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-22612_2/ukb-d-22612_2.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-22612_2/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 16:51:43 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22612_2/ukb-d-22612_2.vcf.gz ...
Read summary statistics for 9680276 SNPs.
Dropped 7294 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, 1275336 SNPs remain.
After merging with regression SNP LD, 1275336 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0167 (0.0064)
Lambda GC: 1.0235
Mean Chi^2: 1.0223
Intercept: 0.9966 (0.0065)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:53:21 2019
Total time elapsed: 1.0m:37.76s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9399,
    "inflation_factor": 1.039,
    "mean_EFFECT": 6.9544e-06,
    "n": 76334,
    "n_snps": 9680276,
    "n_clumped_hits": 2,
    "n_p_sig": 6,
    "n_mono": 0,
    "n_ns": 1062618,
    "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": 192843,
    "n_est": 76349.9773,
    "ratio_se_n": 1.0001,
    "mean_diff": 0.0001,
    "ratio_diff": 104.118,
    "sd_y_est1": 0.1208,
    "sd_y_est2": 0.1209,
    "r2_sum1": 0,
    "r2_sum2": 0.0009,
    "r2_sum3": 0.0009,
    "r2_sum4": 0.0008,
    "ldsc_nsnp_merge_refpanel_ld": 1275336,
    "ldsc_nsnp_merge_regression_ld": 1275336,
    "ldsc_observed_scale_h2_beta": 0.0167,
    "ldsc_observed_scale_h2_se": 0.0064,
    "ldsc_intercept_beta": 0.9966,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0235,
    "ldsc_mean_chisq": 1.0223,
    "ldsc_ratio": -0.1525
}

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 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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 94 0 9673529 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 98 0 47074 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 29689 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.079374e+00 6.175344e+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 7.873977e+07 5.611272e+07 3.02000e+02 3.243467e+07 6.962670e+07 1.147459e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 7.000000e-06 1.403000e-03 -1.36957e-02 -6.794000e-04 -2.400000e-06 6.733000e-04 1.535800e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.207200e-03 6.870000e-04 5.09100e-04 6.771000e-04 9.027000e-04 1.544900e-03 3.925700e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.945682e-01 2.896763e-01 0.00000e+00 2.431431e-01 4.917632e-01 7.455367e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.945661e-01 2.896776e-01 0.00000e+00 2.431392e-01 4.917604e-01 7.455352e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.620879e-01 2.628620e-01 9.90490e-03 4.442710e-02 1.602100e-01 4.168840e-01 9.900950e-01 ▇▂▂▁▁
numeric AF_reference 192843 0.9800788 NA NA NA NA NA 2.615724e-01 2.536695e-01 0.00000e+00 5.051920e-02 1.753190e-01 4.125400e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 7.633400e+04 0.000000e+00 7.63340e+04 7.633400e+04 7.633400e+04 7.633400e+04 7.633400e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0003633 0.0010818 0.7370127 0.7370101 0.1114070 0.1894970 76334
1 693731 rs12238997 A G 0.0005290 0.0010246 0.6056755 0.6056753 0.1164820 0.1417730 76334
1 707522 rs371890604 G C 0.0010664 0.0011500 0.3537708 0.3537692 0.0981206 0.1293930 76334
1 717587 rs144155419 G A 0.0008413 0.0027605 0.7605627 0.7605608 0.0156164 0.0045926 76334
1 730087 rs148120343 T C 0.0017598 0.0014205 0.2153868 0.2153832 0.0570106 0.0127796 76334
1 731718 rs142557973 T C 0.0007739 0.0009720 0.4259111 0.4259080 0.1223470 0.1543530 76334
1 732032 rs61770163 A C 0.0010043 0.0010368 0.3327201 0.3327178 0.1219760 0.1555510 76334
1 734349 rs141242758 T C 0.0008529 0.0009729 0.3806466 0.3806448 0.1215500 0.1525560 76334
1 749963 rs529266287 T TAA -0.0012501 0.0009566 0.1912789 0.1912744 0.8690010 0.7641770 76334
1 751343 rs28544273 T A 0.0011561 0.0009485 0.2229128 0.2229088 0.1236480 0.2426120 76334
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0004978 0.0011379 0.6617486 0.6617468 0.0547925 0.0309934 76334
23 154923374 rs111332691 T A 0.0002976 0.0012313 0.8090311 0.8090305 0.0450848 0.0116556 76334
23 154925045 rs509981 C T 0.0004576 0.0005949 0.4417972 0.4417945 0.2446590 0.3634440 76334
23 154925895 rs538470 C T 0.0004203 0.0006082 0.4895860 0.4895832 0.2411030 0.3634440 76334
23 154927581 rs644138 G A 0.0002655 0.0005595 0.6351115 0.6351101 0.2998360 0.4635760 76334
23 154929412 rs557132 C T 0.0004661 0.0005950 0.4334081 0.4334058 0.2445300 0.3568210 76334
23 154929637 rs35185538 CT C 0.0004263 0.0006210 0.4924771 0.4924756 0.2290470 0.3011920 76334
23 154929952 rs4012982 CAA C 0.0002946 0.0006264 0.6381254 0.6381241 0.2384840 0.3165560 76334
23 154930230 rs781880 A G 0.0004454 0.0005948 0.4540106 0.4540086 0.2450070 0.3618540 76334
23 154930487 rs781879 T A 0.0007317 0.0019979 0.7141756 0.7141731 0.0200009 0.1263580 76334

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111407 ES:SE:LP:AF:SS:ID   0.000363285:0.0010818:0.132525:0.111407:76334:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116482 ES:SE:LP:AF:SS:ID   0.000528977:0.00102464:0.21776:0.116482:76334:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0981206    ES:SE:LP:AF:SS:ID   0.00106638:0.00114998:0.451278:0.0981206:76334:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156164    ES:SE:LP:AF:SS:ID   0.000841253:0.00276052:0.118865:0.0156164:76334:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0570106    ES:SE:LP:AF:SS:ID   0.00175983:0.00142048:0.666781:0.0570106:76334:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122347 ES:SE:LP:AF:SS:ID   0.000773933:0.000972017:0.370681:0.122347:76334:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121976 ES:SE:LP:AF:SS:ID   0.00100432:0.00103682:0.477921:0.121976:76334:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12155  ES:SE:LP:AF:SS:ID   0.000852929:0.000972876:0.419478:0.12155:76334:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.869001 ES:SE:LP:AF:SS:ID   -0.00125013:0.000956621:0.718333:0.869001:76334:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123648 ES:SE:LP:AF:SS:ID   0.00115611:0.000948541:0.651865:0.123648:76334:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14313  ES:SE:LP:AF:SS:ID   0.00135932:0.000938555:0.831111:0.14313:76334:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123792 ES:SE:LP:AF:SS:ID   0.00114182:0.000947117:0.642094:0.123792:76334:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869996 ES:SE:LP:AF:SS:ID   -0.000901448:0.000923139:0.483044:0.869996:76334:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87462  ES:SE:LP:AF:SS:ID   -0.0010838:0.000937842:0.605834:0.87462:76334:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129439 ES:SE:LP:AF:SS:ID   0.000996976:0.000926056:0.550259:0.129439:76334:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0355805    ES:SE:LP:AF:SS:ID   -9.16747e-05:0.00169607:0.0191357:0.0355805:76334:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869628 ES:SE:LP:AF:SS:ID   -0.000898511:0.000922317:0.481531:0.869628:76334:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869694 ES:SE:LP:AF:SS:ID   -0.000905983:0.000922676:0.486584:0.869694:76334:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869624 ES:SE:LP:AF:SS:ID   -0.000901979:0.000922275:0.484019:0.869624:76334:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.869624 ES:SE:LP:AF:SS:ID   -0.000908105:0.000920515:0.489613:0.869624:76334:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126842 ES:SE:LP:AF:SS:ID   0.00107013:0.000939487:0.593997:0.126842:76334:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869147 ES:SE:LP:AF:SS:ID   -0.000865243:0.000918157:0.460916:0.869147:76334:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868488 ES:SE:LP:AF:SS:ID   -0.000887715:0.000917372:0.477281:0.868488:76334:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869307 ES:SE:LP:AF:SS:ID   -0.000892278:0.000918997:0.479401:0.869307:76334:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869312 ES:SE:LP:AF:SS:ID   -0.000890559:0.000919055:0.478142:0.869312:76334:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869315 ES:SE:LP:AF:SS:ID   -0.000891411:0.000919067:0.478738:0.869315:76334:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869774 ES:SE:LP:AF:SS:ID   -0.000907207:0.000921434:0.488326:0.869774:76334:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0993775    ES:SE:LP:AF:SS:ID   0.000947041:0.00107097:0.424181:0.0993775:76334:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.873729 ES:SE:LP:AF:SS:ID   -0.000993979:0.00093473:0.541196:0.873729:76334:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863146 ES:SE:LP:AF:SS:ID   -0.000862424:0.00091713:0.459619:0.863146:76334:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868565 ES:SE:LP:AF:SS:ID   -0.000954619:0.000926232:0.518975:0.868565:76334:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865447 ES:SE:LP:AF:SS:ID   -0.00072642:0.000926311:0.363591:0.865447:76334:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0993259    ES:SE:LP:AF:SS:ID   0.00107327:0.00111024:0.476653:0.0993259:76334:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870674 ES:SE:LP:AF:SS:ID   -0.000956413:0.000936553:0.512635:0.870674:76334:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870674 ES:SE:LP:AF:SS:ID   -0.000956643:0.000936553:0.512799:0.870674:76334:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870671 ES:SE:LP:AF:SS:ID   -0.000956511:0.000936556:0.512703:0.870671:76334:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871043 ES:SE:LP:AF:SS:ID   -0.000996521:0.000937045:0.541255:0.871043:76334:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126455 ES:SE:LP:AF:SS:ID   0.00111627:0.000938241:0.630508:0.126455:76334:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106136 ES:SE:LP:AF:SS:ID   0.00069164:0.00102005:0.302993:0.106136:76334:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854487 ES:SE:LP:AF:SS:ID   -0.00104716:0.000916896:0.596149:0.854487:76334:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839351 ES:SE:LP:AF:SS:ID   0.00107823:0.000905481:0.631265:0.839351:76334:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763309 ES:SE:LP:AF:SS:ID   0.000127928:0.000727665:0.0652759:0.763309:76334:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105091 ES:SE:LP:AF:SS:ID   -0.00119644:0.00100286:0.632903:0.105091:76334:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.129796 ES:SE:LP:AF:SS:ID   0.000997485:0.000925519:0.551068:0.129796:76334:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.129562 ES:SE:LP:AF:SS:ID   0.000989545:0.000924286:0.546145:0.129562:76334:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104373 ES:SE:LP:AF:SS:ID   -0.00112822:0.00101068:0.577911:0.104373:76334:rs7518545
1   770886  rs371458725 G   A   .   PASS    AF=0.103373 ES:SE:LP:AF:SS:ID   -0.00121202:0.00101958:0.629778:0.103373:76334:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.829553 ES:SE:LP:AF:SS:ID   -0.000814454:0.000901934:0.435898:0.829553:76334:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.86915  ES:SE:LP:AF:SS:ID   -0.000872689:0.000919764:0.465066:0.86915:76334:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129657 ES:SE:LP:AF:SS:ID   0.000994303:0.000923799:0.550077:0.129657:76334:rs59066358