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_5086.vcf.gz --id UKB-b:14670 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_5086.txt.gz --cohort_controls 99071 --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-14670/UKB-b-14670_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14670/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:45 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14670/UKB-b-14670_data.vcf.gz ...
Read summary statistics for 9019439 SNPs.
Dropped 8786 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, 1287265 SNPs remain.
After merging with regression SNP LD, 1287265 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0298 (0.0057)
Lambda GC: 1.0697
Mean Chi^2: 1.0758
Intercept: 1.0169 (0.0065)
Ratio: 0.2227 (0.0853)
Analysis finished at Thu Oct 17 14:45:33 2019
Total time elapsed: 1.0m:48.19s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9479,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0.0001,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 5,
    "n_p_sig": 126,
    "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": 93942,
    "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": 1287265,
    "ldsc_nsnp_merge_regression_ld": 1287265,
    "ldsc_observed_scale_h2_beta": 0.0298,
    "ldsc_observed_scale_h2_se": 0.0057,
    "ldsc_intercept_beta": 1.0169,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0697,
    "ldsc_mean_chisq": 1.0758,
    "ldsc_ratio": 0.223
}

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 9010693 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 9019439 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 8.642992e+00 5.758157e+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 7.878496e+07 5.633944e+07 828.0000000 3.242930e+07 6.934579e+07 1.145385e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -5.770000e-05 1.507290e-02 -0.1740070 -5.940300e-03 -2.490000e-05 5.855900e-03 1.995470e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.195590e-02 8.782500e-03 0.0043323 5.167000e-03 7.921300e-03 1.640330e-02 1.005840e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.904117e-01 2.909760e-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 4.904112e-01 2.909499e-01 0.0000000 2.360632e-01 4.871034e-01 7.420197e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.199583e-01 2.585105e-01 0.0035330 2.038700e-02 1.011670e-01 3.468000e-01 9.964670e-01 ▇▂▁▁▁
numeric AF_reference 93942 0.9895845 NA NA NA NA NA NA NA 2.202909e-01 2.504123e-01 0.0000000 1.777160e-02 1.186100e-01 3.452480e-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 0.0110681 0.0080058 0.1700000 0.1668162 0.623764 0.7821490 NA
1 54676 rs2462492 C T 0.0055866 0.0079533 0.4799997 0.4824140 0.398686 NA NA
1 86028 rs114608975 T C -0.0294401 0.0126220 0.0200000 0.0196774 0.103973 0.0277556 NA
1 91536 rs6702460 G T 0.0275377 0.0078175 0.0004300 0.0004274 0.455613 0.4207270 NA
1 234313 rs8179466 C T 0.0026135 0.0153276 0.8600001 0.8646080 0.074778 NA NA
1 534192 rs6680723 C T -0.0081015 0.0089416 0.3599996 0.3649133 0.240464 NA NA
1 546697 rs12025928 A G 0.0093003 0.0110824 0.4000000 0.4013586 0.912871 NA NA
1 693731 rs12238997 A G 0.0062709 0.0074350 0.4000000 0.3989893 0.117768 0.1417730 NA
1 705882 rs72631875 G A -0.0140537 0.0108812 0.2000000 0.1965103 0.067645 0.0315495 NA
1 706368 rs55727773 A G 0.0004207 0.0055132 0.9400001 0.9391768 0.514180 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0080656 0.0066692 0.2300001 0.2265145 0.137223 0.2052720 NA
22 51219387 rs9616832 T C 0.0158820 0.0086924 0.0680002 0.0676818 0.072606 0.0654952 NA
22 51219704 rs147475742 G A 0.0118948 0.0115544 0.2999998 0.3032633 0.041858 0.0473243 NA
22 51221190 rs369304721 G A 0.0203553 0.0116285 0.0800000 0.0800378 0.049110 NA NA
22 51221731 rs115055839 T C 0.0158713 0.0086950 0.0680002 0.0679493 0.072139 0.0625000 NA
22 51222100 rs114553188 G T -0.0085554 0.0101626 0.4000000 0.3998738 0.054533 0.0880591 NA
22 51223637 rs375798137 G A -0.0068845 0.0102156 0.5000000 0.5003632 0.054145 0.0788738 NA
22 51229805 rs9616985 T C 0.0156969 0.0087265 0.0719996 0.0720559 0.072001 0.0730831 NA
22 51232488 rs376461333 A G -0.0062918 0.0205716 0.7600007 0.7597201 0.020054 NA NA
22 51237063 rs3896457 T C -0.0018380 0.0053052 0.7300002 0.7290026 0.298305 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623764 ES:SE:LP:AF:ID  0.0110681:0.00800582:0.769551:0.623764:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.398686 ES:SE:LP:AF:ID  0.00558662:0.00795333:0.318759:0.398686:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103973 ES:SE:LP:AF:ID  -0.0294401:0.012622:1.69897:0.103973:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455613 ES:SE:LP:AF:ID  0.0275377:0.00781753:3.36653:0.455613:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074778 ES:SE:LP:AF:ID  0.00261353:0.0153276:0.0655015:0.074778:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240464 ES:SE:LP:AF:ID  -0.00810148:0.00894161:0.443698:0.240464:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912871 ES:SE:LP:AF:ID  0.00930032:0.0110824:0.39794:0.912871:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117768 ES:SE:LP:AF:ID  0.00627091:0.00743503:0.39794:0.117768:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067645 ES:SE:LP:AF:ID  -0.0140537:0.0108812:0.69897:0.067645:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51418  ES:SE:LP:AF:ID  0.00042068:0.00551317:0.0268721:0.51418:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033663 ES:SE:LP:AF:ID  -0.00244023:0.0137556:0.0655015:0.033663:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.037324 ES:SE:LP:AF:ID  -0.00363582:0.0125111:0.113509:0.037324:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037404 ES:SE:LP:AF:ID  -0.00358026:0.0124712:0.113509:0.037404:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.037098 ES:SE:LP:AF:ID  -0.00467942:0.012557:0.148742:0.037098:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016724 ES:SE:LP:AF:ID  0.00801695:0.019368:0.167491:0.016724:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037665 ES:SE:LP:AF:ID  -0.00417186:0.012417:0.130768:0.037665:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037752 ES:SE:LP:AF:ID  -0.00357797:0.0123789:0.113509:0.037752:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101285 ES:SE:LP:AF:ID  0.0140073:0.0091147:0.920819:0.101285:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958033 ES:SE:LP:AF:ID  0.00332007:0.0119069:0.107905:0.958033:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031831 ES:SE:LP:AF:ID  -0.00259745:0.0217806:0.0409586:0.031831:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.052516 ES:SE:LP:AF:ID  -0.00907121:0.0176192:0.21467:0.052516:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.037209 ES:SE:LP:AF:ID  -0.00300265:0.0124665:0.091515:0.037209:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037525 ES:SE:LP:AF:ID  -0.00176095:0.0123608:0.05061:0.037525:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.840936 ES:SE:LP:AF:ID  -0.00367319:0.00643874:0.244125:0.840936:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.056184 ES:SE:LP:AF:ID  0.00437784:0.0104751:0.167491:0.056184:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123696 ES:SE:LP:AF:ID  0.00538355:0.00705734:0.346787:0.123696:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025917 ES:SE:LP:AF:ID  -0.0304423:0.0173185:1.10237:0.025917:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12289  ES:SE:LP:AF:ID  0.00527252:0.00706094:0.337242:0.12289:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.133662 ES:SE:LP:AF:ID  0.00270003:0.00695968:0.154902:0.133662:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011245 ES:SE:LP:AF:ID  0.0156711:0.0251921:0.275724:0.011245:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.006012 ES:SE:LP:AF:ID  -0.00978195:0.0317267:0.119186:0.006012:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.037495 ES:SE:LP:AF:ID  -0.000841947:0.0122236:0.0222764:0.037495:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.836696 ES:SE:LP:AF:ID  -0.00496782:0.00623064:0.366532:0.836696:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836264 ES:SE:LP:AF:ID  -0.00575458:0.00622357:0.443698:0.836264:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.867973 ES:SE:LP:AF:ID  -0.00532543:0.00667572:0.366532:0.867973:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131689 ES:SE:LP:AF:ID  0.00638793:0.00669006:0.468521:0.131689:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037937 ES:SE:LP:AF:ID  -0.00070306:0.0120311:0.0222764:0.037937:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038185 ES:SE:LP:AF:ID  -0.00114659:0.0119566:0.0362122:0.038185:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867277 ES:SE:LP:AF:ID  -0.00543744:0.00666224:0.387216:0.867277:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867378 ES:SE:LP:AF:ID  -0.00529269:0.00666536:0.366532:0.867378:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.038137 ES:SE:LP:AF:ID  -0.00128696:0.0120043:0.0409586:0.038137:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.867276 ES:SE:LP:AF:ID  -0.00549721:0.00666183:0.387216:0.867276:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005088 ES:SE:LP:AF:ID  0.0326663:0.0345082:0.468521:0.005088:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005055 ES:SE:LP:AF:ID  0.0337972:0.0346043:0.481486:0.005055:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.835809 ES:SE:LP:AF:ID  -0.00502217:0.00621028:0.376751:0.835809:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.038155 ES:SE:LP:AF:ID  -0.00133013:0.0120201:0.0409586:0.038155:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.836413 ES:SE:LP:AF:ID  -0.00520206:0.0062269:0.39794:0.836413:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013199 ES:SE:LP:AF:ID  0.0701872:0.022325:2.76955:0.013199:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005513 ES:SE:LP:AF:ID  0.040865:0.0337395:0.638272:0.005513:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.837704 ES:SE:LP:AF:ID  -0.00488543:0.00631214:0.356547:0.837704:rs3131965