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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    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_2784.vcf.gz --id UKB-b:9509 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_2784.txt.gz --cohort_cases 205516 --cohort_controls 44924 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
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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/public/UKB-b-9509/UKB-b-9509_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9509/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:38 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9509/UKB-b-9509_data.vcf.gz ...
Read summary statistics for 9519492 SNPs.
Dropped 11771 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1288420 SNPs remain.
After merging with regression SNP LD, 1288420 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0205 (0.0023)
Lambda GC: 1.1423
Mean Chi^2: 1.1402
Intercept: 1.0399 (0.0071)
Ratio: 0.2848 (0.0505)
Analysis finished at Thu Oct 17 14:44:48 2019
Total time elapsed: 2.0m:9.87s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9492,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "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": 135456,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1288420,
    "ldsc_nsnp_merge_regression_ld": 1288420,
    "ldsc_observed_scale_h2_beta": 0.0205,
    "ldsc_observed_scale_h2_se": 0.0023,
    "ldsc_intercept_beta": 1.0399,
    "ldsc_intercept_se": 0.0071,
    "ldsc_lambda_gc": 1.1423,
    "ldsc_mean_chisq": 1.1402,
    "ldsc_ratio": 0.2846
}

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 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 logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 9507781 0 NA NA 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 NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 9519492 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.629018e+00 5.751543e+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 NA NA 7.883506e+07 5.630662e+07 828.0000000 3.254473e+07 6.942290e+07 1.145654e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.440000e-05 4.466400e-03 -0.0741897 -1.540300e-03 6.300000e-06 1.563500e-03 7.317100e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.326600e-03 2.803400e-03 0.0010441 1.266000e-03 2.046600e-03 4.522000e-03 3.703800e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.837769e-01 2.929505e-01 0.0000004 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.837765e-01 2.929239e-01 0.0000003 2.258884e-01 4.775306e-01 7.376735e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.094531e-01 2.572885e-01 0.0017040 1.563200e-02 8.640600e-02 3.277202e-01 9.982960e-01 ▇▂▁▁▁
numeric AF_reference 135456 0.9857707 NA NA NA NA NA NA NA 2.112126e-01 2.489939e-01 0.0000000 1.337860e-02 1.060300e-01 3.290730e-01 1.000000e+00 ▇▂▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C 0.0008097 0.0019245 0.6700003 0.6739669 0.623371 0.7821490 NA
1 54676 rs2462492 C T 0.0013166 0.0019027 0.4899999 0.4889487 0.400972 NA NA
1 86028 rs114608975 T C -0.0007784 0.0030529 0.8000000 0.7987535 0.103450 0.0277556 NA
1 91536 rs6702460 G T -0.0003987 0.0018746 0.8300000 0.8315843 0.457043 0.4207270 NA
1 234313 rs8179466 C T 0.0010322 0.0037027 0.7800007 0.7804137 0.074437 NA NA
1 534192 rs6680723 C T 0.0005097 0.0021423 0.8100000 0.8119460 0.241207 NA NA
1 546697 rs12025928 A G 0.0027765 0.0026728 0.2999998 0.2989146 0.913549 NA NA
1 693731 rs12238997 A G 0.0000941 0.0017933 0.9599999 0.9581308 0.116696 0.1417730 NA
1 705882 rs72631875 G A -0.0033424 0.0026327 0.2000000 0.2042484 0.067086 0.0315495 NA
1 706368 rs55727773 A G -0.0013054 0.0013298 0.3300000 0.3262534 0.515101 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0038696 0.0027941 0.1700000 0.1660768 0.041875 0.0473243 NA
22 51219766 rs182321900 C T 0.0151633 0.0132409 0.2500000 0.2521319 0.001878 NA NA
22 51220146 rs868950473 C T 0.0205412 0.0131160 0.1199999 0.1173211 0.001921 NA NA
22 51221190 rs369304721 G A -0.0044292 0.0027911 0.1100001 0.1125413 0.049626 NA NA
22 51221731 rs115055839 T C -0.0023642 0.0020858 0.2599998 0.2570029 0.073199 0.0625000 NA
22 51222100 rs114553188 G T -0.0009421 0.0024519 0.6999999 0.7008102 0.054653 0.0880591 NA
22 51223637 rs375798137 G A -0.0008321 0.0024636 0.7400005 0.7355452 0.054290 0.0788738 NA
22 51229805 rs9616985 T C -0.0024517 0.0020931 0.2399999 0.2414673 0.073071 0.0730831 NA
22 51232488 rs376461333 A G 0.0017123 0.0049305 0.7300002 0.7283739 0.020041 NA NA
22 51237063 rs3896457 T C -0.0011386 0.0012790 0.3700002 0.3733269 0.297893 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623371 ES:SE:LP:AF:ID  0.000809652:0.00192449:0.173925:0.623371:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400972 ES:SE:LP:AF:ID  0.00131662:0.00190268:0.309804:0.400972:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10345  ES:SE:LP:AF:ID  -0.000778359:0.00305286:0.09691:0.10345:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.457043 ES:SE:LP:AF:ID  -0.000398667:0.00187458:0.0809219:0.457043:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074437 ES:SE:LP:AF:ID  0.00103223:0.00370267:0.107905:0.074437:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241207 ES:SE:LP:AF:ID  0.000509693:0.00214232:0.091515:0.241207:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913549 ES:SE:LP:AF:ID  0.00277646:0.00267285:0.522879:0.913549:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116696 ES:SE:LP:AF:ID  9.41466e-05:0.00179329:0.0177288:0.116696:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067086 ES:SE:LP:AF:ID  -0.00334237:0.00263274:0.69897:0.067086:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515101 ES:SE:LP:AF:ID  -0.0013054:0.00132975:0.481486:0.515101:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032863 ES:SE:LP:AF:ID  0.00512005:0.00335965:0.886057:0.032863:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03644  ES:SE:LP:AF:ID  0.00413636:0.00305398:0.744727:0.03644:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036548 ES:SE:LP:AF:ID  0.00431946:0.00304304:0.79588:0.036548:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036239 ES:SE:LP:AF:ID  0.00446048:0.00306549:0.823909:0.036239:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016354 ES:SE:LP:AF:ID  0.00202027:0.0047116:0.173925:0.016354:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036771 ES:SE:LP:AF:ID  0.00415293:0.00303168:0.769551:0.036771:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.036863 ES:SE:LP:AF:ID  0.00408017:0.00302155:0.744727:0.036863:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101107 ES:SE:LP:AF:ID  -0.00298997:0.00219485:0.769551:0.101107:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959322 ES:SE:LP:AF:ID  -0.00391767:0.00291386:0.744727:0.959322:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03142  ES:SE:LP:AF:ID  0.00300271:0.00525831:0.244125:0.03142:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.0534   ES:SE:LP:AF:ID  0.00318779:0.00418383:0.346787:0.0534:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036407 ES:SE:LP:AF:ID  0.00407775:0.00303929:0.744727:0.036407:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036737 ES:SE:LP:AF:ID  0.00345885:0.00301157:0.60206:0.036737:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843057 ES:SE:LP:AF:ID  -0.00163487:0.00155621:0.537602:0.843057:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056028 ES:SE:LP:AF:ID  -0.00104496:0.00251795:0.167491:0.056028:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122688 ES:SE:LP:AF:ID  0.000620151:0.00170089:0.142668:0.122688:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025579 ES:SE:LP:AF:ID  0.000297246:0.00419999:0.0268721:0.025579:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121915 ES:SE:LP:AF:ID  0.000551085:0.00170162:0.124939:0.121915:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132572 ES:SE:LP:AF:ID  0.0010646:0.00167823:0.275724:0.132572:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01113  ES:SE:LP:AF:ID  -0.000727805:0.00610893:0.0409586:0.01113:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005777 ES:SE:LP:AF:ID  0.00544951:0.00780823:0.309804:0.005777:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.002239 ES:SE:LP:AF:ID  -0.0108467:0.0133642:0.376751:0.002239:rs112573343
1   752478  rs146277091 G   A   .   PASS    AF=0.036645 ES:SE:LP:AF:ID  0.00330322:0.00298156:0.568636:0.036645:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838737 ES:SE:LP:AF:ID  -0.00196651:0.00150624:0.721246:0.838737:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838366 ES:SE:LP:AF:ID  -0.0021235:0.00150477:0.79588:0.838366:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869406 ES:SE:LP:AF:ID  -0.0012747:0.00161316:0.366532:0.869406:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130243 ES:SE:LP:AF:ID  0.00156032:0.00161681:0.481486:0.130243:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037114 ES:SE:LP:AF:ID  0.00297943:0.00293227:0.508638:0.037114:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037377 ES:SE:LP:AF:ID  0.00301869:0.00291267:0.522879:0.037377:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868743 ES:SE:LP:AF:ID  -0.00145485:0.00161023:0.431798:0.868743:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868817 ES:SE:LP:AF:ID  -0.00145187:0.0016108:0.431798:0.868817:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037325 ES:SE:LP:AF:ID  0.00302462:0.00292564:0.522879:0.037325:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868743 ES:SE:LP:AF:ID  -0.0014585:0.00161018:0.431798:0.868743:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005082 ES:SE:LP:AF:ID  0.0104209:0.00832211:0.677781:0.005082:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00505  ES:SE:LP:AF:ID  0.0105684:0.00834181:0.677781:0.00505:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.837814 ES:SE:LP:AF:ID  -0.00206659:0.00150055:0.769551:0.837814:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037338 ES:SE:LP:AF:ID  0.00297167:0.00293003:0.508638:0.037338:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838451 ES:SE:LP:AF:ID  -0.00197763:0.00150477:0.721246:0.838451:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013868 ES:SE:LP:AF:ID  0.00255154:0.00523418:0.200659:0.013868:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005572 ES:SE:LP:AF:ID  -0.00415716:0.00809161:0.21467:0.005572:rs184270342