE:LP:AF:ID  -0.00125535:0.00178419:0.318759:0.841429:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056344 ES:SE:LP:AF:ID  0.00282516:0.00289819:0.481486:0.056344:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123099 ES:SE:LP:AF:ID  0.00160255:0.00195963:0.387216:0.123099:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025134 ES:SE:LP:AF:ID  0.00335431:0.00488005:0.309804:0.025134:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122351 ES:SE:LP:AF:ID  0.00174929:0.00196026:0.431798:0.122351:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134148 ES:SE:LP:AF:ID  0.000846631:0.00192439:0.180456:0.134148:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011558 ES:SE:LP:AF:ID  -0.00737404:0.00685821:0.552842:0.011558:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006101 ES:SE:LP:AF:ID  -0.00768563:0.00870907:0.420216:0.006101:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037592 ES:SE:LP:AF:ID  -0.00376323:0.00338379:0.568636:0.037592:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837015 ES:SE:LP:AF:ID  -0.00105981:0.00172599:0.267606:0.837015:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836719 ES:SE:LP:AF:ID  -0.00106503:0.00172472:0.267606:0.836719:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868544 ES:SE:LP:AF:ID  -0.00243017:0.00185326:0.721246:0.868544:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131022 ES:SE:LP:AF:ID  0.00232875:0.00185802:0.677781:0.131022:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038037 ES:SE:LP:AF:ID  -0.00394565:0.00333073:0.619789:0.038037:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038283 ES:SE:LP:AF:ID  -0.00380051:0.00331009:0.60206:0.038283:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867957 ES:SE:LP:AF:ID  -0.00261033:0.00185028:0.79588:0.867957:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868032 ES:SE:LP:AF:ID  -0.00262977:0.00185104:0.79588:0.868032:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038191 ES:SE:LP:AF:ID  -0.00391551:0.00332538:0.619789:0.038191:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867968 ES:SE:LP:AF:ID  -0.0026162:0.00185024:0.79588:0.867968:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005397 ES:SE:LP:AF:ID  0.0126915:0.00927298:0.769551:0.005397:rs150578204
1   754503  rs3115859   G   A   .   PASS    AF=0.836144 ES:SE:LP:AF:ID  -0.00122404:0.00171968:0.318759:0.836144:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038194 ES:SE:LP:AF:ID  -0.00401356:0.00333024:0.638272:0.038194:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836778 ES:SE:LP:AF:ID  -0.00116077:0.00172439:0.30103:0.836778:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013016 ES:SE:LP:AF:ID  -0.000599561:0.00624288:0.0362122:0.013016:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005663 ES:SE:LP:AF:ID  -0.00354507:0.00926083:0.154902:0.005663:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838089 ES:SE:LP:AF:ID  -0.00115285:0.00174863:0.29243:0.838089:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868203 ES:SE:LP:AF:ID  -0.00224128:0.00184784:0.638272:0.868203:rs3115858