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-9363/UKB-b-9363_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9363/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:29 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9363/UKB-b-9363_data.vcf.gz ...
Read summary statistics for 9477637 SNPs.
Dropped 11435 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, 1288312 SNPs remain.
After merging with regression SNP LD, 1288312 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0223 (0.0017)
Lambda GC: 1.2947
Mean Chi^2: 1.3251
Intercept: 1.1229 (0.0083)
Ratio: 0.378 (0.0256)
Analysis finished at Thu Oct 17 14:44:03 2019
Total time elapsed: 1.0m:34.34s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9491,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 3.1187e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 15,
    "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": 130331,
    "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": 1288312,
    "ldsc_nsnp_merge_regression_ld": 1288312,
    "ldsc_observed_scale_h2_beta": 0.0223,
    "ldsc_observed_scale_h2_se": 0.0017,
    "ldsc_intercept_beta": 1.1229,
    "ldsc_intercept_se": 0.0083,
    "ldsc_lambda_gc": 1.2947,
    "ldsc_mean_chisq": 1.3251,
    "ldsc_ratio": 0.378
}

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 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 9466262 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 9477637 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 8.629617e+00 5.752292e+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 7.883518e+07 5.631151e+07 828.0000000 3.253488e+07 6.941744e+07 1.145692e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.100000e-06 4.295200e-03 -0.0745067 -1.528300e-03 1.290000e-05 1.548500e-03 5.597260e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.087800e-03 2.567600e-03 0.0009835 1.189400e-03 1.913700e-03 4.205800e-03 3.414360e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.661590e-01 2.972756e-01 0.0000000 2.000000e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.661606e-01 2.972524e-01 0.0000000 2.005557e-01 4.536057e-01 7.232835e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.102675e-01 2.573766e-01 0.0018180 1.596700e-02 8.750500e-02 3.291860e-01 9.981820e-01 ▇▂▁▁▁
numeric AF_reference 130331 0.9862486 NA NA NA NA NA NA NA 2.118603e-01 2.491059e-01 0.0000000 1.357830e-02 1.070290e-01 3.302720e-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 -0.0021314 0.0018089 0.2399999 0.2386693 0.623758 0.7821490 NA
1 54676 rs2462492 C T 0.0010013 0.0017921 0.5800000 0.5763507 0.400400 NA NA
1 86028 rs114608975 T C 0.0033189 0.0028652 0.2500000 0.2467221 0.103558 0.0277556 NA
1 91536 rs6702460 G T 0.0016309 0.0017646 0.3599996 0.3553636 0.456848 0.4207270 NA
1 234313 rs8179466 C T -0.0017337 0.0034791 0.6200004 0.6182717 0.074507 NA NA
1 534192 rs6680723 C T 0.0016669 0.0020156 0.4100001 0.4082453 0.240949 NA NA
1 546697 rs12025928 A G -0.0027357 0.0025145 0.2800000 0.2765991 0.913472 NA NA
1 693731 rs12238997 A G 0.0006539 0.0016891 0.6999999 0.6986567 0.116334 0.1417730 NA
1 705882 rs72631875 G A 0.0016805 0.0024752 0.5000000 0.4971808 0.067291 0.0315495 NA
1 706368 rs55727773 A G -0.0012947 0.0012512 0.2999998 0.3007779 0.515645 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A 0.0033440 0.0026273 0.2000000 0.2030943 0.041954 0.0473243 NA
22 51219766 rs182321900 C T -0.0062666 0.0122405 0.6100002 0.6086794 0.001937 NA NA
22 51220146 rs868950473 C T -0.0061871 0.0121254 0.6100002 0.6098720 0.001985 NA NA
22 51221190 rs369304721 G A 0.0006377 0.0026230 0.8100000 0.8079014 0.049730 NA NA
22 51221731 rs115055839 T C 0.0012759 0.0019619 0.5199996 0.5154713 0.073235 0.0625000 NA
22 51222100 rs114553188 G T 0.0015851 0.0023096 0.4899999 0.4925165 0.054462 0.0880591 NA
22 51223637 rs375798137 G A 0.0015376 0.0023208 0.5099998 0.5076508 0.054091 0.0788738 NA
22 51229805 rs9616985 T C 0.0010876 0.0019690 0.5800000 0.5806755 0.073070 0.0730831 NA
22 51232488 rs376461333 A G 0.0015423 0.0046379 0.7400005 0.7394757 0.020046 NA NA
22 51237063 rs3896457 T C 0.0023585 0.0012042 0.0500000 0.0501766 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623758 ES:SE:LP:AF:ID  -0.00213145:0.00180889:0.619789:0.623758:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.4004   ES:SE:LP:AF:ID  0.00100131:0.00179214:0.236572:0.4004:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103558 ES:SE:LP:AF:ID  0.00331891:0.00286521:0.60206:0.103558:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456848 ES:SE:LP:AF:ID  0.00163086:0.00176455:0.443698:0.456848:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074507 ES:SE:LP:AF:ID  -0.00173366:0.00347914:0.207608:0.074507:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240949 ES:SE:LP:AF:ID  0.00166688:0.00201561:0.387216:0.240949:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913472 ES:SE:LP:AF:ID  -0.00273571:0.00251446:0.552842:0.913472:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116334 ES:SE:LP:AF:ID  0.000653901:0.00168908:0.154902:0.116334:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067291 ES:SE:LP:AF:ID  0.0016805:0.00247521:0.30103:0.067291:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  -0.0012947:0.0012512:0.522879:0.515645:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033002 ES:SE:LP:AF:ID  -0.00170059:0.00315456:0.229148:0.033002:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036618 ES:SE:LP:AF:ID  -0.00136516:0.00286536:0.200659:0.036618:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036735 ES:SE:LP:AF:ID  -0.00173602:0.00285452:0.267606:0.036735:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036434 ES:SE:LP:AF:ID  -0.00161096:0.0028751:0.236572:0.036434:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016412 ES:SE:LP:AF:ID  0.00412012:0.00442611:0.455932:0.016412:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036974 ES:SE:LP:AF:ID  -0.00180284:0.00284319:0.275724:0.036974:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037071 ES:SE:LP:AF:ID  -0.00182746:0.00283345:0.283997:0.037071:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101207 ES:SE:LP:AF:ID  0.00316848:0.00206443:0.920819:0.101207:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959097 ES:SE:LP:AF:ID  0.00327979:0.00273277:0.638272:0.959097:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031451 ES:SE:LP:AF:ID  -0.00640573:0.00496093:0.69897:0.031451:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053254 ES:SE:LP:AF:ID  -0.00920157:0.0039466:1.69897:0.053254:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036588 ES:SE:LP:AF:ID  -0.00139826:0.00285184:0.207608:0.036588:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036905 ES:SE:LP:AF:ID  -0.00122585:0.00282588:0.180456:0.036905:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843204 ES:SE:LP:AF:ID  0.000285657:0.00146381:0.0705811:0.843204:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055915 ES:SE:LP:AF:ID  -0.000644055:0.00237006:0.102373:0.055915:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122316 ES:SE:LP:AF:ID  0.000298932:0.00160226:0.0705811:0.122316:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025716 ES:SE:LP:AF:ID  0.00161874:0.00394093:0.167491:0.025716:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121559 ES:SE:LP:AF:ID  0.000430864:0.00160293:0.102373:0.121559:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132333 ES:SE:LP:AF:ID  -0.000506463:0.00157985:0.124939:0.132333:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011136 ES:SE:LP:AF:ID  0.000134743:0.0057439:0.00877392:0.011136:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005697 ES:SE:LP:AF:ID  -0.00816399:0.00741726:0.568636:0.005697:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002271 ES:SE:LP:AF:ID  -0.0197507:0.0124625:0.958607:0.002271:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036819 ES:SE:LP:AF:ID  -0.00117683:0.00279728:0.173925:0.036819:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838945 ES:SE:LP:AF:ID  -0.000388075:0.00141761:0.107905:0.838945:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838574 ES:SE:LP:AF:ID  -0.000249248:0.00141608:0.0655015:0.838574:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869772 ES:SE:LP:AF:ID  -0.000341717:0.00151951:0.0861861:0.869772:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12988  ES:SE:LP:AF:ID  0.000342861:0.00152261:0.0861861:0.12988:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037331 ES:SE:LP:AF:ID  -0.00126306:0.00274984:0.187087:0.037331:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037575 ES:SE:LP:AF:ID  -0.00103256:0.00273245:0.148742:0.037575:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869114 ES:SE:LP:AF:ID  -0.00015082:0.00151653:0.0362122:0.869114:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869212 ES:SE:LP:AF:ID  -0.000169977:0.00151713:0.0409586:0.869212:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037533 ES:SE:LP:AF:ID  -0.00121443:0.00274428:0.180456:0.037533:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869117 ES:SE:LP:AF:ID  -0.000173324:0.0015165:0.0409586:0.869117:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00512  ES:SE:LP:AF:ID  0.00876875:0.00778795:0.585027:0.00512:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005086 ES:SE:LP:AF:ID  0.00876668:0.00780836:0.585027:0.005086:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838026 ES:SE:LP:AF:ID  -8.46196e-05:0.00141215:0.0222764:0.838026:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037545 ES:SE:LP:AF:ID  -0.00120214:0.00274815:0.180456:0.037545:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838657 ES:SE:LP:AF:ID  -5.08315e-05:0.00141612:0.0132283:0.838657:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013776 ES:SE:LP:AF:ID  -0.00173642:0.00494255:0.136677:0.013776:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005546 ES:SE:LP:AF:ID  -0.00228476:0.00762729:0.119186:0.005546:rs184270342