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-a-import/processed/ukb-a-357/ukb-a-357.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-a-import/processed/ukb-a-357/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Sun Feb 16 01:58:41 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-a-import/processed/ukb-a-357/ukb-a-357.vcf.gz ...
Read summary statistics for 10877936 SNPs.
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, 1281483 SNPs remain.
After merging with regression SNP LD, 1281483 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1235 (0.0589)
Lambda GC: 1.068
Mean Chi^2: 1.0097
Intercept: 0.9915 (0.0071)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Sun Feb 16 02:00:26 2020
Total time elapsed: 1.0m:44.73s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9533,
    "inflation_factor": 0.4736,
    "mean_EFFECT": 5.0212e-06,
    "n": 7637,
    "n_snps": 10877936,
    "n_clumped_hits": 402,
    "n_p_sig": 28811,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 356865,
    "n_est": 7632.3545,
    "ratio_se_n": 0.9997,
    "mean_diff": 0.0002,
    "ratio_diff": 31.6732,
    "sd_y_est1": 0.0305,
    "sd_y_est2": 0.0305,
    "r2_sum1": 0.0023,
    "r2_sum2": 2.5108,
    "r2_sum3": 2.5124,
    "r2_sum4": 2.3195,
    "ldsc_nsnp_merge_refpanel_ld": 1281483,
    "ldsc_nsnp_merge_regression_ld": 1281483,
    "ldsc_observed_scale_h2_beta": 0.1235,
    "ldsc_observed_scale_h2_se": 0.0589,
    "ldsc_intercept_beta": 0.9915,
    "ldsc_intercept_se": 0.0071,
    "ldsc_lambda_gc": 1.068,
    "ldsc_mean_chisq": 1.0097,
    "ldsc_ratio": -0.8763
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq FALSE
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 TRUE
r2_sum3 TRUE
r2_sum4 TRUE

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 58 0 10877936 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.598638e+00 5.745666e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.911383e+07 5.624931e+07 828.0000000 3.287294e+07 6.988889e+07 1.148258e+08 2.492251e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 5.000000e-06 3.011300e-03 -0.1042320 -9.838000e-04 -5.893000e-04 2.482000e-04 1.922350e-01 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.143000e-03 2.068600e-03 0.0004786 6.020000e-04 1.156100e-03 3.086500e-03 2.395360e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 5.768961e-01 2.784804e-01 0.0000000 3.638874e-01 6.425161e-01 8.136610e-01 1.000000e+00 ▅▅▅▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 5.768796e-01 2.784912e-01 0.0000000 3.638589e-01 6.425026e-01 8.136551e-01 1.000000e+00 ▅▅▅▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.820865e-01 2.503832e-01 0.0010009 6.878700e-03 5.191440e-02 2.739880e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 356865 0.9671937 NA NA NA NA NA 1.877709e-01 2.439191e-01 0.0000000 5.191700e-03 7.468050e-02 2.873400e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 7.637000e+03 0.000000e+00 7637.0000000 7.637000e+03 7.637000e+03 7.637000e+03 7.637000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 693731 rs12238997 A G 0.0000158 0.0008009 0.9842240 0.9842238 0.1169260 0.1417730 7637
1 717587 rs144155419 G A -0.0012380 0.0022716 0.5857685 0.5857516 0.0143862 0.0045926 7637
1 730087 rs148120343 T C 0.0014529 0.0010974 0.1855658 0.1855275 0.0554733 0.0127796 7637
1 731718 rs142557973 T C 0.0000545 0.0007551 0.9424871 0.9424849 0.1216580 0.1543530 7637
1 734349 rs141242758 T C 0.0000597 0.0007553 0.9369841 0.9369819 0.1215130 0.1525560 7637
1 740284 rs61770167 C T -0.0011339 0.0034122 0.7396768 0.7396688 0.0058556 0.0023962 7637
1 742813 rs112573343 C T -0.0016499 0.0063452 0.7948500 0.7948425 0.0015525 0.1030350 7637
1 753405 rs3115860 C A 0.0000583 0.0007177 0.9352469 0.9352445 0.8706760 0.7517970 7637
1 753541 rs2073813 G A -0.0000523 0.0007191 0.9419690 0.9419675 0.1288330 0.3019170 7637
1 754182 rs3131969 A G 0.0000629 0.0007174 0.9301040 0.9301019 0.8703180 0.6785140 7637
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219387 rs9616832 T C -0.0009235 0.0009222 0.3166547 0.3166235 0.0729806 0.0654952 7637
22 51219704 rs147475742 G A -0.0010227 0.0012630 0.4180864 0.4180574 0.0418225 0.0473243 7637
22 51219766 rs182321900 C T -0.0011110 0.0058259 0.8487700 0.8487651 0.0014546 NA 7637
22 51220088 rs566371895 G A -0.0009711 0.0039269 0.8046880 0.8046807 0.0039843 0.0003994 7637
22 51220146 rs868950473 C T -0.0011529 0.0058736 0.8443949 0.8443897 0.0015139 NA 7637
22 51221731 rs115055839 T C -0.0009177 0.0009216 0.3193979 0.3193664 0.0728101 0.0625000 7637
22 51223637 rs375798137 G A -0.0010567 0.0011237 0.3470843 0.3470558 0.0540289 0.0788738 7637
22 51226692 rs150189434 G A -0.0010216 0.0062228 0.8695969 0.8695921 0.0013983 0.0155751 7637
22 51229805 rs9616985 T C -0.0009234 0.0009262 0.3188027 0.3187710 0.0727671 0.0730831 7637
22 51237063 rs3896457 T C -0.0001423 0.0005799 0.8061150 0.8061088 0.2968410 0.2050720 7637

bcf preview

1   693731  rs12238997  A   G   .   PASS    AF=0.116926 ES:SE:LP:AF:SS:ID   1.58371e-05:0.000800911:0.00690605:0.116926:7637:rs12238997
1   717587  rs144155419 G   A   .   PASS    AF=0.0143862    ES:SE:LP:AF:SS:ID   -0.00123805:0.00227164:0.232274:0.0143862:7637:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0554733    ES:SE:LP:AF:SS:ID   0.00145289:0.00109741:0.731502:0.0554733:7637:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121658 ES:SE:LP:AF:SS:ID   5.44816e-05:0.000755147:0.0257246:0.121658:7637:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121513 ES:SE:LP:AF:SS:ID   5.97175e-05:0.000755308:0.0282678:0.121513:7637:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00585559   ES:SE:LP:AF:SS:ID   -0.00113386:0.00341224:0.130958:0.00585559:7637:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0015525    ES:SE:LP:AF:SS:ID   -0.00164994:0.00634525:0.0997148:0.0015525:7637:rs112573343
1   753405  rs3115860   C   A   .   PASS    AF=0.870676 ES:SE:LP:AF:SS:ID   5.83147e-05:0.000717734:0.0290737:0.870676:7637:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.128833 ES:SE:LP:AF:SS:ID   -5.23496e-05:0.000719115:0.0259634:0.128833:7637:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.870318 ES:SE:LP:AF:SS:ID   6.29305e-05:0.00071743:0.0314685:0.870318:7637:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870409 ES:SE:LP:AF:SS:ID   6.33632e-05:0.000717522:0.031688:0.870409:7637:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870037 ES:SE:LP:AF:SS:ID   6.29983e-05:0.000717389:0.0315054:0.870037:7637:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00465304   ES:SE:LP:AF:SS:ID   -0.00121172:0.00357629:0.133858:0.00465304:7637:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00464711   ES:SE:LP:AF:SS:ID   -0.00120897:0.00358472:0.133162:0.00464711:7637:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00590897   ES:SE:LP:AF:SS:ID   -0.00100386:0.00335874:0.116316:0.00590897:7637:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870329 ES:SE:LP:AF:SS:ID   6.25684e-05:0.000716131:0.0313396:0.870329:7637:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.87002  ES:SE:LP:AF:SS:ID   6.58506e-05:0.00071407:0.0331419:0.87002:7637:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869421 ES:SE:LP:AF:SS:ID   7.41759e-05:0.000713913:0.0375118:0.869421:7637:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870219 ES:SE:LP:AF:SS:ID   6.49611e-05:0.00071469:0.0326491:0.870219:7637:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870219 ES:SE:LP:AF:SS:ID   6.48987e-05:0.000714738:0.0326144:0.870219:7637:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870222 ES:SE:LP:AF:SS:ID   6.49164e-05:0.000714755:0.0326229:0.870222:7637:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870396 ES:SE:LP:AF:SS:ID   6.19672e-05:0.000716546:0.0310097:0.870396:7637:rs3131954
1   761732  rs2286139   C   T   .   PASS    AF=0.867743 ES:SE:LP:AF:SS:ID   0.000107206:0.000713452:0.0552406:0.867743:7637:rs2286139
1   766007  rs61768174  A   C   .   PASS    AF=0.106958 ES:SE:LP:AF:SS:ID   0.000185822:0.00078971:0.0893868:0.106958:7637:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.763932 ES:SE:LP:AF:SS:ID   -0.00013659:0.000568208:0.0914951:0.763932:7637:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105257 ES:SE:LP:AF:SS:ID   0.000356381:0.000791314:0.185447:0.105257:7637:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00692766   ES:SE:LP:AF:SS:ID   -0.000903385:0.00331637:0.104953:0.00692766:7637:rs12562811
1   769223  rs60320384  C   G   .   PASS    AF=0.128651 ES:SE:LP:AF:SS:ID   -5.32804e-05:0.000718056:0.0264787:0.128651:7637:rs60320384
1   769224  rs141644775 G   A   .   PASS    AF=0.00143239   ES:SE:LP:AF:SS:ID   -0.00137859:0.00631059:0.082453:0.00143239:7637:rs141644775
1   770181  rs146076599 A   G   .   PASS    AF=0.00907328   ES:SE:LP:AF:SS:ID   -0.00117926:0.00260275:0.186751:0.00907328:7637:rs146076599
1   770377  rs112563271 A   T   .   PASS    AF=0.00692321   ES:SE:LP:AF:SS:ID   -0.000881782:0.00331711:0.102165:0.00692321:7637:rs112563271
1   771823  rs2977605   T   C   .   PASS    AF=0.869934 ES:SE:LP:AF:SS:ID   6.40686e-05:0.00071507:0.0321671:0.869934:7637:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.128709 ES:SE:LP:AF:SS:ID   -5.42679e-05:0.000717281:0.027014:0.128709:7637:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.870112 ES:SE:LP:AF:SS:ID   6.64348e-05:0.000714931:0.033405:0.870112:7637:rs2905039
1   774736  rs28830877  A   C   .   PASS    AF=0.998797 ES:SE:LP:AF:SS:ID   0.00140235:0.00735398:0.071209:0.998797:7637:rs28830877
1   776556  rs151160018 C   T   .   PASS    AF=0.00851871   ES:SE:LP:AF:SS:ID   -0.00112087:0.00264453:0.17283:0.00851871:7637:rs151160018
1   777122  rs2980319   A   T   .   PASS    AF=0.871122 ES:SE:LP:AF:SS:ID   5.33508e-05:0.000716782:0.0265632:0.871122:7637:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.0961319    ES:SE:LP:AF:SS:ID   0.000476502:0.000835206:0.245391:0.0961319:7637:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.127871 ES:SE:LP:AF:SS:ID   -4.07912e-05:0.000718545:0.020119:0.127871:7637:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.127984 ES:SE:LP:AF:SS:ID   -4.33435e-05:0.000717157:0.0214506:0.127984:7637:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.870455 ES:SE:LP:AF:SS:ID   6.15115e-05:0.000714921:0.0308465:0.870455:7637:rs2977612
1   781367  rs149821290 A   C   .   PASS    AF=0.00989772   ES:SE:LP:AF:SS:ID   0.00581701:0.00261462:1.58297:0.00989772:7637:rs149821290
1   781845  rs61768199  A   G   .   PASS    AF=0.1044   ES:SE:LP:AF:SS:ID   0.000229259:0.000799128:0.111143:0.1044:7637:rs61768199
1   782721  rs185280546 G   A   .   PASS    AF=0.0143713    ES:SE:LP:AF:SS:ID   0.00366653:0.00219722:1.02129:0.0143713:7637:rs185280546
1   782981  rs6594026   C   T   .   PASS    AF=0.128338 ES:SE:LP:AF:SS:ID   -4.58491e-05:0.000716675:0.0227374:0.128338:7637:rs6594026
1   783193  rs145767270 G   C   .   PASS    AF=0.0143639    ES:SE:LP:AF:SS:ID   0.00357764:0.00219649:0.985492:0.0143639:7637:rs145767270
1   783194  rs138555831 G   T   .   PASS    AF=0.0143713    ES:SE:LP:AF:SS:ID   0.00357553:0.00219592:0.985009:0.0143713:7637:rs138555831
1   783711  rs184266993 G   A   .   PASS    AF=0.00541372   ES:SE:LP:AF:SS:ID   -0.00117466:0.00354976:0.130347:0.00541372:7637:rs184266993
1   785050  rs2905062   G   A   .   PASS    AF=0.87014  ES:SE:LP:AF:SS:ID   6.12749e-05:0.000715065:0.0307174:0.87014:7637:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.87009  ES:SE:LP:AF:SS:ID   6.28509e-05:0.00071549:0.0315152:0.87009:7637:rs2980300