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-5559/UKB-b-5559_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5559/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:26 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5559/UKB-b-5559_data.vcf.gz ...
Read summary statistics for 4826253 SNPs.
Dropped 1259 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, 1091279 SNPs remain.
After merging with regression SNP LD, 1091279 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0023 (0.0014)
Lambda GC: 1.2573
Mean Chi^2: 1.2653
Intercept: 1.2432 (0.0091)
Ratio: 0.9167 (0.0342)
Analysis finished at Thu Oct 17 14:46:15 2019
Total time elapsed: 49.47s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9022,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 1.5487e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "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": 40819,
    "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": 1091279,
    "ldsc_nsnp_merge_regression_ld": 1091279,
    "ldsc_observed_scale_h2_beta": 0.0023,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.2432,
    "ldsc_intercept_se": 0.0091,
    "ldsc_lambda_gc": 1.2573,
    "ldsc_mean_chisq": 1.2653,
    "ldsc_ratio": 0.9167
}

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 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 4825003 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 4826253 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 8.667366e+00 5.766925e+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 7.857334e+07 5.665600e+07 828.0000000 3.185649e+07 6.893388e+07 1.146440e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.500000e-06 3.006000e-04 -0.0021101 -1.922000e-04 6.000000e-07 1.938000e-04 2.852600e-03 ▁▃▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.622000e-04 5.410000e-05 0.0001998 2.161000e-04 2.431000e-04 2.973000e-04 7.586000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.628484e-01 2.972336e-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 4.628483e-01 2.972057e-01 0.0000000 1.960535e-01 4.490027e-01 7.202013e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.591139e-01 2.347294e-01 0.0735300 1.565520e-01 2.966460e-01 5.250130e-01 9.264700e-01 ▇▅▃▂▂
numeric AF_reference 40819 0.9915423 NA NA NA NA NA NA NA 3.517750e-01 2.324677e-01 0.0000000 1.599440e-01 2.979230e-01 5.139780e-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 -0.0002121 0.0003675 0.5600000 0.5637364 0.623761 0.7821490 NA
1 54676 rs2462492 C T 0.0000626 0.0003640 0.8600001 0.8634762 0.400407 NA NA
1 86028 rs114608975 T C -0.0006429 0.0005821 0.2700001 0.2693843 0.103553 0.0277556 NA
1 91536 rs6702460 G T 0.0000101 0.0003584 0.9800000 0.9775091 0.456863 0.4207270 NA
1 234313 rs8179466 C T 0.0001809 0.0007068 0.8000000 0.7980101 0.074508 NA NA
1 534192 rs6680723 C T 0.0003185 0.0004094 0.4400003 0.4366978 0.240956 NA NA
1 546697 rs12025928 A G -0.0006925 0.0005108 0.1800002 0.1751710 0.913475 NA NA
1 693731 rs12238997 A G -0.0005626 0.0003431 0.1000000 0.1010445 0.116333 0.1417730 NA
1 706368 rs55727773 A G 0.0001815 0.0002542 0.4799997 0.4750530 0.515654 0.2751600 NA
1 722670 rs116030099 T C 0.0002191 0.0004193 0.5999997 0.6012638 0.101209 0.0413339 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51210289 rs112565862 C T -0.0002343 0.0003378 0.4899999 0.4880158 0.129957 0.1018370 NA
22 51211106 rs9628250 T C -0.0001494 0.0002516 0.5500004 0.5525882 0.271540 0.1671330 NA
22 51211392 rs3888396 T C -0.0002165 0.0003348 0.5199996 0.5178642 0.132637 0.1641370 NA
22 51212875 rs2238837 A C 0.0001147 0.0002390 0.6300007 0.6313516 0.331477 0.3724040 NA
22 51213613 rs34726907 C T 0.0001387 0.0003149 0.6600001 0.6597047 0.127819 0.1727240 NA
22 51216564 rs9616970 T C 0.0001017 0.0003136 0.7499995 0.7457820 0.128334 0.1563500 NA
22 51218377 rs2519461 G C 0.0006219 0.0003976 0.1199999 0.1177990 0.073622 0.0826677 NA
22 51219006 rs28729663 G A 0.0000439 0.0003069 0.8900000 0.8862929 0.137954 0.2052720 NA
22 51219387 rs9616832 T C 0.0006641 0.0003984 0.0959997 0.0955283 0.073746 0.0654952 NA
22 51237063 rs3896457 T C -0.0001117 0.0002447 0.6499995 0.6480626 0.297981 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623761 ES:SE:LP:AF:ID  -0.000212132:0.000367455:0.251812:0.623761:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400407 ES:SE:LP:AF:ID  6.25982e-05:0.000364047:0.0655015:0.400407:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103553 ES:SE:LP:AF:ID  -0.00064288:0.000582065:0.568636:0.103553:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456863 ES:SE:LP:AF:ID  1.01054e-05:0.00035845:0.00877392:0.456863:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074508 ES:SE:LP:AF:ID  0.000180875:0.000706755:0.09691:0.074508:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240956 ES:SE:LP:AF:ID  0.000318451:0.000409435:0.356547:0.240956:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913475 ES:SE:LP:AF:ID  -0.000692516:0.00051079:0.744727:0.913475:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116333 ES:SE:LP:AF:ID  -0.000562647:0.000343117:1:0.116333:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.515654 ES:SE:LP:AF:ID  0.000181544:0.000254163:0.318759:0.515654:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101209 ES:SE:LP:AF:ID  0.000219143:0.000419345:0.221849:0.101209:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.84321  ES:SE:LP:AF:ID  0.000427096:0.000297357:0.823909:0.84321:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.122316 ES:SE:LP:AF:ID  -0.000587657:0.000325479:1.14874:0.122316:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.12156  ES:SE:LP:AF:ID  -0.000576047:0.000325615:1.11351:0.12156:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132333 ES:SE:LP:AF:ID  -0.000310979:0.000320922:0.481486:0.132333:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.83895  ES:SE:LP:AF:ID  0.000464794:0.000287969:0.958607:0.83895:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838579 ES:SE:LP:AF:ID  0.000466921:0.000287659:1:0.838579:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869772 ES:SE:LP:AF:ID  0.000554579:0.000308666:1.14267:0.869772:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129881 ES:SE:LP:AF:ID  -0.000591576:0.000309297:1.25181:0.129881:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869113 ES:SE:LP:AF:ID  0.000559695:0.00030806:1.16115:0.869113:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869212 ES:SE:LP:AF:ID  0.000558761:0.000308183:1.1549:0.869212:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869117 ES:SE:LP:AF:ID  0.000558922:0.000308055:1.1549:0.869117:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838031 ES:SE:LP:AF:ID  0.000480763:0.000286861:1.02687:0.838031:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838662 ES:SE:LP:AF:ID  0.000489365:0.000287667:1.05061:0.838662:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839774 ES:SE:LP:AF:ID  0.000476538:0.000291556:1:0.839774:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869397 ES:SE:LP:AF:ID  0.000550241:0.000307699:1.13077:0.869397:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868943 ES:SE:LP:AF:ID  0.000558582:0.000306924:1.16115:0.868943:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867896 ES:SE:LP:AF:ID  0.000555107:0.000306336:1.1549:0.867896:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869087 ES:SE:LP:AF:ID  0.000551982:0.000307176:1.14267:0.869087:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869095 ES:SE:LP:AF:ID  0.000551827:0.000307199:1.14267:0.869095:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869103 ES:SE:LP:AF:ID  0.000552057:0.000307206:1.14267:0.869103:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869581 ES:SE:LP:AF:ID  0.000549773:0.00030805:1.13077:0.869581:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838311 ES:SE:LP:AF:ID  0.000512792:0.000286317:1.13668:0.838311:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838432 ES:SE:LP:AF:ID  0.000510454:0.000286519:1.12494:0.838432:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862253 ES:SE:LP:AF:ID  0.000589179:0.000306094:1.26761:0.862253:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706732 ES:SE:LP:AF:ID  0.000452541:0.000297988:0.886057:0.706732:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.10515  ES:SE:LP:AF:ID  -0.000352209:0.000343261:0.522879:0.10515:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761319 ES:SE:LP:AF:ID  0.000319991:0.000243215:0.721246:0.761319:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106464 ES:SE:LP:AF:ID  9.76593e-05:0.000335252:0.113509:0.106464:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129586 ES:SE:LP:AF:ID  -0.00063885:0.000309112:1.40894:0.129586:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868902 ES:SE:LP:AF:ID  0.000580675:0.000307462:1.22915:0.868902:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129685 ES:SE:LP:AF:ID  -0.00063667:0.000308914:1.40894:0.129685:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868911 ES:SE:LP:AF:ID  0.000579273:0.000307467:1.22185:0.868911:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.26539  ES:SE:LP:AF:ID  -0.000344802:0.000271669:0.69897:0.26539:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870036 ES:SE:LP:AF:ID  0.000660482:0.000308095:1.49485:0.870036:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095131 ES:SE:LP:AF:ID  -3.28329e-05:0.000357102:0.0315171:0.095131:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128584 ES:SE:LP:AF:ID  -0.000725207:0.000309312:1.72125:0.128584:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128881 ES:SE:LP:AF:ID  -0.000709838:0.000308786:1.65758:0.128881:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868776 ES:SE:LP:AF:ID  0.00064891:0.000307273:1.45593:0.868776:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.101877 ES:SE:LP:AF:ID  -0.000453642:0.00034816:0.721246:0.101877:rs61768199
1   782981  rs6594026   C   T   .   PASS    AF=0.129522 ES:SE:LP:AF:ID  -0.000685317:0.000308687:1.58503:0.129522:rs6594026