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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    "FORMAT.5": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
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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_5117.vcf.gz --id UKB-b:16677 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_5117.txt.gz --cohort_controls 84303 --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-16677/UKB-b-16677_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16677/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:15 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16677/UKB-b-16677_data.vcf.gz ...
Read summary statistics for 8887262 SNPs.
Dropped 8243 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, 1286829 SNPs remain.
After merging with regression SNP LD, 1286829 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0389 (0.0058)
Lambda GC: 1.0775
Mean Chi^2: 1.0799
Intercept: 1.0146 (0.0067)
Ratio: 0.1822 (0.0833)
Analysis finished at Thu Oct 17 14:46:43 2019
Total time elapsed: 1.0m:28.23s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9474,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 4,
    "n_p_sig": 43,
    "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": 89248,
    "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": 1286829,
    "ldsc_nsnp_merge_regression_ld": 1286829,
    "ldsc_observed_scale_h2_beta": 0.0389,
    "ldsc_observed_scale_h2_se": 0.0058,
    "ldsc_intercept_beta": 1.0146,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.0775,
    "ldsc_mean_chisq": 1.0799,
    "ldsc_ratio": 0.1827
}

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 8879058 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 8887262 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 8.646363e+00 5.759728e+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 7.877882e+07 5.634575e+07 828.0000000 3.241416e+07 6.933239e+07 1.145492e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.330000e-05 1.565240e-02 -0.1833010 -6.364900e-03 -4.700000e-06 6.302700e-03 1.843720e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.257920e-02 8.994400e-03 0.0047046 5.589600e-03 8.454700e-03 1.719970e-02 1.076080e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.906553e-01 2.913274e-01 0.0000000 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.906551e-01 2.913022e-01 0.0000000 2.360091e-01 4.870745e-01 7.429827e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.229324e-01 2.588377e-01 0.0041520 2.190300e-02 1.054090e-01 3.518930e-01 9.958480e-01 ▇▂▁▁▁
numeric AF_reference 89248 0.9899578 NA NA NA NA NA NA NA 2.230286e-01 2.507842e-01 0.0000000 1.936900e-02 1.224040e-01 3.500400e-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 -0.0073684 0.0087005 0.4000000 0.3970534 0.623328 0.7821490 NA
1 54676 rs2462492 C T -0.0137043 0.0086414 0.1100001 0.1127658 0.399068 NA NA
1 86028 rs114608975 T C 0.0464423 0.0136872 0.0006900 0.0006910 0.104087 0.0277556 NA
1 91536 rs6702460 G T -0.0277031 0.0084832 0.0011000 0.0010921 0.455590 0.4207270 NA
1 234313 rs8179466 C T 0.0113055 0.0165969 0.5000000 0.4957567 0.074857 NA NA
1 534192 rs6680723 C T -0.0087137 0.0097073 0.3700002 0.3693780 0.240530 NA NA
1 546697 rs12025928 A G -0.0006637 0.0120200 0.9599999 0.9559653 0.912604 NA NA
1 693731 rs12238997 A G -0.0007284 0.0080632 0.9299999 0.9280190 0.117886 0.1417730 NA
1 705882 rs72631875 G A -0.0016490 0.0118460 0.8900000 0.8892870 0.067380 0.0315495 NA
1 706368 rs55727773 A G -0.0004465 0.0059806 0.9400001 0.9404881 0.514497 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0063273 0.0072440 0.3800004 0.3824208 0.137315 0.2052720 NA
22 51219387 rs9616832 T C -0.0138047 0.0094558 0.1400000 0.1443107 0.072445 0.0654952 NA
22 51219704 rs147475742 G A -0.0189037 0.0125658 0.1299999 0.1324843 0.041844 0.0473243 NA
22 51221190 rs369304721 G A -0.0165965 0.0126437 0.1900002 0.1893077 0.049027 NA NA
22 51221731 rs115055839 T C -0.0135166 0.0094577 0.1499999 0.1529585 0.071981 0.0625000 NA
22 51222100 rs114553188 G T -0.0011332 0.0110262 0.9199999 0.9181421 0.054759 0.0880591 NA
22 51223637 rs375798137 G A -0.0011673 0.0110831 0.9199999 0.9161235 0.054381 0.0788738 NA
22 51229805 rs9616985 T C -0.0146642 0.0094943 0.1199999 0.1224600 0.071827 0.0730831 NA
22 51232488 rs376461333 A G -0.0068376 0.0223210 0.7600007 0.7593521 0.020127 NA NA
22 51237063 rs3896457 T C 0.0040668 0.0057602 0.4799997 0.4801764 0.298658 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623328 ES:SE:LP:AF:ID  -0.00736838:0.00870046:0.39794:0.623328:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399068 ES:SE:LP:AF:ID  -0.0137043:0.00864143:0.958607:0.399068:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.104087 ES:SE:LP:AF:ID  0.0464423:0.0136872:3.16115:0.104087:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.45559  ES:SE:LP:AF:ID  -0.0277031:0.00848316:2.95861:0.45559:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074857 ES:SE:LP:AF:ID  0.0113055:0.0165969:0.30103:0.074857:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24053  ES:SE:LP:AF:ID  -0.00871367:0.00970732:0.431798:0.24053:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912604 ES:SE:LP:AF:ID  -0.000663712:0.01202:0.0177288:0.912604:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117886 ES:SE:LP:AF:ID  -0.00072841:0.0080632:0.0315171:0.117886:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06738  ES:SE:LP:AF:ID  -0.00164904:0.011846:0.05061:0.06738:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.514497 ES:SE:LP:AF:ID  -0.000446486:0.00598055:0.0268721:0.514497:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033641 ES:SE:LP:AF:ID  -0.0191756:0.0149496:0.69897:0.033641:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037343 ES:SE:LP:AF:ID  -0.0181223:0.0135848:0.744727:0.037343:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037429 ES:SE:LP:AF:ID  -0.0173156:0.0135416:0.69897:0.037429:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037126 ES:SE:LP:AF:ID  -0.0180413:0.0136348:0.721246:0.037126:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016858 ES:SE:LP:AF:ID  -0.00192079:0.0209415:0.0315171:0.016858:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037677 ES:SE:LP:AF:ID  -0.0185727:0.0134846:0.769551:0.037677:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037773 ES:SE:LP:AF:ID  -0.0188391:0.0134404:0.79588:0.037773:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10073  ES:SE:LP:AF:ID  -0.0139024:0.00993959:0.79588:0.10073:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.957986 ES:SE:LP:AF:ID  0.0137573:0.012918:0.537602:0.957986:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031745 ES:SE:LP:AF:ID  0.0111541:0.0237057:0.19382:0.031745:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052556 ES:SE:LP:AF:ID  -0.0207692:0.0190946:0.552842:0.052556:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037261 ES:SE:LP:AF:ID  -0.0176128:0.0135274:0.721246:0.037261:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.03756  ES:SE:LP:AF:ID  -0.0204777:0.0134173:0.886057:0.03756:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.840764 ES:SE:LP:AF:ID  0.00506181:0.00698597:0.327902:0.840764:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056161 ES:SE:LP:AF:ID  0.00155272:0.0113726:0.05061:0.056161:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123753 ES:SE:LP:AF:ID  -0.00257376:0.0076583:0.130768:0.123753:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025786 ES:SE:LP:AF:ID  -0.0140047:0.0188617:0.337242:0.025786:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122943 ES:SE:LP:AF:ID  -0.00214484:0.00766267:0.107905:0.122943:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133622 ES:SE:LP:AF:ID  -0.00706398:0.00755654:0.455932:0.133622:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01134  ES:SE:LP:AF:ID  0.0171077:0.0272419:0.275724:0.01134:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006117 ES:SE:LP:AF:ID  -0.00454049:0.0341339:0.05061:0.006117:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037535 ES:SE:LP:AF:ID  -0.0165744:0.0132702:0.677781:0.037535:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.8367   ES:SE:LP:AF:ID  0.00565327:0.00676116:0.39794:0.8367:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836251 ES:SE:LP:AF:ID  0.00578284:0.00675281:0.408935:0.836251:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868092 ES:SE:LP:AF:ID  0.00266963:0.00724708:0.148742:0.868092:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131595 ES:SE:LP:AF:ID  -0.00419778:0.0072611:0.251812:0.131595:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037984 ES:SE:LP:AF:ID  -0.0161736:0.0130601:0.657577:0.037984:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038243 ES:SE:LP:AF:ID  -0.0168662:0.0129776:0.721246:0.038243:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867391 ES:SE:LP:AF:ID  0.00320732:0.00723211:0.180456:0.867391:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867486 ES:SE:LP:AF:ID  0.00347242:0.00723573:0.200659:0.867486:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038174 ES:SE:LP:AF:ID  -0.0162764:0.0130315:0.677781:0.038174:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86738  ES:SE:LP:AF:ID  0.00290965:0.00723155:0.161151:0.86738:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005063 ES:SE:LP:AF:ID  -0.00702257:0.0376485:0.0705811:0.005063:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00503  ES:SE:LP:AF:ID  -0.00784476:0.0377553:0.0757207:0.00503:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.835803 ES:SE:LP:AF:ID  0.00604025:0.00673858:0.431798:0.835803:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038191 ES:SE:LP:AF:ID  -0.016305:0.013049:0.677781:0.038191:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836415 ES:SE:LP:AF:ID  0.00610808:0.00675713:0.431798:0.836415:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013196 ES:SE:LP:AF:ID  -0.00336321:0.0242613:0.05061:0.013196:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005531 ES:SE:LP:AF:ID  -0.0248449:0.0365545:0.30103:0.005531:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.837734 ES:SE:LP:AF:ID  0.00573576:0.00685063:0.39794:0.837734:rs3131965