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-312/ukb-a-312.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-312/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 01:55:19 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-a-import/processed/ukb-a-312/ukb-a-312.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: 0.0331 (0.0037)
Lambda GC: 1.0886
Mean Chi^2: 1.0976
Intercept: 1.0079 (0.0067)
Ratio: 0.0808 (0.0686)
Analysis finished at Sun Feb 16 01:57:06 2020
Total time elapsed: 1.0m:47.01s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9533,
    "inflation_factor": 1.0521,
    "mean_EFFECT": -0.0001,
    "n": 137364,
    "n_snps": 10877936,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 136953.0161,
    "ratio_se_n": 0.9985,
    "mean_diff": 0,
    "ratio_diff": 23.6867,
    "sd_y_est1": 1.661,
    "sd_y_est2": 1.6586,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1281483,
    "ldsc_nsnp_merge_regression_ld": 1281483,
    "ldsc_observed_scale_h2_beta": 0.0331,
    "ldsc_observed_scale_h2_se": 0.0037,
    "ldsc_intercept_beta": 1.0079,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.0886,
    "ldsc_mean_chisq": 1.0976,
    "ldsc_ratio": 0.0809
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique FALSE
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 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 1.00000e+00 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 8.28000e+02 3.287294e+07 6.988889e+07 1.148258e+08 2.492251e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -8.430000e-05 3.781970e-02 -4.38166e-01 -1.051350e-02 -5.840000e-05 1.034970e-02 4.943120e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.730270e-02 2.587270e-02 6.25290e-03 7.736000e-03 1.485480e-02 3.969840e-02 1.468570e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.915455e-01 2.912829e-01 4.00000e-07 2.368460e-01 4.890463e-01 7.437774e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.915443e-01 2.912836e-01 4.00000e-07 2.368438e-01 4.890452e-01 7.437767e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.820865e-01 2.503832e-01 1.00090e-03 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 0.00000e+00 5.191700e-03 7.468050e-02 2.873400e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.373640e+05 0.000000e+00 1.37364e+05 1.373640e+05 1.373640e+05 1.373640e+05 1.373640e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 693731 rs12238997 A G 0.0012092 0.0104536 0.9079090 0.9079094 0.1169260 0.1417730 137364
1 717587 rs144155419 G A -0.0020927 0.0281588 0.9407571 0.9407570 0.0143862 0.0045926 137364
1 730087 rs148120343 T C -0.0181436 0.0145533 0.2125079 0.2125075 0.0554733 0.0127796 137364
1 731718 rs142557973 T C -0.0004698 0.0099208 0.9622300 0.9622295 0.1216580 0.1543530 137364
1 734349 rs141242758 T C -0.0001972 0.0099274 0.9841490 0.9841493 0.1215130 0.1525560 137364
1 740284 rs61770167 C T 0.0387402 0.0450297 0.3896117 0.3896096 0.0058556 0.0023962 137364
1 742813 rs112573343 C T 0.0595388 0.0839960 0.4784318 0.4784306 0.0015525 0.1030350 137364
1 753405 rs3115860 C A -0.0031586 0.0094202 0.7374015 0.7374006 0.8706760 0.7517970 137364
1 753541 rs2073813 G A 0.0024362 0.0094460 0.7964800 0.7964805 0.1288330 0.3019170 137364
1 754182 rs3131969 A G -0.0031861 0.0094102 0.7349250 0.7349242 0.8703180 0.6785140 137364
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219387 rs9616832 T C 0.0208975 0.0122230 0.0873253 0.0873238 0.0729806 0.0654952 137364
22 51219704 rs147475742 G A 0.0427932 0.0163533 0.0088769 0.0088760 0.0418225 0.0473243 137364
22 51219766 rs182321900 C T 0.1027000 0.0820269 0.2105620 0.2105596 0.0014546 NA 137364
22 51220088 rs566371895 G A 0.0034936 0.0555625 0.9498650 0.9498645 0.0039843 0.0003994 137364
22 51220146 rs868950473 C T 0.1077580 0.0811720 0.1843372 0.1843345 0.0015139 NA 137364
22 51221731 rs115055839 T C 0.0208447 0.0122351 0.0884423 0.0884408 0.0728101 0.0625000 137364
22 51223637 rs375798137 G A -0.0027442 0.0142390 0.8471759 0.8471750 0.0540289 0.0788738 137364
22 51226692 rs150189434 G A 0.1269260 0.0845519 0.1333171 0.1333140 0.0013983 0.0155751 137364
22 51229805 rs9616985 T C 0.0199847 0.0122810 0.1036800 0.1036764 0.0727671 0.0730831 137364
22 51237063 rs3896457 T C 0.0039390 0.0074145 0.5952453 0.5952435 0.2968410 0.2050720 137364

bcf preview

1   693731  rs12238997  A   G   .   PASS    AF=0.116926 ES:SE:LP:AF:SS:ID   0.00120923:0.0104536:0.0419577:0.116926:137364:rs12238997
1   717587  rs144155419 G   A   .   PASS    AF=0.0143862    ES:SE:LP:AF:SS:ID   -0.00209272:0.0281588:0.0265225:0.0143862:137364:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0554733    ES:SE:LP:AF:SS:ID   -0.0181436:0.0145533:0.672625:0.0554733:137364:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121658 ES:SE:LP:AF:SS:ID   -0.000469809:0.00992078:0.0167211:0.121658:137364:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121513 ES:SE:LP:AF:SS:ID   -0.000197229:0.00992735:0.00693914:0.121513:137364:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00585559   ES:SE:LP:AF:SS:ID   0.0387402:0.0450297:0.409368:0.00585559:137364:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0015525    ES:SE:LP:AF:SS:ID   0.0595388:0.083996:0.32018:0.0015525:137364:rs112573343
1   753405  rs3115860   C   A   .   PASS    AF=0.870676 ES:SE:LP:AF:SS:ID   -0.00315857:0.0094202:0.132296:0.870676:137364:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.128833 ES:SE:LP:AF:SS:ID   0.00243618:0.00944605:0.0988251:0.128833:137364:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.870318 ES:SE:LP:AF:SS:ID   -0.00318613:0.0094102:0.133757:0.870318:137364:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870409 ES:SE:LP:AF:SS:ID   -0.00356095:0.00941427:0.15166:0.870409:137364:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870037 ES:SE:LP:AF:SS:ID   -0.00317609:0.0094101:0.133284:0.870037:137364:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00465304   ES:SE:LP:AF:SS:ID   0.00504848:0.047825:0.0381377:0.00465304:137364:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00464711   ES:SE:LP:AF:SS:ID   0.00157868:0.0479644:0.0115552:0.00464711:137364:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00590897   ES:SE:LP:AF:SS:ID   0.0675964:0.0473872:0.813227:0.00590897:137364:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870329 ES:SE:LP:AF:SS:ID   -0.0027917:0.00939363:0.115589:0.870329:137364:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.87002  ES:SE:LP:AF:SS:ID   -0.00343355:0.00937077:0.146266:0.87002:137364:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869421 ES:SE:LP:AF:SS:ID   -0.00374575:0.00936034:0.161762:0.869421:137364:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870219 ES:SE:LP:AF:SS:ID   -0.00329101:0.0093781:0.139276:0.870219:137364:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870219 ES:SE:LP:AF:SS:ID   -0.00328829:0.00937873:0.139135:0.870219:137364:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870222 ES:SE:LP:AF:SS:ID   -0.00329909:0.00937905:0.139647:0.870222:137364:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870396 ES:SE:LP:AF:SS:ID   -0.00273338:0.00940287:0.112786:0.870396:137364:rs3131954
1   761732  rs2286139   C   T   .   PASS    AF=0.867743 ES:SE:LP:AF:SS:ID   -0.00246763:0.00935819:0.101263:0.867743:137364:rs2286139
1   766007  rs61768174  A   C   .   PASS    AF=0.106958 ES:SE:LP:AF:SS:ID   0.00181223:0.0104088:0.0646021:0.106958:137364:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.763932 ES:SE:LP:AF:SS:ID   0.00293312:0.00742052:0.159491:0.763932:137364:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105257 ES:SE:LP:AF:SS:ID   -0.00927762:0.0102555:0.436932:0.105257:137364:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00692766   ES:SE:LP:AF:SS:ID   0.0168094:0.0380317:0.181444:0.00692766:137364:rs12562811
1   769223  rs60320384  C   G   .   PASS    AF=0.128651 ES:SE:LP:AF:SS:ID   0.00217552:0.00943019:0.0874851:0.128651:137364:rs60320384
1   769224  rs141644775 G   A   .   PASS    AF=0.00143239   ES:SE:LP:AF:SS:ID   -0.163596:0.0882132:1.19611:0.00143239:137364:rs141644775
1   770181  rs146076599 A   G   .   PASS    AF=0.00907328   ES:SE:LP:AF:SS:ID   0.0353445:0.0359064:0.48819:0.00907328:137364:rs146076599
1   770377  rs112563271 A   T   .   PASS    AF=0.00692321   ES:SE:LP:AF:SS:ID   0.0141813:0.0381944:0.148485:0.00692321:137364:rs112563271
1   771823  rs2977605   T   C   .   PASS    AF=0.869934 ES:SE:LP:AF:SS:ID   -0.00302715:0.00938825:0.12661:0.869934:137364:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.128709 ES:SE:LP:AF:SS:ID   0.00253136:0.00942678:0.103312:0.128709:137364:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.870112 ES:SE:LP:AF:SS:ID   -0.00311395:0.00938912:0.13068:0.870112:137364:rs2905039
1   774736  rs28830877  A   C   .   PASS    AF=0.998797 ES:SE:LP:AF:SS:ID   0.0233313:0.0968942:0.0916667:0.998797:137364:rs28830877
1   776556  rs151160018 C   T   .   PASS    AF=0.00851871   ES:SE:LP:AF:SS:ID   0.0104225:0.035029:0.115739:0.00851871:137364:rs151160018
1   777122  rs2980319   A   T   .   PASS    AF=0.871122 ES:SE:LP:AF:SS:ID   -0.00235793:0.00940616:0.0957921:0.871122:137364:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.0961319    ES:SE:LP:AF:SS:ID   -0.0128402:0.01088:0.623544:0.0961319:137364:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.127871 ES:SE:LP:AF:SS:ID   0.00229115:0.00943823:0.0924828:0.127871:137364:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.127984 ES:SE:LP:AF:SS:ID   0.00237549:0.00942636:0.0963474:0.127984:137364:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.870455 ES:SE:LP:AF:SS:ID   -0.00238637:0.00938974:0.0972451:0.870455:137364:rs2977612
1   781367  rs149821290 A   C   .   PASS    AF=0.00989772   ES:SE:LP:AF:SS:ID   -0.00345151:0.0336587:0.0370036:0.00989772:137364:rs149821290
1   781845  rs61768199  A   G   .   PASS    AF=0.1044   ES:SE:LP:AF:SS:ID   0.00213476:0.0105526:0.0758841:0.1044:137364:rs61768199
1   782721  rs185280546 G   A   .   PASS    AF=0.0143713    ES:SE:LP:AF:SS:ID   -0.0209653:0.0285943:0.334007:0.0143713:137364:rs185280546
1   782981  rs6594026   C   T   .   PASS    AF=0.128338 ES:SE:LP:AF:SS:ID   0.00244461:0.00943014:0.0993838:0.128338:137364:rs6594026
1   783193  rs145767270 G   C   .   PASS    AF=0.0143639    ES:SE:LP:AF:SS:ID   -0.023583:0.0286822:0.386207:0.0143639:137364:rs145767270
1   783194  rs138555831 G   T   .   PASS    AF=0.0143713    ES:SE:LP:AF:SS:ID   -0.0236511:0.0286786:0.387697:0.0143713:137364:rs138555831
1   783711  rs184266993 G   A   .   PASS    AF=0.00541372   ES:SE:LP:AF:SS:ID   0.0178836:0.0453515:0.159056:0.00541372:137364:rs184266993
1   785050  rs2905062   G   A   .   PASS    AF=0.87014  ES:SE:LP:AF:SS:ID   -0.0024748:0.00939121:0.101194:0.87014:137364:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.87009  ES:SE:LP:AF:SS:ID   -0.00262615:0.00939721:0.107966:0.87009:137364:rs2980300