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-11542/UKB-b-11542_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11542/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:50 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11542/UKB-b-11542_data.vcf.gz ...
Read summary statistics for 5604760 SNPs.
Dropped 2168 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, 1183380 SNPs remain.
After merging with regression SNP LD, 1183380 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.029 (0.0152)
Lambda GC: 1.025
Mean Chi^2: 1.021
Intercept: 1.0027 (0.0068)
Ratio: 0.1286 (0.3244)
Analysis finished at Thu Oct 17 14:41:55 2019
Total time elapsed: 1.0m:5.24s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9189,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 2.6156e-06,
    "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": 49484,
    "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": 1183380,
    "ldsc_nsnp_merge_regression_ld": 1183380,
    "ldsc_observed_scale_h2_beta": 0.029,
    "ldsc_observed_scale_h2_se": 0.0152,
    "ldsc_intercept_beta": 1.0027,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 1.025,
    "ldsc_mean_chisq": 1.021,
    "ldsc_ratio": 0.1286
}

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 5602608 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 5604760 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 8.672162e+00 5.763256e+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 7.858730e+07 5.656679e+07 828.0000000 3.197629e+07 6.901775e+07 1.145287e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.600000e-06 5.068400e-03 -0.0374686 -3.115200e-03 1.200000e-06 3.121200e-03 3.704930e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.825500e-03 1.389900e-03 0.0033325 3.668200e-03 4.301900e-03 5.660000e-03 1.597760e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.958248e-01 2.895461e-01 0.0000017 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 4.958235e-01 2.895223e-01 0.0000017 2.440800e-01 4.939613e-01 7.459307e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.271948e-01 2.485092e-01 0.0444340 1.151310e-01 2.514435e-01 4.938700e-01 9.555660e-01 ▇▃▂▂▁
numeric AF_reference 49484 0.9911711 NA NA NA NA NA NA NA 3.226860e-01 2.427540e-01 0.0000000 1.230030e-01 2.571880e-01 4.838260e-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 0.0110132 0.0061492 0.0729995 0.0732937 0.623710 0.7821490 NA
1 54676 rs2462492 C T -0.0029256 0.0061197 0.6300007 0.6326102 0.399162 NA NA
1 86028 rs114608975 T C -0.0065394 0.0096837 0.5000000 0.4994864 0.103756 0.0277556 NA
1 91536 rs6702460 G T 0.0007644 0.0060173 0.9000000 0.8989087 0.455304 0.4207270 NA
1 234313 rs8179466 C T -0.0174518 0.0119617 0.1400000 0.1445725 0.073691 NA NA
1 534192 rs6680723 C T -0.0043991 0.0069004 0.5199996 0.5237860 0.240720 NA NA
1 546697 rs12025928 A G -0.0145256 0.0085310 0.0890000 0.0886253 0.912539 NA NA
1 693731 rs12238997 A G -0.0041073 0.0057326 0.4700002 0.4736877 0.118189 0.1417730 NA
1 705882 rs72631875 G A 0.0087760 0.0083764 0.2900000 0.2947788 0.068040 0.0315495 NA
1 706368 rs55727773 A G -0.0028529 0.0042572 0.5000000 0.5027765 0.513640 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218224 rs9616975 C A 0.0077952 0.0066841 0.2399999 0.2435179 0.072874 0.0619010 NA
22 51218377 rs2519461 G C 0.0077965 0.0066686 0.2399999 0.2423520 0.073259 0.0826677 NA
22 51219006 rs28729663 G A 0.0083552 0.0051416 0.1000000 0.1041617 0.138957 0.2052720 NA
22 51219387 rs9616832 T C 0.0080566 0.0066874 0.2300001 0.2283043 0.073345 0.0654952 NA
22 51221190 rs369304721 G A 0.0071459 0.0089689 0.4299995 0.4256007 0.049369 NA NA
22 51221731 rs115055839 T C 0.0076755 0.0066938 0.2500000 0.2515230 0.072770 0.0625000 NA
22 51222100 rs114553188 G T 0.0105076 0.0078109 0.1800002 0.1785451 0.055203 0.0880591 NA
22 51223637 rs375798137 G A 0.0098790 0.0078491 0.2099999 0.2081726 0.054822 0.0788738 NA
22 51229805 rs9616985 T C 0.0079146 0.0067214 0.2399999 0.2389860 0.072555 0.0730831 NA
22 51237063 rs3896457 T C -0.0050340 0.0041243 0.2200002 0.2222469 0.295451 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.62371  ES:SE:LP:AF:ID  0.0110132:0.0061492:1.13668:0.62371:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399162 ES:SE:LP:AF:ID  -0.00292557:0.00611972:0.200659:0.399162:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103756 ES:SE:LP:AF:ID  -0.00653937:0.00968368:0.30103:0.103756:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455304 ES:SE:LP:AF:ID  0.000764441:0.00601732:0.0457575:0.455304:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.073691 ES:SE:LP:AF:ID  -0.0174518:0.0119617:0.853872:0.073691:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24072  ES:SE:LP:AF:ID  -0.00439912:0.00690036:0.283997:0.24072:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912539 ES:SE:LP:AF:ID  -0.0145256:0.00853095:1.05061:0.912539:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.118189 ES:SE:LP:AF:ID  -0.00410734:0.00573257:0.327902:0.118189:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06804  ES:SE:LP:AF:ID  0.00877596:0.00837644:0.537602:0.06804:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51364  ES:SE:LP:AF:ID  -0.00285286:0.00425719:0.30103:0.51364:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.100278 ES:SE:LP:AF:ID  0.00551476:0.00705161:0.366532:0.100278:rs116030099
1   725060  rs865924913 A   T   .   PASS    AF=0.052547 ES:SE:LP:AF:ID  0.00204907:0.0135818:0.0555173:0.052547:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.840353 ES:SE:LP:AF:ID  0.00798924:0.00495499:0.958607:0.840353:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056243 ES:SE:LP:AF:ID  -0.00227786:0.00808351:0.107905:0.056243:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.124107 ES:SE:LP:AF:ID  -0.00617417:0.00544776:0.585027:0.124107:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.123373 ES:SE:LP:AF:ID  -0.00620645:0.00545001:0.60206:0.123373:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134053 ES:SE:LP:AF:ID  -0.0093069:0.00537529:1.08092:0.134053:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.835828 ES:SE:LP:AF:ID  0.00701806:0.0048112:0.853872:0.835828:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.835345 ES:SE:LP:AF:ID  0.00673852:0.00480263:0.79588:0.835345:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.866915 ES:SE:LP:AF:ID  0.0042408:0.00514799:0.387216:0.866915:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.132666 ES:SE:LP:AF:ID  -0.00380909:0.00516115:0.337242:0.132666:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.866153 ES:SE:LP:AF:ID  0.00402456:0.00513481:0.366532:0.866153:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.866318 ES:SE:LP:AF:ID  0.00399637:0.0051376:0.356547:0.866318:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86615  ES:SE:LP:AF:ID  0.00403478:0.00513434:0.366532:0.86615:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.834923 ES:SE:LP:AF:ID  0.00647878:0.00479488:0.744727:0.834923:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.835586 ES:SE:LP:AF:ID  0.00660225:0.00480939:0.769551:0.835586:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.836772 ES:SE:LP:AF:ID  0.00613566:0.00487182:0.677781:0.836772:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.866643 ES:SE:LP:AF:ID  0.00427428:0.0051326:0.39794:0.866643:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.866271 ES:SE:LP:AF:ID  0.00440305:0.0051202:0.408935:0.866271:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.864793 ES:SE:LP:AF:ID  0.00342117:0.00510305:0.30103:0.864793:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.866378 ES:SE:LP:AF:ID  0.00443423:0.00512478:0.408935:0.866378:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.866402 ES:SE:LP:AF:ID  0.00440364:0.00512511:0.408935:0.866402:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.866407 ES:SE:LP:AF:ID  0.00440794:0.00512523:0.408935:0.866407:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86679  ES:SE:LP:AF:ID  0.00420208:0.00513854:0.387216:0.86679:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.835422 ES:SE:LP:AF:ID  0.00656565:0.00478837:0.769551:0.835422:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.835566 ES:SE:LP:AF:ID  0.00652885:0.00479188:0.769551:0.835566:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.859182 ES:SE:LP:AF:ID  0.00434074:0.00510168:0.408935:0.859182:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.705081 ES:SE:LP:AF:ID  0.00384552:0.00497551:0.356547:0.705081:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.106752 ES:SE:LP:AF:ID  -0.00668309:0.00574722:0.619789:0.106752:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.756826 ES:SE:LP:AF:ID  0.00238378:0.00405221:0.251812:0.756826:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.108264 ES:SE:LP:AF:ID  -0.000349387:0.00555189:0.0222764:0.108264:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.131879 ES:SE:LP:AF:ID  -0.0037282:0.00516828:0.327902:0.131879:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.866392 ES:SE:LP:AF:ID  0.00398625:0.00513195:0.356547:0.866392:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.131995 ES:SE:LP:AF:ID  -0.00358684:0.00516346:0.309804:0.131995:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.866394 ES:SE:LP:AF:ID  0.00383078:0.00513179:0.337242:0.866394:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.264497 ES:SE:LP:AF:ID  -0.00233144:0.00457774:0.21467:0.264497:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.868007 ES:SE:LP:AF:ID  0.00337272:0.00514941:0.29243:0.868007:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.096795 ES:SE:LP:AF:ID  -0.000496958:0.00592622:0.0315171:0.096795:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.130462 ES:SE:LP:AF:ID  -0.00276968:0.00517518:0.229148:0.130462:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.130808 ES:SE:LP:AF:ID  -0.00261955:0.00516506:0.21467:0.130808:rs4040617