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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    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
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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_100520.vcf.gz --id UKB-b:2966 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_100520.txt.gz --cohort_controls 64943 --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-2966/UKB-b-2966_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2966/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:12 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2966/UKB-b-2966_data.vcf.gz ...
Read summary statistics for 8624976 SNPs.
Dropped 7372 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, 1285749 SNPs remain.
After merging with regression SNP LD, 1285749 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0166 (0.0076)
Lambda GC: 1.013
Mean Chi^2: 1.0149
Intercept: 0.9931 (0.0067)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:44:45 2019
Total time elapsed: 1.0m:33.52s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9462,
    "inflation_factor": 1,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "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": 83093,
    "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": 1285749,
    "ldsc_nsnp_merge_regression_ld": 1285749,
    "ldsc_observed_scale_h2_beta": 0.0166,
    "ldsc_observed_scale_h2_se": 0.0076,
    "ldsc_intercept_beta": 0.9931,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.013,
    "ldsc_mean_chisq": 1.0149,
    "ldsc_ratio": -0.4631
}

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 1.000000 3 58 0 8617638 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 8624976 0.000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA NA NA 8.650341e+00 5.760980e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.877019e+07 5.637175e+07 828.0000000 3.238533e+07 6.929209e+07 1.145691e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA -1.900000e-05 7.366300e-03 -0.0681194 -3.112900e-03 -4.700000e-05 3.002800e-03 9.540810e-02 ▁▃▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 6.063000e-03 4.138600e-03 0.0024080 2.835700e-03 4.181000e-03 8.195900e-03 4.150750e-02 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.980393e-01 2.891823e-01 0.0000000 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.980378e-01 2.891547e-01 0.0000000 2.470307e-01 4.972062e-01 7.485123e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA NA NA 2.291177e-01 2.594884e-01 0.0053900 2.519000e-02 1.138980e-01 3.626180e-01 9.946100e-01 ▇▂▁▁▁
numeric AF_reference 83093 0.990366 NA NA NA NA NA NA NA 2.288667e-01 2.514592e-01 0.0000000 2.316290e-02 1.303910e-01 3.596250e-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 -0.0045796 0.0044377 0.2999998 0.3020875 0.623804 0.7821490 NA
1 54676 rs2462492 C T -0.0065021 0.0044248 0.1400000 0.1417024 0.399150 NA NA
1 86028 rs114608975 T C 0.0100214 0.0070434 0.1499999 0.1547921 0.103540 0.0277556 NA
1 91536 rs6702460 G T -0.0058061 0.0043521 0.1800002 0.1821781 0.455906 0.4207270 NA
1 234313 rs8179466 C T 0.0033677 0.0086066 0.6999999 0.6955850 0.074456 NA NA
1 534192 rs6680723 C T -0.0033700 0.0049567 0.5000000 0.4965854 0.242057 NA NA
1 546697 rs12025928 A G -0.0000599 0.0061505 0.9900000 0.9922298 0.912867 NA NA
1 693731 rs12238997 A G -0.0030267 0.0041334 0.4600002 0.4640174 0.117294 0.1417730 NA
1 705882 rs72631875 G A 0.0030220 0.0060250 0.6200004 0.6159664 0.067689 0.0315495 NA
1 706368 rs55727773 A G -0.0042266 0.0030679 0.1700000 0.1683047 0.513298 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0001024 0.0037316 0.9800000 0.9781100 0.136312 0.2052720 NA
22 51219387 rs9616832 T C -0.0058026 0.0048639 0.2300001 0.2328651 0.071789 0.0654952 NA
22 51219704 rs147475742 G A -0.0047086 0.0064708 0.4700002 0.4668141 0.041179 0.0473243 NA
22 51221190 rs369304721 G A -0.0062026 0.0065162 0.3400001 0.3411609 0.048366 NA NA
22 51221731 rs115055839 T C -0.0056940 0.0048649 0.2399999 0.2418331 0.071339 0.0625000 NA
22 51222100 rs114553188 G T 0.0034414 0.0056369 0.5400003 0.5415207 0.054855 0.0880591 NA
22 51223637 rs375798137 G A 0.0028454 0.0056664 0.6200004 0.6155636 0.054475 0.0788738 NA
22 51229805 rs9616985 T C -0.0057501 0.0048800 0.2399999 0.2386702 0.071244 0.0730831 NA
22 51232488 rs376461333 A G 0.0015568 0.0112385 0.8900000 0.8898278 0.020462 NA NA
22 51237063 rs3896457 T C 0.0022534 0.0029460 0.4400003 0.4443300 0.298401 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623804 ES:SE:LP:AF:ID  -0.00457955:0.00443769:0.522879:0.623804:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.39915  ES:SE:LP:AF:ID  -0.00650213:0.00442478:0.853872:0.39915:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10354  ES:SE:LP:AF:ID  0.0100214:0.0070434:0.823909:0.10354:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455906 ES:SE:LP:AF:ID  -0.00580607:0.00435212:0.744727:0.455906:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074456 ES:SE:LP:AF:ID  0.00336766:0.00860662:0.154902:0.074456:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.242057 ES:SE:LP:AF:ID  -0.00336995:0.00495674:0.30103:0.242057:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912867 ES:SE:LP:AF:ID  -5.98981e-05:0.00615052:0.00436481:0.912867:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117294 ES:SE:LP:AF:ID  -0.00302668:0.00413341:0.337242:0.117294:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067689 ES:SE:LP:AF:ID  0.00302199:0.006025:0.207608:0.067689:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.513298 ES:SE:LP:AF:ID  -0.0042266:0.00306793:0.769551:0.513298:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03368  ES:SE:LP:AF:ID  0.00824797:0.00764666:0.552842:0.03368:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037461 ES:SE:LP:AF:ID  0.00606066:0.00693515:0.420216:0.037461:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037647 ES:SE:LP:AF:ID  0.00571257:0.00689886:0.387216:0.037647:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037224 ES:SE:LP:AF:ID  0.00452113:0.0069619:0.283997:0.037224:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016283 ES:SE:LP:AF:ID  -0.00925057:0.0109202:0.39794:0.016283:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037864 ES:SE:LP:AF:ID  0.00558779:0.00687528:0.376751:0.037864:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037958 ES:SE:LP:AF:ID  0.00535881:0.00685347:0.366532:0.037958:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.102744 ES:SE:LP:AF:ID  0.0099923:0.00500633:1.33724:0.102744:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958086 ES:SE:LP:AF:ID  -0.0010361:0.00661942:0.0555173:0.958086:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031683 ES:SE:LP:AF:ID  -0.00395831:0.0121251:0.130768:0.031683:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052725 ES:SE:LP:AF:ID  -0.00107926:0.00976331:0.0409586:0.052725:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037452 ES:SE:LP:AF:ID  0.00530387:0.00689847:0.356547:0.037452:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037721 ES:SE:LP:AF:ID  0.00454477:0.00684133:0.29243:0.037721:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841457 ES:SE:LP:AF:ID  0.00341627:0.00357452:0.468521:0.841457:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056324 ES:SE:LP:AF:ID  -0.00551391:0.00580701:0.468521:0.056324:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123058 ES:SE:LP:AF:ID  -0.00276162:0.00392623:0.318759:0.123058:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025131 ES:SE:LP:AF:ID  -0.0155518:0.00977678:0.958607:0.025131:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122311 ES:SE:LP:AF:ID  -0.00275137:0.0039275:0.318759:0.122311:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134121 ES:SE:LP:AF:ID  -0.00134268:0.00385545:0.136677:0.134121:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011559 ES:SE:LP:AF:ID  0.00719088:0.0137399:0.221849:0.011559:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006088 ES:SE:LP:AF:ID  -0.00670386:0.0174664:0.154902:0.006088:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037603 ES:SE:LP:AF:ID  0.00397784:0.00677793:0.251812:0.037603:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837045 ES:SE:LP:AF:ID  0.00318415:0.0034579:0.443698:0.837045:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836749 ES:SE:LP:AF:ID  0.00328667:0.00345536:0.468521:0.836749:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868581 ES:SE:LP:AF:ID  0.00372416:0.00371303:0.49485:0.868581:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130986 ES:SE:LP:AF:ID  -0.00294394:0.00372257:0.366532:0.130986:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.038049 ES:SE:LP:AF:ID  0.00506198:0.00667161:0.346787:0.038049:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038295 ES:SE:LP:AF:ID  0.00554595:0.00663026:0.39794:0.038295:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867994 ES:SE:LP:AF:ID  0.00357206:0.00370706:0.468521:0.867994:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868068 ES:SE:LP:AF:ID  0.00351928:0.00370858:0.468521:0.868068:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038203 ES:SE:LP:AF:ID  0.00534712:0.00666088:0.376751:0.038203:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868005 ES:SE:LP:AF:ID  0.00355526:0.00370697:0.468521:0.868005:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005397 ES:SE:LP:AF:ID  0.00642647:0.0185777:0.136677:0.005397:rs150578204
1   754503  rs3115859   G   A   .   PASS    AF=0.836175 ES:SE:LP:AF:ID  0.00309073:0.00344525:0.431798:0.836175:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038206 ES:SE:LP:AF:ID  0.00539559:0.0066706:0.376751:0.038206:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836809 ES:SE:LP:AF:ID  0.00294956:0.00345469:0.408935:0.836809:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013031 ES:SE:LP:AF:ID  -0.0232064:0.0124979:1.20066:0.013031:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005662 ES:SE:LP:AF:ID  0.00171381:0.0185534:0.0315171:0.005662:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.838125 ES:SE:LP:AF:ID  0.00348306:0.00350333:0.49485:0.838125:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868246 ES:SE:LP:AF:ID  0.00357025:0.00370219:0.481486:0.868246:rs3115858