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/dev/ukb-d-import/processed/ukb-d-100920_2105/ukb-d-100920_2105.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-100920_2105/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Mon Nov 25 14:59:54 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-100920_2105/ukb-d-100920_2105.vcf.gz ...
Read summary statistics for 10020307 SNPs.
Dropped 7758 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1278346 SNPs remain.
After merging with regression SNP LD, 1278346 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0003 (0.0077)
Lambda GC: 1.0215
Mean Chi^2: 1.0078
Intercept: 1.0081 (0.006)
Ratio: 1.0329 (0.7692)
Analysis finished at Mon Nov 25 15:01:36 2019
Total time elapsed: 1.0m:41.84s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9418,
    "inflation_factor": 1.0158,
    "mean_EFFECT": 4.0072e-06,
    "n": 51427,
    "n_snps": 10020307,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1084092,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 197970,
    "n_est": 51472.2243,
    "ratio_se_n": 1.0004,
    "mean_diff": 0,
    "ratio_diff": 76.331,
    "sd_y_est1": 0.1709,
    "sd_y_est2": 0.171,
    "r2_sum1": 0,
    "r2_sum2": 0.0006,
    "r2_sum3": 0.0006,
    "r2_sum4": 0.0006,
    "ldsc_nsnp_merge_refpanel_ld": 1278346,
    "ldsc_nsnp_merge_regression_ld": 1278346,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0081,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0215,
    "ldsc_mean_chisq": 1.0078,
    "ldsc_ratio": 1.0385
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 94 0 10013102 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 98 0 48244 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 30163 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.079477e+00 6.176881e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.876083e+07 5.608678e+07 3.02000e+02 3.248339e+07 6.966694e+07 1.147317e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.000000e-06 2.590400e-03 -2.92065e-02 -1.199600e-03 -1.090000e-05 1.179800e-03 2.792050e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.206400e-03 1.345800e-03 8.77800e-04 1.174300e-03 1.600600e-03 2.856700e-03 7.724700e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.979556e-01 2.883497e-01 0.00000e+00 2.484180e-01 4.966392e-01 7.473327e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.979525e-01 2.883516e-01 0.00000e+00 2.484123e-01 4.966363e-01 7.473317e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.541096e-01 2.629518e-01 8.08540e-03 3.813660e-02 1.486440e-01 4.054330e-01 9.919150e-01 ▇▂▂▁▁
numeric AF_reference 197970 0.9802431 NA NA NA NA NA 2.537737e-01 2.537938e-01 0.00000e+00 4.233230e-02 1.645370e-01 4.017570e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.142700e+04 0.000000e+00 5.14270e+04 5.142700e+04 5.142700e+04 5.142700e+04 5.142700e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0005461 0.0018563 0.7686241 0.7686226 0.1121000 0.1894970 51427
1 693731 rs12238997 A G -0.0002732 0.0017640 0.8769431 0.8769422 0.1168090 0.1417730 51427
1 707522 rs371890604 G C 0.0006479 0.0019784 0.7432895 0.7432876 0.0982930 0.1293930 51427
1 717587 rs144155419 G A 0.0017195 0.0047830 0.7192237 0.7192212 0.0154808 0.0045926 51427
1 730087 rs148120343 T C -0.0019819 0.0024566 0.4198034 0.4197992 0.0570822 0.0127796 51427
1 731718 rs142557973 T C -0.0000892 0.0016763 0.9575549 0.9575549 0.1225210 0.1543530 51427
1 732032 rs61770163 A C 0.0005749 0.0017869 0.7476511 0.7476493 0.1216510 0.1555510 51427
1 734349 rs141242758 T C -0.0001195 0.0016772 0.9431900 0.9431902 0.1217650 0.1525560 51427
1 749963 rs529266287 T TAA -0.0009292 0.0016511 0.5735879 0.5735868 0.8686130 0.7641770 51427
1 751343 rs28544273 T A 0.0012226 0.0016356 0.4547660 0.4547612 0.1239570 0.2426120 51427
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0017621 0.0019721 0.3715823 0.3715781 0.0542488 0.0309934 51427
23 154923374 rs111332691 T A -0.0013531 0.0021363 0.5264741 0.5264701 0.0445389 0.0116556 51427
23 154925045 rs509981 C T -0.0006355 0.0010270 0.5360447 0.5360419 0.2434190 0.3634440 51427
23 154925895 rs538470 C T -0.0006317 0.0010491 0.5470928 0.5470905 0.2401390 0.3634440 51427
23 154927581 rs644138 G A -0.0010286 0.0009660 0.2869783 0.2869750 0.2981050 0.4635760 51427
23 154929412 rs557132 C T -0.0006187 0.0010274 0.5470122 0.5470113 0.2432580 0.3568210 51427
23 154929637 rs35185538 CT C -0.0007397 0.0010704 0.4895477 0.4895461 0.2278210 0.3011920 51427
23 154929952 rs4012982 CAA C -0.0005573 0.0010809 0.6061150 0.6061119 0.2374290 0.3165560 51427
23 154930230 rs781880 A G -0.0006011 0.0010269 0.5582902 0.5582894 0.2438260 0.3618540 51427
23 154930487 rs781879 T A 0.0029122 0.0035708 0.4147534 0.4147496 0.0189843 0.1263580 51427

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.1121   ES:SE:LP:AF:SS:ID   0.000546078:0.00185629:0.114286:0.1121:51427:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116809 ES:SE:LP:AF:SS:ID   -0.000273151:0.00176401:0.0570286:0.116809:51427:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.098293 ES:SE:LP:AF:SS:ID   0.000647948:0.00197845:0.128842:0.098293:51427:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0154808    ES:SE:LP:AF:SS:ID   0.00171947:0.00478295:0.143136:0.0154808:51427:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0570822    ES:SE:LP:AF:SS:ID   -0.00198187:0.00245655:0.376954:0.0570822:51427:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122521 ES:SE:LP:AF:SS:ID   -8.92169e-05:0.00167631:0.0188363:0.122521:51427:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121651 ES:SE:LP:AF:SS:ID   0.000574931:0.00178694:0.126301:0.121651:51427:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121765 ES:SE:LP:AF:SS:ID   -0.00011952:0.00167722:0.0254008:0.121765:51427:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.868613 ES:SE:LP:AF:SS:ID   -0.000929184:0.00165107:0.2414:0.868613:51427:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123957 ES:SE:LP:AF:SS:ID   0.00122262:0.00163561:0.342212:0.123957:51427:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143385 ES:SE:LP:AF:SS:ID   0.000313547:0.00162278:0.0722238:0.143385:51427:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124126 ES:SE:LP:AF:SS:ID   0.00132405:0.00163289:0.379396:0.124126:51427:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869933 ES:SE:LP:AF:SS:ID   -0.000832303:0.00159141:0.221141:0.869933:51427:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874426 ES:SE:LP:AF:SS:ID   -0.00141907:0.0016167:0.420124:0.874426:51427:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129659 ES:SE:LP:AF:SS:ID   0.000559713:0.00159533:0.139239:0.129659:51427:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0369164    ES:SE:LP:AF:SS:ID   0.00620252:0.00287328:1.51034:0.0369164:51427:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869554 ES:SE:LP:AF:SS:ID   -0.00078315:0.00158993:0.205987:0.869554:51427:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869648 ES:SE:LP:AF:SS:ID   -0.000702505:0.00159075:0.181267:0.869648:51427:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86957  ES:SE:LP:AF:SS:ID   -0.000787582:0.00158992:0.207364:0.86957:51427:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.869706 ES:SE:LP:AF:SS:ID   -0.000832208:0.00158753:0.221755:0.869706:51427:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12702  ES:SE:LP:AF:SS:ID   0.000912625:0.0016191:0.241855:0.12702:51427:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869213 ES:SE:LP:AF:SS:ID   -0.000883813:0.00158335:0.239038:0.869213:51427:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868449 ES:SE:LP:AF:SS:ID   -0.000717864:0.00158182:0.187114:0.868449:51427:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869419 ES:SE:LP:AF:SS:ID   -0.00086853:0.0015851:0.233781:0.869419:51427:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869426 ES:SE:LP:AF:SS:ID   -0.000867839:0.0015852:0.23354:0.869426:51427:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869437 ES:SE:LP:AF:SS:ID   -0.000869963:0.00158528:0.234212:0.869437:51427:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869848 ES:SE:LP:AF:SS:ID   -0.000828991:0.00158898:0.220496:0.869848:51427:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0999077    ES:SE:LP:AF:SS:ID   1.91796e-05:0.00184268:0.00362188:0.0999077:51427:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.87358  ES:SE:LP:AF:SS:ID   -0.00122363:0.00161193:0.348927:0.87358:51427:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86295  ES:SE:LP:AF:SS:ID   -0.000989602:0.00158139:0.274528:0.86295:51427:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868667 ES:SE:LP:AF:SS:ID   -0.000890557:0.0015969:0.238774:0.868667:51427:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.8652   ES:SE:LP:AF:SS:ID   -0.000962391:0.00159619:0.262363:0.8652:51427:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0992889    ES:SE:LP:AF:SS:ID   0.0010904:0.0019157:0.244713:0.0992889:51427:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870459 ES:SE:LP:AF:SS:ID   -0.00140752:0.00161413:0.416561:0.870459:51427:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870459 ES:SE:LP:AF:SS:ID   -0.00140752:0.00161413:0.416561:0.870459:51427:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870456 ES:SE:LP:AF:SS:ID   -0.00140708:0.00161414:0.416389:0.870456:51427:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870829 ES:SE:LP:AF:SS:ID   -0.00138509:0.00161505:0.4077:0.870829:51427:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126636 ES:SE:LP:AF:SS:ID   0.0008291:0.00161686:0.216021:0.126636:51427:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106247 ES:SE:LP:AF:SS:ID   -0.000258113:0.0017608:0.0538146:0.106247:51427:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854084 ES:SE:LP:AF:SS:ID   -0.000682106:0.00158123:0.176399:0.854084:51427:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.836377 ES:SE:LP:AF:SS:ID   -0.000113471:0.00154856:0.0261395:0.836377:51427:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.76015  ES:SE:LP:AF:SS:ID   0.000225024:0.00124492:0.0672417:0.76015:51427:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.108173 ES:SE:LP:AF:SS:ID   -0.00140424:0.0017087:0.385961:0.108173:51427:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.129757 ES:SE:LP:AF:SS:ID   0.000663702:0.00159549:0.169141:0.129757:51427:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.129482 ES:SE:LP:AF:SS:ID   0.000601428:0.00159417:0.151209:0.129482:51427:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.107436 ES:SE:LP:AF:SS:ID   -0.00123951:0.00172172:0.32645:0.107436:51427:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.00955937   ES:SE:LP:AF:SS:ID   -0.00568924:0.00598342:0.466364:0.00955937:51427:rs146076599
1   770886  rs371458725 G   A   .   PASS    AF=0.106291 ES:SE:LP:AF:SS:ID   -0.00140953:0.00173758:0.379602:0.106291:51427:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.828506 ES:SE:LP:AF:SS:ID   -0.000399853:0.0015525:0.0986768:0.828506:51427:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.869399 ES:SE:LP:AF:SS:ID   -0.00087157:0.00158744:0.234346:0.869399:51427:rs2977605