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-5855_1/ukb-d-5855_1.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-5855_1/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 16:53:50 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-5855_1/ukb-d-5855_1.vcf.gz ...
Read summary statistics for 9914174 SNPs.
Dropped 7596 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, 1277432 SNPs remain.
After merging with regression SNP LD, 1277432 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1574 (0.0508)
Lambda GC: 1.0189
Mean Chi^2: 1.0221
Intercept: 0.991 (0.0066)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:55:27 2019
Total time elapsed: 1.0m:37.2s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9412,
    "inflation_factor": 1.018,
    "mean_EFFECT": -0,
    "n": 9749,
    "n_snps": 9914174,
    "n_clumped_hits": 1,
    "n_p_sig": 3,
    "n_mono": 0,
    "n_ns": 1077542,
    "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": 196403,
    "n_est": 9768.7965,
    "ratio_se_n": 1.001,
    "mean_diff": -0,
    "ratio_diff": 44.7077,
    "sd_y_est1": 0.3577,
    "sd_y_est2": 0.358,
    "r2_sum1": 0.0005,
    "r2_sum2": 0.0037,
    "r2_sum3": 0.0037,
    "r2_sum4": 0.0034,
    "ldsc_nsnp_merge_refpanel_ld": 1277432,
    "ldsc_nsnp_merge_regression_ld": 1277432,
    "ldsc_observed_scale_h2_beta": 0.1574,
    "ldsc_observed_scale_h2_se": 0.0508,
    "ldsc_intercept_beta": 0.991,
    "ldsc_intercept_se": 0.0066,
    "ldsc_lambda_gc": 1.0189,
    "ldsc_mean_chisq": 1.0221,
    "ldsc_ratio": -0.4072
}

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 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 9907127 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 98 0 47873 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 30022 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.079562e+00 6.176522e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.875289e+07 5.609583e+07 3.0200e+02 3.245813e+07 6.965823e+07 1.147364e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -2.710000e-05 1.216390e-02 -1.0425e-01 -5.751300e-03 -6.800000e-05 5.594100e-03 1.540080e-01 ▁▇▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.041070e-02 6.215800e-03 4.2813e-03 5.633200e-03 7.624400e-03 1.343440e-02 3.512250e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.975893e-01 2.891277e-01 0.0000e+00 2.471741e-01 4.961580e-01 7.483625e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.975729e-01 2.891375e-01 0.0000e+00 2.471457e-01 4.961421e-01 7.483553e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.565664e-01 2.629553e-01 8.6149e-03 3.999060e-02 1.522680e-01 4.090690e-01 9.913850e-01 ▇▂▂▁▁
numeric AF_reference 196403 0.9801897 NA NA NA NA NA 2.561702e-01 2.537852e-01 0.0000e+00 4.472840e-02 1.679310e-01 4.049520e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 9.749000e+03 0.000000e+00 9.7490e+03 9.749000e+03 9.749000e+03 9.749000e+03 9.749000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0196426 0.0088667 0.0267602 0.0267374 0.1142420 0.1894970 9749
1 693731 rs12238997 A G 0.0178721 0.0083667 0.0326964 0.0326709 0.1187010 0.1417730 9749
1 707522 rs371890604 G C 0.0172135 0.0094321 0.0680315 0.0680018 0.1007710 0.1293930 9749
1 717587 rs144155419 G A 0.0124014 0.0225324 0.5820724 0.5820582 0.0159707 0.0045926 9749
1 730087 rs148120343 T C 0.0316083 0.0118257 0.0075334 0.0075210 0.0571894 0.0127796 9749
1 731718 rs142557973 T C 0.0158041 0.0079389 0.0465382 0.0465107 0.1248650 0.1543530 9749
1 732032 rs61770163 A C 0.0158619 0.0084934 0.0618557 0.0618255 0.1241390 0.1555510 9749
1 734349 rs141242758 T C 0.0159415 0.0079522 0.0450267 0.0449994 0.1239920 0.1525560 9749
1 749963 rs529266287 T TAA -0.0128957 0.0078222 0.0992613 0.0992278 0.8665310 0.7641770 9749
1 751343 rs28544273 T A 0.0130185 0.0077634 0.0935923 0.0935590 0.1259490 0.2426120 9749
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0152755 0.0097451 0.1170281 0.1169962 0.0528342 0.0309934 9749
23 154923374 rs111332691 T A -0.0026122 0.0103744 0.8012080 0.8012034 0.0460047 0.0116556 9749
23 154925045 rs509981 C T -0.0030502 0.0050378 0.5448889 0.5448742 0.2399570 0.3634440 9749
23 154925895 rs538470 C T -0.0036251 0.0051503 0.4815385 0.4815202 0.2362200 0.3634440 9749
23 154927581 rs644138 G A -0.0064878 0.0047372 0.1708591 0.1708279 0.2933230 0.4635760 9749
23 154929412 rs557132 C T -0.0029132 0.0050412 0.5633587 0.5633451 0.2397070 0.3568210 9749
23 154929637 rs35185538 CT C -0.0028303 0.0052615 0.5906361 0.5906239 0.2242450 0.3011920 9749
23 154929952 rs4012982 CAA C -0.0035964 0.0052942 0.4969629 0.4969459 0.2333320 0.3165560 9749
23 154930230 rs781880 A G -0.0027668 0.0050416 0.5831604 0.5831482 0.2398920 0.3618540 9749
23 154930487 rs781879 T A -0.0289095 0.0171974 0.0927876 0.0927553 0.0185018 0.1263580 9749

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.114242 ES:SE:LP:AF:SS:ID   0.0196426:0.00886667:1.57251:0.114242:9749:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.118701 ES:SE:LP:AF:SS:ID   0.0178721:0.00836668:1.4855:0.118701:9749:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.100771 ES:SE:LP:AF:SS:ID   0.0172135:0.00943208:1.16729:0.100771:9749:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0159707    ES:SE:LP:AF:SS:ID   0.0124014:0.0225324:0.235023:0.0159707:9749:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0571894    ES:SE:LP:AF:SS:ID   0.0316083:0.0118257:2.12301:0.0571894:9749:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.124865 ES:SE:LP:AF:SS:ID   0.0158041:0.00793885:1.33219:0.124865:9749:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.124139 ES:SE:LP:AF:SS:ID   0.0158619:0.00849345:1.20862:0.124139:9749:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.123992 ES:SE:LP:AF:SS:ID   0.0159415:0.00795222:1.34653:0.123992:9749:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.866531 ES:SE:LP:AF:SS:ID   -0.0128957:0.00782217:1.00322:0.866531:9749:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.125949 ES:SE:LP:AF:SS:ID   0.0130185:0.00776336:1.02876:0.125949:9749:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.144819 ES:SE:LP:AF:SS:ID   0.0128674:0.00773211:1.01721:0.144819:9749:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.126104 ES:SE:LP:AF:SS:ID   0.0129172:0.00775095:1.01936:0.126104:9749:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.867084 ES:SE:LP:AF:SS:ID   -0.013818:0.00754104:1.1744:0.867084:9749:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.872272 ES:SE:LP:AF:SS:ID   -0.0122597:0.00767458:0.957822:0.872272:9749:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.132153 ES:SE:LP:AF:SS:ID   0.0147116:0.00756018:1.28657:0.132153:9749:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0374397    ES:SE:LP:AF:SS:ID   0.00740941:0.0137097:0.229959:0.0374397:9749:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.866829 ES:SE:LP:AF:SS:ID   -0.0140361:0.00753808:1.20322:0.866829:9749:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.866825 ES:SE:LP:AF:SS:ID   -0.0140232:0.00753829:1.2015:0.866825:9749:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.866826 ES:SE:LP:AF:SS:ID   -0.0140146:0.00753779:1.2005:0.866826:9749:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.866917 ES:SE:LP:AF:SS:ID   -0.01372:0.00752232:1.16623:0.866917:9749:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.129067 ES:SE:LP:AF:SS:ID   0.0125341:0.00767373:0.989611:0.129067:9749:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.866345 ES:SE:LP:AF:SS:ID   -0.0137983:0.00749916:1.18177:0.866345:9749:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.865774 ES:SE:LP:AF:SS:ID   -0.0133662:0.00749887:1.12662:0.865774:9749:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.866606 ES:SE:LP:AF:SS:ID   -0.0139063:0.00750833:1.19355:0.866606:9749:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.866611 ES:SE:LP:AF:SS:ID   -0.0138979:0.00750887:1.19233:0.866611:9749:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.866635 ES:SE:LP:AF:SS:ID   -0.0139417:0.0075095:1.19786:0.866635:9749:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.867029 ES:SE:LP:AF:SS:ID   -0.0137009:0.00752863:1.16233:0.867029:9749:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.102203 ES:SE:LP:AF:SS:ID   0.0147961:0.00874659:1.04217:0.102203:9749:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.871134 ES:SE:LP:AF:SS:ID   -0.0129519:0.00764656:1.04416:0.871134:9749:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.860725 ES:SE:LP:AF:SS:ID   -0.0135692:0.00750849:1.15019:0.860725:9749:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.865849 ES:SE:LP:AF:SS:ID   -0.0133178:0.00758001:1.10262:0.865849:9749:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.862713 ES:SE:LP:AF:SS:ID   -0.0136821:0.00757106:1.15015:0.862713:9749:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.101338 ES:SE:LP:AF:SS:ID   0.00970964:0.0090377:0.548685:0.101338:9749:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.868004 ES:SE:LP:AF:SS:ID   -0.0136098:0.00766557:1.12001:0.868004:9749:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.868004 ES:SE:LP:AF:SS:ID   -0.01361:0.00766556:1.12004:0.868004:9749:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.868002 ES:SE:LP:AF:SS:ID   -0.013614:0.00766558:1.12052:0.868002:9749:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.868382 ES:SE:LP:AF:SS:ID   -0.0130103:0.00767231:1.04592:0.868382:9749:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.128883 ES:SE:LP:AF:SS:ID   0.0140576:0.00766765:1.17536:0.128883:9749:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.108582 ES:SE:LP:AF:SS:ID   0.0140815:0.00836364:1.03489:0.108582:9749:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.851426 ES:SE:LP:AF:SS:ID   -0.0106788:0.00750269:0.810591:0.851426:9749:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837626 ES:SE:LP:AF:SS:ID   0.00179825:0.00749426:0.0913145:0.837626:9749:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.759154 ES:SE:LP:AF:SS:ID   -0.00502089:0.0059905:0.395804:0.759154:9749:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106678 ES:SE:LP:AF:SS:ID   -0.00724408:0.00824731:0.420477:0.106678:9749:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.132197 ES:SE:LP:AF:SS:ID   0.0140674:0.0075597:1.20207:0.132197:9749:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.131943 ES:SE:LP:AF:SS:ID   0.0144996:0.00754775:1.26158:0.131943:9749:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.10582  ES:SE:LP:AF:SS:ID   -0.00735572:0.00832186:0.423924:0.10582:9749:rs7518545
1   770886  rs371458725 G   A   .   PASS    AF=0.104877 ES:SE:LP:AF:SS:ID   -0.00731757:0.00838571:0.416926:0.104877:9749:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.827243 ES:SE:LP:AF:SS:ID   -0.0126014:0.00743127:1.04591:0.827243:9749:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.866554 ES:SE:LP:AF:SS:ID   -0.0141155:0.0075188:1.21825:0.866554:9749:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.131979 ES:SE:LP:AF:SS:ID   0.0146962:0.00754553:1.28834:0.131979:9749:rs59066358