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-30830_irnt/ukb-d-30830_irnt.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-30830_irnt/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 15:36:11 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30830_irnt/ukb-d-30830_irnt.vcf.gz ...
Read summary statistics for 13585246 SNPs.
Dropped 12712 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, 1283502 SNPs remain.
After merging with regression SNP LD, 1283502 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2363 (0.0672)
Lambda GC: 1.5618
Mean Chi^2: 2.511
Intercept: 1.1295 (0.0201)
Ratio: 0.0857 (0.0133)
Analysis finished at Mon Nov 25 15:38:31 2019
Total time elapsed: 2.0m:19.46s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.3401,
    "mean_EFFECT": -0,
    "n": 312215,
    "n_snps": 13585246,
    "n_clumped_hits": 266,
    "n_p_sig": 52500,
    "n_mono": 0,
    "n_ns": 1251735,
    "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": 568991,
    "n_est": 313455.0029,
    "ratio_se_n": 1.002,
    "mean_diff": -2.1357e-06,
    "ratio_diff": 1.8536,
    "sd_y_est1": 0.8985,
    "sd_y_est2": 0.9003,
    "r2_sum1": 0.0789,
    "r2_sum2": 0.0977,
    "r2_sum3": 0.0973,
    "r2_sum4": 0.0969,
    "ldsc_nsnp_merge_refpanel_ld": 1283502,
    "ldsc_nsnp_merge_regression_ld": 1283502,
    "ldsc_observed_scale_h2_beta": 0.2363,
    "ldsc_observed_scale_h2_se": 0.0672,
    "ldsc_intercept_beta": 1.1295,
    "ldsc_intercept_se": 0.0201,
    "ldsc_lambda_gc": 1.5618,
    "ldsc_mean_chisq": 2.511,
    "ldsc_ratio": 0.0857
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
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 1.000000 3 94 0 13573198 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 100 0 57081 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 342 0 33334 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 9.051262e+00 6.184964e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.902551e+07 5.591508e+07 3.02000e+02 3.293070e+07 7.013916e+07 1.148601e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA -2.970000e-05 1.414830e-02 -1.32740e+00 -4.262500e-03 1.720000e-05 4.255500e-03 4.779800e-01 ▁▁▁▇▁
numeric SE 0 1.000000 NA NA NA NA NA 9.553600e-03 9.215300e-03 1.86660e-03 2.720500e-03 5.012400e-03 1.372800e-02 4.644700e-02 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.512869e-01 3.031896e-01 0.00000e+00 1.762199e-01 4.349196e-01 7.145292e-01 1.000000e+00 ▇▆▅▅▅
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.512864e-01 3.031899e-01 0.00000e+00 1.762171e-01 4.349203e-01 7.145261e-01 1.000000e+00 ▇▆▅▅▅
numeric AF 0 1.000000 NA NA NA NA NA 1.908184e-01 2.544052e-01 1.00000e-03 7.433900e-03 6.004500e-02 2.953300e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 568991 0.958117 NA NA NA NA NA 1.963451e-01 2.471029e-01 0.00000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.000000 NA NA NA NA NA 3.122150e+05 0.000000e+00 3.12215e+05 3.122150e+05 3.122150e+05 3.122150e+05 3.122150e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0067749 0.0039840 0.0890348 0.0890318 0.1104600 0.1894970 312215
1 693731 rs12238997 A G 0.0029678 0.0037636 0.4303601 0.4303730 0.1157500 0.1417730 312215
1 707522 rs371890604 G C 0.0009823 0.0042346 0.8165600 0.8165577 0.0971530 0.1293930 312215
1 717587 rs144155419 G A 0.0233240 0.0100910 0.0208109 0.0208126 0.0156810 0.0045926 312215
1 723329 rs189787166 A T -0.0111150 0.0297830 0.7089996 0.7090000 0.0017330 0.0003994 312215
1 730087 rs148120343 T C 0.0044796 0.0052433 0.3929099 0.3929125 0.0564350 0.0127796 312215
1 731718 rs142557973 T C 0.0029298 0.0035699 0.4118196 0.4118199 0.1216400 0.1543530 312215
1 732032 rs61770163 A C 0.0036636 0.0038097 0.3362204 0.3362252 0.1210100 0.1555510 312215
1 734349 rs141242758 T C 0.0029863 0.0035718 0.4031197 0.4031116 0.1208600 0.1525560 312215
1 740284 rs61770167 C T -0.0089003 0.0164080 0.5875096 0.5875178 0.0057346 0.0023962 312215
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0060131 0.0041192 0.1443600 0.1443523 0.056128 0.0309934 312215
23 154923374 rs111332691 T A -0.0038711 0.0045127 0.3909903 0.3909899 0.044947 0.0116556 312215
23 154925045 rs509981 C T 0.0070547 0.0021762 0.0011878 0.0011880 0.245800 0.3634440 312215
23 154925895 rs538470 C T 0.0068962 0.0022261 0.0019490 0.0019491 0.242090 0.3634440 312215
23 154927581 rs644138 G A 0.0076987 0.0020469 0.0001691 0.0001691 0.302300 0.4635760 312215
23 154929412 rs557132 C T 0.0070063 0.0021768 0.0012880 0.0012881 0.245650 0.3568210 312215
23 154929637 rs35185538 CT C 0.0072035 0.0022714 0.0015175 0.0015171 0.230020 0.3011920 312215
23 154929952 rs4012982 CAA C 0.0081331 0.0022891 0.0003809 0.0003809 0.239600 0.3165560 312215
23 154930230 rs781880 A G 0.0068226 0.0021765 0.0017208 0.0017205 0.246030 0.3618540 312215
23 154930487 rs781879 T A -0.0074628 0.0074758 0.3181501 0.3181528 0.019488 0.1263580 312215

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11046  ES:SE:LP:AF:SS:ID   0.0067749:0.003984:1.05044:0.11046:312215:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11575  ES:SE:LP:AF:SS:ID   0.0029678:0.0037636:0.366168:0.11575:312215:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097153 ES:SE:LP:AF:SS:ID   0.00098232:0.0042346:0.0880119:0.097153:312215:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015681 ES:SE:LP:AF:SS:ID   0.023324:0.010091:1.68171:0.015681:312215:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.001733 ES:SE:LP:AF:SS:ID   -0.011115:0.029783:0.149354:0.001733:312215:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056435 ES:SE:LP:AF:SS:ID   0.0044796:0.0052433:0.405707:0.056435:312215:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12164  ES:SE:LP:AF:SS:ID   0.0029298:0.0035699:0.385293:0.12164:312215:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12101  ES:SE:LP:AF:SS:ID   0.0036636:0.0038097:0.473376:0.12101:312215:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12086  ES:SE:LP:AF:SS:ID   0.0029863:0.0035718:0.394566:0.12086:312215:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057346    ES:SE:LP:AF:SS:ID   -0.0089003:0.016408:0.230985:0.0057346:312215:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018613    ES:SE:LP:AF:SS:ID   -0.059032:0.031023:1.24364:0.0018613:312215:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86983  ES:SE:LP:AF:SS:ID   -0.0043645:0.003521:0.667279:0.86983:312215:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015162    ES:SE:LP:AF:SS:ID   -0.012867:0.032027:0.162506:0.0015162:312215:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12283  ES:SE:LP:AF:SS:ID   0.0044134:0.0034873:0.686829:0.12283:312215:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14262  ES:SE:LP:AF:SS:ID   0.0042189:0.0034462:0.655863:0.14262:312215:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12295  ES:SE:LP:AF:SS:ID   0.0043265:0.0034824:0.669383:0.12295:312215:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87104  ES:SE:LP:AF:SS:ID   -0.0031735:0.0033944:0.456155:0.87104:312215:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87558  ES:SE:LP:AF:SS:ID   -0.0037533:0.0034497:0.558164:0.87558:312215:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12851  ES:SE:LP:AF:SS:ID   0.0037002:0.0034026:0.557787:0.12851:312215:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036292 ES:SE:LP:AF:SS:ID   0.0066169:0.0061758:0.546712:0.036292:312215:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87063  ES:SE:LP:AF:SS:ID   -0.0032342:0.0033907:0.468317:0.87063:312215:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87074  ES:SE:LP:AF:SS:ID   -0.0033748:0.0033924:0.495094:0.87074:312215:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87062  ES:SE:LP:AF:SS:ID   -0.0032064:0.0033906:0.46305:0.87062:312215:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050365    ES:SE:LP:AF:SS:ID   -0.0015812:0.017391:0.032658:0.0050365:312215:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050039    ES:SE:LP:AF:SS:ID   -0.0011309:0.017437:0.0230588:0.0050039:312215:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055192    ES:SE:LP:AF:SS:ID   0.01549:0.016947:0.442842:0.0055192:312215:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87072  ES:SE:LP:AF:SS:ID   -0.0034049:0.0033849:0.502435:0.87072:312215:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12584  ES:SE:LP:AF:SS:ID   0.004148:0.0034534:0.638839:0.12584:312215:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87029  ES:SE:LP:AF:SS:ID   -0.0035236:0.0033768:0.527624:0.87029:312215:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86956  ES:SE:LP:AF:SS:ID   -0.0030659:0.0033738:0.439508:0.86956:312215:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87044  ES:SE:LP:AF:SS:ID   -0.0034156:0.0033797:0.505567:0.87044:312215:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87044  ES:SE:LP:AF:SS:ID   -0.0034207:0.0033799:0.506528:0.87044:312215:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87045  ES:SE:LP:AF:SS:ID   -0.0034791:0.00338:0.51807:0.87045:312215:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8709   ES:SE:LP:AF:SS:ID   -0.0032897:0.0033886:0.47932:0.8709:312215:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098742 ES:SE:LP:AF:SS:ID   0.0020584:0.003938:0.220988:0.098742:312215:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0063972    ES:SE:LP:AF:SS:ID   0.020552:0.015326:0.744921:0.0063972:312215:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87475  ES:SE:LP:AF:SS:ID   -0.0041508:0.0034383:0.643305:0.87475:312215:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86418  ES:SE:LP:AF:SS:ID   -0.003817:0.0033727:0.588784:0.86418:312215:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86957  ES:SE:LP:AF:SS:ID   -0.0036859:0.0034048:0.554396:0.86957:312215:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86651  ES:SE:LP:AF:SS:ID   -0.0040876:0.0034055:0.638234:0.86651:312215:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.09874  ES:SE:LP:AF:SS:ID   0.004386:0.0040755:0.549997:0.09874:312215:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87168  ES:SE:LP:AF:SS:ID   -0.0047092:0.0034441:0.76566:0.87168:312215:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87168  ES:SE:LP:AF:SS:ID   -0.0047094:0.0034441:0.765736:0.87168:312215:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87168  ES:SE:LP:AF:SS:ID   -0.0047189:0.0034441:0.767894:0.87168:312215:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87204  ES:SE:LP:AF:SS:ID   -0.0045346:0.003446:0.725334:0.87204:312215:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12546  ES:SE:LP:AF:SS:ID   0.004565:0.0034487:0.731399:0.12546:312215:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10531  ES:SE:LP:AF:SS:ID   0.0012371:0.0037563:0.129655:0.10531:312215:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.8555   ES:SE:LP:AF:SS:ID   -0.0036965:0.0033712:0.564044:0.8555:312215:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016517    ES:SE:LP:AF:SS:ID   -0.006542:0.029854:0.0827309:0.0016517:312215:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83831  ES:SE:LP:AF:SS:ID   -0.0053433:0.0033159:0.970251:0.83831:312215:rs376645387