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-20554_6/ukb-d-20554_6.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-20554_6/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 16:50:56 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20554_6/ukb-d-20554_6.vcf.gz ...
Read summary statistics for 9914392 SNPs.
Dropped 7620 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, 1277462 SNPs remain.
After merging with regression SNP LD, 1277462 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 1.7154e-05 (0.0035)
Lambda GC: 1.0064
Mean Chi^2: 1.0174
Intercept: 1.0174 (0.0064)
Ratio: 0.9976 (0.3654)
Analysis finished at Mon Nov 25 16:52:38 2019
Total time elapsed: 1.0m:41.96s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9412,
    "inflation_factor": 1.0048,
    "mean_EFFECT": 5.4749e-07,
    "n": 117733,
    "n_snps": 9914392,
    "n_clumped_hits": 1,
    "n_p_sig": 2,
    "n_mono": 0,
    "n_ns": 1077517,
    "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": 196367,
    "n_est": 117715.3426,
    "ratio_se_n": 0.9999,
    "mean_diff": 4.8036e-06,
    "ratio_diff": 11.9538,
    "sd_y_est1": 0.1106,
    "sd_y_est2": 0.1106,
    "r2_sum1": 4.3758e-06,
    "r2_sum2": 0.0004,
    "r2_sum3": 0.0004,
    "r2_sum4": 0.0003,
    "ldsc_nsnp_merge_refpanel_ld": 1277462,
    "ldsc_nsnp_merge_regression_ld": 1277462,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0174,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.0064,
    "ldsc_mean_chisq": 1.0174,
    "ldsc_ratio": 1
}

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 9907322 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 98 0 47892 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 30009 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.080516e+00 6.176923e+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 7.875312e+07 5.609493e+07 3.02000e+02 3.246164e+07 6.965466e+07 1.147365e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 5.000000e-07 1.084400e-03 -1.13034e-02 -5.098000e-04 -7.200000e-06 4.947000e-04 1.264730e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.265000e-04 5.533000e-04 3.77800e-04 5.013000e-04 6.787000e-04 1.195500e-03 3.069700e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.986871e-01 2.894868e-01 0.00000e+00 2.478090e-01 4.989810e-01 7.490866e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.986857e-01 2.894876e-01 0.00000e+00 2.478071e-01 4.989798e-01 7.490854e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.565376e-01 2.629502e-01 8.60290e-03 3.999310e-02 1.522480e-01 4.089890e-01 9.913960e-01 ▇▂▂▁▁
numeric AF_reference 196367 0.9801937 NA NA NA NA NA 2.561510e-01 2.537738e-01 0.00000e+00 4.472840e-02 1.679310e-01 4.049520e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.177330e+05 0.000000e+00 1.17733e+05 1.177330e+05 1.177330e+05 1.177330e+05 1.177330e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0001638 0.0007943 0.8365791 0.8365783 0.1117700 0.1894970 117733
1 693731 rs12238997 A G 0.0007157 0.0007522 0.3414027 0.3414016 0.1167970 0.1417730 117733
1 707522 rs371890604 G C 0.0002688 0.0008439 0.7500634 0.7500622 0.0984203 0.1293930 117733
1 717587 rs144155419 G A 0.0011979 0.0020225 0.5536483 0.5536474 0.0157696 0.0045926 117733
1 730087 rs148120343 T C -0.0001342 0.0010467 0.8979710 0.8979713 0.0569438 0.0127796 117733
1 731718 rs142557973 T C 0.0006295 0.0007137 0.3778174 0.3778148 0.1227180 0.1543530 117733
1 732032 rs61770163 A C 0.0003526 0.0007607 0.6429778 0.6429781 0.1223370 0.1555510 117733
1 734349 rs141242758 T C 0.0006214 0.0007141 0.3842510 0.3842494 0.1219750 0.1525560 117733
1 749963 rs529266287 T TAA -0.0003842 0.0007036 0.5850419 0.5850412 0.8689330 0.7641770 117733
1 751343 rs28544273 T A 0.0006697 0.0006972 0.3367387 0.3367376 0.1237660 0.2426120 117733
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0003087 0.0008394 0.7130697 0.7130698 0.0554864 0.0309934 117733
23 154923374 rs111332691 T A -0.0009093 0.0009150 0.3203642 0.3203618 0.0447750 0.0116556 117733
23 154925045 rs509981 C T 0.0009868 0.0004406 0.0251004 0.0250983 0.2447700 0.3634440 117733
23 154925895 rs538470 C T 0.0010101 0.0004505 0.0249454 0.0249443 0.2412000 0.3634440 117733
23 154927581 rs644138 G A 0.0008036 0.0004145 0.0525569 0.0525548 0.3006190 0.4635760 117733
23 154929412 rs557132 C T 0.0010039 0.0004407 0.0227243 0.0227224 0.2446450 0.3568210 117733
23 154929637 rs35185538 CT C 0.0008919 0.0004604 0.0526987 0.0526964 0.2288480 0.3011920 117733
23 154929952 rs4012982 CAA C 0.0010078 0.0004638 0.0297886 0.0297868 0.2387180 0.3165560 117733
23 154930230 rs781880 A G 0.0009784 0.0004405 0.0263572 0.0263552 0.2450680 0.3618540 117733
23 154930487 rs781879 T A 0.0025771 0.0014974 0.0852334 0.0852301 0.0196901 0.1263580 117733

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11177  ES:SE:LP:AF:SS:ID   0.000163841:0.000794295:0.077493:0.11177:117733:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116797 ES:SE:LP:AF:SS:ID   0.000715678:0.000752237:0.466733:0.116797:117733:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0984203    ES:SE:LP:AF:SS:ID   0.000268842:0.000843936:0.124902:0.0984203:117733:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157696    ES:SE:LP:AF:SS:ID   0.00119791:0.00202246:0.256766:0.0157696:117733:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569438    ES:SE:LP:AF:SS:ID   -0.00013421:0.00104668:0.0467377:0.0569438:117733:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122718 ES:SE:LP:AF:SS:ID   0.000629472:0.000713744:0.422718:0.122718:117733:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122337 ES:SE:LP:AF:SS:ID   0.000352596:0.000760661:0.191804:0.122337:117733:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121975 ES:SE:LP:AF:SS:ID   0.000621351:0.00071412:0.415385:0.121975:117733:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.868933 ES:SE:LP:AF:SS:ID   -0.00038421:0.000703635:0.232813:0.868933:117733:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123766 ES:SE:LP:AF:SS:ID   0.000669708:0.000697154:0.472707:0.123766:117733:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.1434   ES:SE:LP:AF:SS:ID   0.000727802:0.000689511:0.535834:0.1434:117733:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123888 ES:SE:LP:AF:SS:ID   0.000692614:0.000696188:0.495117:0.123888:117733:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869714 ES:SE:LP:AF:SS:ID   -0.000675969:0.000678029:0.496502:0.869714:117733:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874485 ES:SE:LP:AF:SS:ID   -0.000953419:0.000689387:0.778145:0.874485:117733:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129745 ES:SE:LP:AF:SS:ID   0.000620221:0.000679928:0.441685:0.129745:117733:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365403    ES:SE:LP:AF:SS:ID   -0.00151756:0.00123487:0.659352:0.0365403:117733:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869307 ES:SE:LP:AF:SS:ID   -0.000714734:0.000677384:0.535564:0.869307:117733:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869378 ES:SE:LP:AF:SS:ID   -0.000721567:0.000677635:0.542186:0.869378:117733:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869306 ES:SE:LP:AF:SS:ID   -0.000715258:0.000677366:0.53611:0.869306:117733:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.86938  ES:SE:LP:AF:SS:ID   -0.000671275:0.000676119:0.493776:0.86938:117733:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127028 ES:SE:LP:AF:SS:ID   0.00055592:0.000690142:0.376209:0.127028:117733:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868903 ES:SE:LP:AF:SS:ID   -0.000667236:0.000674346:0.491548:0.868903:117733:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868299 ES:SE:LP:AF:SS:ID   -0.00080489:0.000674082:0.633652:0.868299:117733:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869089 ES:SE:LP:AF:SS:ID   -0.000688835:0.000675011:0.512151:0.869089:117733:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869096 ES:SE:LP:AF:SS:ID   -0.000689124:0.000675059:0.512388:0.869096:117733:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869098 ES:SE:LP:AF:SS:ID   -0.000687143:0.000675062:0.510421:0.869098:117733:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869534 ES:SE:LP:AF:SS:ID   -0.000689826:0.000676792:0.511334:0.869534:117733:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0996366    ES:SE:LP:AF:SS:ID   0.000137497:0.000786714:0.0648667:0.0996366:117733:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.873583 ES:SE:LP:AF:SS:ID   -0.000837195:0.00068713:0.651545:0.873583:117733:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862878 ES:SE:LP:AF:SS:ID   -0.000738679:0.000673909:0.563785:0.862878:117733:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868273 ES:SE:LP:AF:SS:ID   -0.000625851:0.00068038:0.446542:0.868273:117733:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865286 ES:SE:LP:AF:SS:ID   -0.000639836:0.000680472:0.459577:0.865286:117733:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0998136    ES:SE:LP:AF:SS:ID   0.000760724:0.000813138:0.456539:0.0998136:117733:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870572 ES:SE:LP:AF:SS:ID   -0.000766328:0.000688494:0.575625:0.870572:117733:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870572 ES:SE:LP:AF:SS:ID   -0.000766324:0.000688494:0.575622:0.870572:117733:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870571 ES:SE:LP:AF:SS:ID   -0.000766628:0.000688495:0.575931:0.870571:117733:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870892 ES:SE:LP:AF:SS:ID   -0.000795012:0.000688786:0.604827:0.870892:117733:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126623 ES:SE:LP:AF:SS:ID   0.00068085:0.00068938:0.490345:0.126623:117733:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106376 ES:SE:LP:AF:SS:ID   0.000220012:0.00074924:0.114058:0.106376:117733:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854328 ES:SE:LP:AF:SS:ID   -0.00069145:0.000673742:0.516042:0.854328:117733:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839072 ES:SE:LP:AF:SS:ID   -0.000726385:0.000667673:0.558107:0.839072:117733:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.762955 ES:SE:LP:AF:SS:ID   -0.000571283:0.000535114:0.544079:0.762955:117733:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105259 ES:SE:LP:AF:SS:ID   8.1529e-05:0.000740332:0.0398571:0.105259:117733:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.130028 ES:SE:LP:AF:SS:ID   0.000515619:0.000679573:0.348712:0.130028:117733:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.12973  ES:SE:LP:AF:SS:ID   0.000592277:0.000678753:0.416931:0.12973:117733:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104502 ES:SE:LP:AF:SS:ID   0.000116809:0.000746141:0.0576947:0.104502:117733:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.00918492   ES:SE:LP:AF:SS:ID   0.000935196:0.00260799:0.142726:0.00918492:117733:rs146076599
1   770886  rs371458725 G   A   .   PASS    AF=0.103549 ES:SE:LP:AF:SS:ID   4.89663e-05:0.000752356:0.0231426:0.103549:117733:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.82917  ES:SE:LP:AF:SS:ID   -0.000539337:0.000662198:0.381553:0.82917:117733:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.868945 ES:SE:LP:AF:SS:ID   -0.000704995:0.000675583:0.52768:0.868945:117733:rs2977605