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-4067/ukb-d-4067.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-4067/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 17:18:24 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-4067/ukb-d-4067.vcf.gz ...
Read summary statistics for 11208820 SNPs.
Dropped 9361 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, 1282195 SNPs remain.
After merging with regression SNP LD, 1282195 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0529 (0.0734)
Lambda GC: 1.0104
Mean Chi^2: 1.0027
Intercept: 1.0095 (0.0061)
Ratio: 3.5487 (2.3068)
Analysis finished at Mon Nov 25 17:20:21 2019
Total time elapsed: 1.0m:56.62s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9466,
    "inflation_factor": 1.005,
    "mean_EFFECT": 0.0001,
    "n": 6510,
    "n_snps": 11208820,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1147951,
    "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": 229773,
    "n_est": 6531.5068,
    "ratio_se_n": 1.0017,
    "mean_diff": 0,
    "ratio_diff": 25.7288,
    "sd_y_est1": 0.5019,
    "sd_y_est2": 0.5028,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1282195,
    "ldsc_nsnp_merge_regression_ld": 1282195,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0095,
    "ldsc_intercept_se": 0.0061,
    "ldsc_lambda_gc": 1.0104,
    "ldsc_mean_chisq": 1.0027,
    "ldsc_ratio": 3.5185
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
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 11200053 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 51530 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 31482 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.075047e+00 6.182270e+00 1.0000000 4.00000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.883345e+07 5.600945e+07 302.0000000 3.26140e+07 6.983391e+07 1.147478e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 5.130000e-05 2.842380e-02 -0.2961720 -1.08543e-02 9.900000e-06 1.091510e-02 3.004090e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.274280e-02 1.695580e-02 0.0075844 9.93630e-03 1.475980e-02 3.064160e-02 9.484810e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.993650e-01 2.886962e-01 0.0000003 2.48958e-01 4.989258e-01 7.495956e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.993404e-01 2.887110e-01 0.0000003 2.48916e-01 4.989014e-01 7.495846e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.289781e-01 2.613785e-01 0.0040234 2.21225e-02 1.126000e-01 3.663100e-01 9.959770e-01 ▇▂▁▁▁
numeric AF_reference 229773 0.9795007 NA NA NA NA NA 2.293791e-01 2.525306e-01 0.0000000 2.01677e-02 1.307910e-01 3.654150e-01 1.000000e+00 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 6.510000e+03 0.000000e+00 6510.0000000 6.51000e+03 6.510000e+03 6.510000e+03 6.510000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0028314 0.0153727 0.8538750 0.8538689 0.1097410 0.1894970 6510
1 693731 rs12238997 A G 0.0162647 0.0146078 0.2655682 0.2655256 0.1150260 0.1417730 6510
1 707522 rs371890604 G C 0.0102094 0.0164355 0.5345016 0.5344814 0.0958890 0.1293930 6510
1 717587 rs144155419 G A 0.0412892 0.0385498 0.2841823 0.2841419 0.0161655 0.0045926 6510
1 730087 rs148120343 T C -0.0091756 0.0201956 0.6496015 0.6495855 0.0557402 0.0127796 6510
1 731718 rs142557973 T C 0.0107750 0.0137882 0.4345562 0.4345289 0.1207380 0.1543530 6510
1 732032 rs61770163 A C 0.0120886 0.0147366 0.4120700 0.4120386 0.1196240 0.1555510 6510
1 734349 rs141242758 T C 0.0098312 0.0137885 0.4758729 0.4758480 0.1201130 0.1525560 6510
1 740284 rs61770167 C T -0.0625949 0.0639484 0.3276989 0.3276618 0.0056658 0.0023962 6510
1 749963 rs529266287 T TAA -0.0103862 0.0136200 0.4457466 0.4457200 0.8695260 0.7641770 6510
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0255191 0.0161964 0.1151659 0.1151173 0.0591076 0.0309934 6510
23 154923374 rs111332691 T A -0.0168323 0.0190687 0.3774218 0.3773882 0.0415515 0.0116556 6510
23 154925045 rs509981 C T 0.0012618 0.0091133 0.8898861 0.8898816 0.2360660 0.3634440 6510
23 154925895 rs538470 C T 0.0002339 0.0093100 0.9799540 0.9799537 0.2332280 0.3634440 6510
23 154927581 rs644138 G A -0.0057803 0.0084748 0.4952244 0.4952002 0.2957900 0.4635760 6510
23 154929412 rs557132 C T 0.0011747 0.0091167 0.8974780 0.8974733 0.2358840 0.3568210 6510
23 154929637 rs35185538 CT C -0.0050457 0.0095701 0.5980521 0.5980335 0.2207480 0.3011920 6510
23 154929952 rs4012982 CAA C 0.0006439 0.0095655 0.9463330 0.9463304 0.2309040 0.3165560 6510
23 154930230 rs781880 A G 0.0016156 0.0091178 0.8593631 0.8593569 0.2362700 0.3618540 6510
23 154930487 rs781879 T A -0.0251516 0.0310331 0.4176957 0.4176663 0.0189820 0.1263580 6510

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.109741 ES:SE:LP:AF:SS:ID   0.00283141:0.0153727:0.0686057:0.109741:6510:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115026 ES:SE:LP:AF:SS:ID   0.0162647:0.0146078:0.575824:0.115026:6510:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.095889 ES:SE:LP:AF:SS:ID   0.0102094:0.0164355:0.272051:0.095889:6510:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0161655    ES:SE:LP:AF:SS:ID   0.0412892:0.0385498:0.546403:0.0161655:6510:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0557402    ES:SE:LP:AF:SS:ID   -0.00917563:0.0201956:0.187353:0.0557402:6510:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.120738 ES:SE:LP:AF:SS:ID   0.010775:0.0137882:0.361954:0.120738:6510:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.119624 ES:SE:LP:AF:SS:ID   0.0120886:0.0147366:0.385029:0.119624:6510:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120113 ES:SE:LP:AF:SS:ID   0.00983115:0.0137885:0.322509:0.120113:6510:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00566579   ES:SE:LP:AF:SS:ID   -0.0625949:0.0639484:0.484525:0.00566579:6510:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.869526 ES:SE:LP:AF:SS:ID   -0.0103862:0.01362:0.350912:0.869526:6510:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123062 ES:SE:LP:AF:SS:ID   0.00952371:0.0134828:0.31877:0.123062:6510:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.144052 ES:SE:LP:AF:SS:ID   0.00915571:0.0132265:0.310849:0.144052:6510:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123188 ES:SE:LP:AF:SS:ID   0.00920484:0.0134626:0.306126:0.123188:6510:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87077  ES:SE:LP:AF:SS:ID   -0.00906481:0.0131161:0.310235:0.87077:6510:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875501 ES:SE:LP:AF:SS:ID   -0.0103357:0.0133342:0.358235:0.875501:6510:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129059 ES:SE:LP:AF:SS:ID   0.00924191:0.0131464:0.316879:0.129059:6510:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0350998    ES:SE:LP:AF:SS:ID   0.0152484:0.0242729:0.275814:0.0350998:6510:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870335 ES:SE:LP:AF:SS:ID   -0.0100097:0.0131072:0.351554:0.870335:6510:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870496 ES:SE:LP:AF:SS:ID   -0.00999137:0.0131135:0.350532:0.870496:6510:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870337 ES:SE:LP:AF:SS:ID   -0.0100548:0.0131065:0.35358:0.870337:6510:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005845 ES:SE:LP:AF:SS:ID   -0.0171758:0.0626151:0.105763:0.005845:6510:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00582482   ES:SE:LP:AF:SS:ID   -0.0172373:0.0627428:0.105943:0.00582482:6510:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00515647   ES:SE:LP:AF:SS:ID   -0.0193248:0.0696463:0.107111:0.00515647:6510:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870351 ES:SE:LP:AF:SS:ID   -0.00884857:0.0130839:0.302005:0.870351:6510:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126388 ES:SE:LP:AF:SS:ID   0.0098291:0.0133432:0.335951:0.126388:6510:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870046 ES:SE:LP:AF:SS:ID   -0.00919362:0.013063:0.317325:0.870046:6510:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869276 ES:SE:LP:AF:SS:ID   -0.0097011:0.0130528:0.339728:0.869276:6510:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87019  ES:SE:LP:AF:SS:ID   -0.00910131:0.0130701:0.313153:0.87019:6510:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870196 ES:SE:LP:AF:SS:ID   -0.00909236:0.0130709:0.312747:0.870196:6510:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870204 ES:SE:LP:AF:SS:ID   -0.00907491:0.0130716:0.311978:0.870204:6510:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870509 ES:SE:LP:AF:SS:ID   -0.00920128:0.0130932:0.31674:0.870509:6510:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0976528    ES:SE:LP:AF:SS:ID   0.00518509:0.0153122:0.13377:0.0976528:6510:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00615102   ES:SE:LP:AF:SS:ID   0.00402806:0.0603739:0.0237381:0.00615102:6510:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874256 ES:SE:LP:AF:SS:ID   -0.0103213:0.0132793:0.359479:0.874256:6510:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863963 ES:SE:LP:AF:SS:ID   -0.00827498:0.0130469:0.279063:0.863963:6510:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869469 ES:SE:LP:AF:SS:ID   -0.00923994:0.0131706:0.31607:0.869469:6510:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865595 ES:SE:LP:AF:SS:ID   -0.0113166:0.0131519:0.409414:0.865595:6510:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0975483    ES:SE:LP:AF:SS:ID   0.0203232:0.0159461:0.6935:0.0975483:6510:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870901 ES:SE:LP:AF:SS:ID   -0.0112917:0.0133054:0.402191:0.870901:6510:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870901 ES:SE:LP:AF:SS:ID   -0.0112917:0.0133054:0.402191:0.870901:6510:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870898 ES:SE:LP:AF:SS:ID   -0.0112906:0.0133054:0.402138:0.870898:6510:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87149  ES:SE:LP:AF:SS:ID   -0.0111442:0.0133136:0.395133:0.87149:6510:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126075 ES:SE:LP:AF:SS:ID   0.00911242:0.0133279:0.306113:0.126075:6510:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10386  ES:SE:LP:AF:SS:ID   0.00124022:0.0145752:0.0304946:0.10386:6510:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855752 ES:SE:LP:AF:SS:ID   -0.0089666:0.0130849:0.306973:0.855752:6510:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.836003 ES:SE:LP:AF:SS:ID   -0.00483653:0.0127908:0.151596:0.836003:6510:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.762741 ES:SE:LP:AF:SS:ID   -0.00578176:0.0102702:0.241482:0.762741:6510:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106528 ES:SE:LP:AF:SS:ID   0.001944:0.0141964:0.0500804:0.106528:6510:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00885756   ES:SE:LP:AF:SS:ID   0.100612:0.0490495:1.39487:0.00885756:6510:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.12918  ES:SE:LP:AF:SS:ID   0.00757524:0.0131619:0.247995:0.12918:6510:rs762168062