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_2473.vcf.gz --id UKB-b:14961 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_2473.txt.gz --cohort_cases 93267 --cohort_controls 360986 --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-14961/UKB-b-14961_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14961/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:49 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14961/UKB-b-14961_data.vcf.gz ...
Read summary statistics for 8962820 SNPs.
Dropped 8563 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, 1286998 SNPs remain.
After merging with regression SNP LD, 1286998 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0249 (0.0014)
Lambda GC: 1.2107
Mean Chi^2: 1.2394
Intercept: 1.0219 (0.0066)
Ratio: 0.0913 (0.0277)
Analysis finished at Thu Oct 17 14:45:28 2019
Total time elapsed: 1.0m:38.89s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9475,
    "inflation_factor": 1.1474,
    "mean_EFFECT": -0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 8,
    "n_p_sig": 1294,
    "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": 91980,
    "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": 1286998,
    "ldsc_nsnp_merge_regression_ld": 1286998,
    "ldsc_observed_scale_h2_beta": 0.0249,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0219,
    "ldsc_intercept_se": 0.0066,
    "ldsc_lambda_gc": 1.2107,
    "ldsc_mean_chisq": 1.2394,
    "ldsc_ratio": 0.0915
}

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 TRUE
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 8954296 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 8962820 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 8.644535e+00 5.758409e+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 7.879178e+07 5.633881e+07 828.0000000 3.243196e+07 6.935800e+07 1.145515e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.550000e-05 2.837000e-03 -0.0328174 -1.185300e-03 -1.300000e-05 1.158400e-03 4.646050e-02 ▁▃▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.226300e-03 1.617300e-03 0.0008175 9.731000e-04 1.484000e-03 3.050800e-03 1.899330e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.759887e-01 2.955999e-01 0.0000000 2.099999e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.759889e-01 2.955732e-01 0.0000000 2.138346e-01 4.680403e-01 7.322738e-01 9.999999e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.211594e-01 2.586519e-01 0.0037530 2.098200e-02 1.028460e-01 3.490242e-01 9.962470e-01 ▇▂▁▁▁
numeric AF_reference 91980 0.9897376 NA NA NA NA NA NA NA 2.213630e-01 2.505615e-01 0.0000000 1.837060e-02 1.202080e-01 3.472440e-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 0.0029870 0.0015043 0.0470002 0.0470768 0.623785 0.7821490 NA
1 54676 rs2462492 C T 0.0004925 0.0014901 0.7400005 0.7410298 0.400414 NA NA
1 86028 rs114608975 T C 0.0009033 0.0023833 0.6999999 0.7046772 0.103528 0.0277556 NA
1 91536 rs6702460 G T 0.0007629 0.0014671 0.5999997 0.6030549 0.456889 0.4207270 NA
1 234313 rs8179466 C T 0.0020741 0.0028922 0.4700002 0.4732864 0.074526 NA NA
1 534192 rs6680723 C T 0.0015438 0.0016758 0.3599996 0.3569204 0.240949 NA NA
1 546697 rs12025928 A G -0.0001540 0.0020898 0.9400001 0.9412517 0.913434 NA NA
1 693731 rs12238997 A G 0.0011092 0.0014050 0.4299995 0.4298652 0.116229 0.1417730 NA
1 705882 rs72631875 G A -0.0021532 0.0020574 0.2999998 0.2953059 0.067316 0.0315495 NA
1 706368 rs55727773 A G -0.0004958 0.0010406 0.6300007 0.6337229 0.515731 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0024514 0.0012551 0.0510000 0.0507971 0.138046 0.2052720 NA
22 51219387 rs9616832 T C -0.0018544 0.0016290 0.2500000 0.2549654 0.073809 0.0654952 NA
22 51219704 rs147475742 G A -0.0003334 0.0021826 0.8800001 0.8785856 0.042004 0.0473243 NA
22 51221190 rs369304721 G A -0.0020274 0.0021790 0.3500000 0.3521497 0.049783 NA NA
22 51221731 rs115055839 T C -0.0019563 0.0016301 0.2300001 0.2300826 0.073298 0.0625000 NA
22 51222100 rs114553188 G T -0.0027396 0.0019194 0.1499999 0.1534889 0.054476 0.0880591 NA
22 51223637 rs375798137 G A -0.0028115 0.0019287 0.1400000 0.1449085 0.054105 0.0788738 NA
22 51229805 rs9616985 T C -0.0018643 0.0016359 0.2500000 0.2544574 0.073135 0.0730831 NA
22 51232488 rs376461333 A G -0.0032622 0.0038547 0.4000000 0.3973932 0.020050 NA NA
22 51237063 rs3896457 T C 0.0011419 0.0010009 0.2500000 0.2539126 0.297940 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623785 ES:SE:LP:AF:ID  0.00298701:0.00150433:1.3279:0.623785:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400414 ES:SE:LP:AF:ID  0.000492463:0.0014901:0.130768:0.400414:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103528 ES:SE:LP:AF:ID  0.000903324:0.00238335:0.154902:0.103528:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456889 ES:SE:LP:AF:ID  0.000762931:0.00146714:0.221849:0.456889:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074526 ES:SE:LP:AF:ID  0.00207414:0.00289223:0.327902:0.074526:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240949 ES:SE:LP:AF:ID  0.00154382:0.00167579:0.443698:0.240949:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913434 ES:SE:LP:AF:ID  -0.000154013:0.00208982:0.0268721:0.913434:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116229 ES:SE:LP:AF:ID  0.00110917:0.00140504:0.366532:0.116229:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067316 ES:SE:LP:AF:ID  -0.00215323:0.00205745:0.522879:0.067316:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515731 ES:SE:LP:AF:ID  -0.00049582:0.00104056:0.200659:0.515731:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033034 ES:SE:LP:AF:ID  -0.00143242:0.0026221:0.236572:0.033034:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03666  ES:SE:LP:AF:ID  -0.00206423:0.00238143:0.408935:0.03666:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036772 ES:SE:LP:AF:ID  -0.00215217:0.00237259:0.443698:0.036772:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036474 ES:SE:LP:AF:ID  -0.00181891:0.00238959:0.346787:0.036474:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016377 ES:SE:LP:AF:ID  -0.00177587:0.00368482:0.200659:0.016377:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037015 ES:SE:LP:AF:ID  -0.00167434:0.00236302:0.318759:0.037015:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.03711  ES:SE:LP:AF:ID  -0.00177616:0.00235501:0.346787:0.03711:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101271 ES:SE:LP:AF:ID  0.00118338:0.00171581:0.309804:0.101271:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959061 ES:SE:LP:AF:ID  0.00298317:0.00227169:0.721246:0.959061:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031442 ES:SE:LP:AF:ID  -0.00421659:0.00412638:0.508638:0.031442:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053275 ES:SE:LP:AF:ID  -0.00695935:0.00327968:1.46852:0.053275:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.03663  ES:SE:LP:AF:ID  -0.0017099:0.00237016:0.327902:0.03663:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036944 ES:SE:LP:AF:ID  -0.00175094:0.0023487:0.337242:0.036944:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843259 ES:SE:LP:AF:ID  -0.000419286:0.00121742:0.136677:0.843259:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055892 ES:SE:LP:AF:ID  0.00217959:0.00197123:0.568636:0.055892:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122222 ES:SE:LP:AF:ID  0.00152503:0.00133272:0.60206:0.122222:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025723 ES:SE:LP:AF:ID  0.00729244:0.00327713:1.58503:0.025723:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12146  ES:SE:LP:AF:ID  0.00149226:0.00133334:0.585027:0.12146:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132317 ES:SE:LP:AF:ID  0.000859594:0.00131379:0.29243:0.132317:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01114  ES:SE:LP:AF:ID  0.00122687:0.00477467:0.09691:0.01114:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005702 ES:SE:LP:AF:ID  -0.0056573:0.00616432:0.443698:0.005702:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036861 ES:SE:LP:AF:ID  -0.00184409:0.00232489:0.366532:0.036861:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.839019 ES:SE:LP:AF:ID  -4.65554e-05:0.00117914:0.0132283:0.839019:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83864  ES:SE:LP:AF:ID  -1.57093e-05:0.00117784:0.00436481:0.83864:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869895 ES:SE:LP:AF:ID  -0.000525085:0.00126409:0.167491:0.869895:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129766 ES:SE:LP:AF:ID  0.000860263:0.00126662:0.30103:0.129766:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037369 ES:SE:LP:AF:ID  -0.00215424:0.00228563:0.455932:0.037369:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037613 ES:SE:LP:AF:ID  -0.00196943:0.00227119:0.408935:0.037613:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869231 ES:SE:LP:AF:ID  -0.000592495:0.00126158:0.19382:0.869231:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869331 ES:SE:LP:AF:ID  -0.000550831:0.00126209:0.180456:0.869331:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037572 ES:SE:LP:AF:ID  -0.00201215:0.00228102:0.420216:0.037572:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869234 ES:SE:LP:AF:ID  -0.000618564:0.00126155:0.207608:0.869234:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005119 ES:SE:LP:AF:ID  -0.00399783:0.00647678:0.267606:0.005119:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005085 ES:SE:LP:AF:ID  -0.00398837:0.00649384:0.267606:0.005085:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838095 ES:SE:LP:AF:ID  7.76127e-06:0.00117458:0.00436481:0.838095:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037585 ES:SE:LP:AF:ID  -0.00201829:0.00228422:0.420216:0.037585:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838725 ES:SE:LP:AF:ID  -1.95792e-05:0.00117788:0.00436481:0.838725:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013792 ES:SE:LP:AF:ID  -0.00141031:0.00410756:0.136677:0.013792:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005544 ES:SE:LP:AF:ID  0.00141634:0.00634427:0.0861861:0.005544:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839842 ES:SE:LP:AF:ID  -0.000124677:0.00119385:0.0362122:0.839842:rs3131965