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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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_6156_13.vcf.gz --id UKB-b:11588 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_6156_13.txt.gz --cohort_cases 4245 --cohort_controls 27072 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
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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-11588/UKB-b-11588_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11588/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:53 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11588/UKB-b-11588_data.vcf.gz ...
Read summary statistics for 4640847 SNPs.
Dropped 1128 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, 1063321 SNPs remain.
After merging with regression SNP LD, 1063321 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0148 (0.0165)
Lambda GC: 1.0162
Mean Chi^2: 1.0199
Intercept: 1.0098 (0.0073)
Ratio: 0.495 (0.3701)
Analysis finished at Thu Oct 17 14:41:50 2019
Total time elapsed: 56.5s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8977,
    "inflation_factor": 1,
    "mean_EFFECT": 7.542e-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": 38863,
    "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": 1063321,
    "ldsc_nsnp_merge_regression_ld": 1063321,
    "ldsc_observed_scale_h2_beta": 0.0148,
    "ldsc_observed_scale_h2_se": 0.0165,
    "ldsc_intercept_beta": 1.0098,
    "ldsc_intercept_se": 0.0073,
    "ldsc_lambda_gc": 1.0162,
    "ldsc_mean_chisq": 1.0199,
    "ldsc_ratio": 0.4925
}

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 4639728 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 4640847 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 8.663515e+00 5.766431e+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 7.857028e+07 5.671118e+07 828.0000000 3.177929e+07 6.888472e+07 1.146931e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 7.500000e-06 3.483800e-03 -0.0238127 -2.246600e-03 1.070000e-05 2.251400e-03 2.343110e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.395900e-03 6.414000e-04 0.0026294 2.846900e-03 3.174100e-03 3.818200e-03 9.613100e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.971912e-01 2.894246e-01 0.0000003 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 4.971905e-01 2.893976e-01 0.0000003 2.460678e-01 4.968444e-01 7.473826e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.670212e-01 2.304222e-01 0.0824500 1.676560e-01 3.077670e-01 5.314555e-01 9.175500e-01 ▇▅▃▂▂
numeric AF_reference 38863 0.9916259 NA NA NA NA NA NA NA 3.589929e-01 2.293008e-01 0.0000000 1.699280e-01 3.081070e-01 5.203670e-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 0.0019320 0.0048518 0.6899999 0.6904856 0.623710 0.7821490 NA
1 54676 rs2462492 C T -0.0019548 0.0048285 0.6899999 0.6855927 0.399162 NA NA
1 86028 rs114608975 T C 0.0006658 0.0076405 0.9299999 0.9305603 0.103756 0.0277556 NA
1 91536 rs6702460 G T 0.0000924 0.0047477 0.9800000 0.9844758 0.455304 0.4207270 NA
1 534192 rs6680723 C T -0.0053049 0.0054444 0.3300000 0.3298709 0.240720 NA NA
1 546697 rs12025928 A G -0.0022316 0.0067310 0.7400005 0.7402395 0.912539 NA NA
1 693731 rs12238997 A G -0.0036957 0.0045230 0.4100001 0.4138807 0.118189 0.1417730 NA
1 706368 rs55727773 A G 0.0021378 0.0033590 0.5199996 0.5244851 0.513640 0.2751600 NA
1 722670 rs116030099 T C -0.0055993 0.0055638 0.3100002 0.3142282 0.100278 0.0413339 NA
1 729679 rs4951859 C G 0.0003602 0.0039095 0.9299999 0.9265974 0.840353 0.6399760 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51198027 rs34939255 A G 0.0035550 0.0033374 0.2900000 0.2867979 0.257301 0.0984425 NA
22 51208537 rs72619593 G A 0.0066136 0.0044974 0.1400000 0.1414183 0.120551 0.1142170 NA
22 51210289 rs112565862 C T 0.0022166 0.0045378 0.6300007 0.6252160 0.126382 0.1018370 NA
22 51211106 rs9628250 T C 0.0040278 0.0033134 0.2200002 0.2241259 0.274349 0.1671330 NA
22 51211392 rs3888396 T C 0.0019485 0.0044965 0.6600001 0.6647623 0.128916 0.1641370 NA
22 51212875 rs2238837 A C -0.0014198 0.0031833 0.6600001 0.6555825 0.328738 0.3724040 NA
22 51213613 rs34726907 C T 0.0008906 0.0041641 0.8300000 0.8306413 0.128115 0.1727240 NA
22 51216564 rs9616970 T C 0.0005321 0.0041484 0.9000000 0.8979282 0.128577 0.1563500 NA
22 51219006 rs28729663 G A 0.0012360 0.0040568 0.7600007 0.7606155 0.138957 0.2052720 NA
22 51237063 rs3896457 T C -0.0003058 0.0032541 0.9299999 0.9251275 0.295451 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.62371  ES:SE:LP:AF:ID  0.00193196:0.00485178:0.161151:0.62371:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399162 ES:SE:LP:AF:ID  -0.00195479:0.00482851:0.161151:0.399162:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103756 ES:SE:LP:AF:ID  0.000665794:0.00764052:0.0315171:0.103756:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455304 ES:SE:LP:AF:ID  9.23809e-05:0.00474772:0.00877392:0.455304:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.24072  ES:SE:LP:AF:ID  -0.00530493:0.00544445:0.481486:0.24072:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912539 ES:SE:LP:AF:ID  -0.00223157:0.006731:0.130768:0.912539:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.118189 ES:SE:LP:AF:ID  -0.00369571:0.00452305:0.387216:0.118189:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.51364  ES:SE:LP:AF:ID  0.0021378:0.00335896:0.283997:0.51364:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.100278 ES:SE:LP:AF:ID  -0.00559934:0.00556379:0.508638:0.100278:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.840353 ES:SE:LP:AF:ID  0.000360172:0.00390953:0.0315171:0.840353:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.124107 ES:SE:LP:AF:ID  -0.00390555:0.00429833:0.443698:0.124107:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.123373 ES:SE:LP:AF:ID  -0.0041536:0.00430011:0.481486:0.123373:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134053 ES:SE:LP:AF:ID  0.000272772:0.00424116:0.0222764:0.134053:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.835828 ES:SE:LP:AF:ID  0.00173994:0.00379608:0.187087:0.835828:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.835345 ES:SE:LP:AF:ID  0.0014419:0.00378932:0.154902:0.835345:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.866915 ES:SE:LP:AF:ID  0.00516971:0.00406182:0.69897:0.866915:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.132666 ES:SE:LP:AF:ID  -0.00452498:0.00407219:0.568636:0.132666:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.866153 ES:SE:LP:AF:ID  0.00475768:0.00405141:0.619789:0.866153:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.866318 ES:SE:LP:AF:ID  0.00471123:0.00405362:0.60206:0.866318:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86615  ES:SE:LP:AF:ID  0.00463105:0.00405104:0.60206:0.86615:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.834923 ES:SE:LP:AF:ID  0.00126258:0.0037832:0.130768:0.834923:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.835586 ES:SE:LP:AF:ID  0.00123841:0.00379465:0.130768:0.835586:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.836772 ES:SE:LP:AF:ID  0.00133517:0.00384392:0.136677:0.836772:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.866643 ES:SE:LP:AF:ID  0.00509745:0.00404967:0.677781:0.866643:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.866271 ES:SE:LP:AF:ID  0.00532472:0.00403989:0.721246:0.866271:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.864793 ES:SE:LP:AF:ID  0.00454679:0.00402635:0.585027:0.864793:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.866378 ES:SE:LP:AF:ID  0.005201:0.0040435:0.69897:0.866378:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.866402 ES:SE:LP:AF:ID  0.00519067:0.00404376:0.69897:0.866402:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.866407 ES:SE:LP:AF:ID  0.00518645:0.00404385:0.69897:0.866407:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86679  ES:SE:LP:AF:ID  0.00506288:0.00405436:0.677781:0.86679:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.835422 ES:SE:LP:AF:ID  0.00114271:0.00377807:0.119186:0.835422:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.835566 ES:SE:LP:AF:ID  0.00107684:0.00378084:0.107905:0.835566:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.859182 ES:SE:LP:AF:ID  0.00389024:0.00402527:0.481486:0.859182:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.705081 ES:SE:LP:AF:ID  0.00247138:0.00392573:0.275724:0.705081:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.106752 ES:SE:LP:AF:ID  -0.00356979:0.00453461:0.366532:0.106752:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.756826 ES:SE:LP:AF:ID  0.00146978:0.00319723:0.187087:0.756826:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.108264 ES:SE:LP:AF:ID  0.0032227:0.00438049:0.337242:0.108264:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.131879 ES:SE:LP:AF:ID  -0.00505035:0.00407782:0.657577:0.131879:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.866392 ES:SE:LP:AF:ID  0.00515689:0.00404916:0.69897:0.866392:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.131995 ES:SE:LP:AF:ID  -0.0047415:0.00407402:0.619789:0.131995:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.866394 ES:SE:LP:AF:ID  0.00516772:0.00404903:0.69897:0.866394:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.264497 ES:SE:LP:AF:ID  0.00317565:0.00361188:0.420216:0.264497:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.868007 ES:SE:LP:AF:ID  0.00495178:0.00406293:0.657577:0.868007:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.096795 ES:SE:LP:AF:ID  0.00574694:0.00467585:0.657577:0.096795:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.130462 ES:SE:LP:AF:ID  -0.00407734:0.00408326:0.49485:0.130462:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.130808 ES:SE:LP:AF:ID  -0.00401966:0.00407529:0.49485:0.130808:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.866654 ES:SE:LP:AF:ID  0.00446825:0.00404866:0.568636:0.866654:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.102937 ES:SE:LP:AF:ID  -0.00269442:0.00460713:0.251812:0.102937:rs61768199
1   782981  rs6594026   C   T   .   PASS    AF=0.131418 ES:SE:LP:AF:ID  -0.00383823:0.00407222:0.455932:0.131418:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.866227 ES:SE:LP:AF:ID  0.00403026:0.00404405:0.49485:0.866227:rs2905062