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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}

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/dev/ieu-a-import/processed/ieu-a-1239/ieu-a-1239.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1239/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Wed Feb  5 08:25:29 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1239/ieu-a-1239.vcf.gz ...
Read summary statistics for 10054403 SNPs.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1276597 SNPs remain.
After merging with regression SNP LD, 1276597 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1065 (0.0026)
Lambda GC: 2.0897
Mean Chi^2: 2.6414
Intercept: 1.0251 (0.0135)
Ratio: 0.0153 (0.0082)
Analysis finished at Wed Feb  5 08:27:08 2020
Total time elapsed: 1.0m:39.78s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9535,
    "inflation_factor": 1.5903,
    "mean_EFFECT": -0.0001,
    "n": 766345,
    "n_snps": 10054403,
    "n_clumped_hits": 317,
    "n_p_sig": 30389,
    "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": 2369,
    "n_est": 758809.7657,
    "ratio_se_n": 0.9951,
    "mean_diff": 0,
    "ratio_diff": 1.5261,
    "sd_y_est1": 1.072,
    "sd_y_est2": 1.0668,
    "r2_sum1": 0.0226,
    "r2_sum2": 0.0196,
    "r2_sum3": 0.0198,
    "r2_sum4": 0.0203,
    "ldsc_nsnp_merge_refpanel_ld": 1276597,
    "ldsc_nsnp_merge_regression_ld": 1276597,
    "ldsc_observed_scale_h2_beta": 0.1065,
    "ldsc_observed_scale_h2_se": 0.0026,
    "ldsc_intercept_beta": 1.0251,
    "ldsc_intercept_se": 0.0135,
    "ldsc_lambda_gc": 2.0897,
    "ldsc_mean_chisq": 2.6414,
    "ldsc_ratio": 0.0153
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 47 0 10054403 0 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
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.643709e+00 5.769073e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.915177e+07 5.644155e+07 8.28000e+02 3.276902e+07 6.988553e+07 1.150264e+08 2.492251e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.015000e-04 1.483220e-02 -4.25690e-01 -3.580000e-03 -4.000000e-05 3.470000e-03 4.031400e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.159800e-03 1.237830e-02 1.70000e-03 2.040000e-03 3.660000e-03 9.310000e-03 1.118300e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.242246e-01 3.083991e-01 0.00000e+00 1.370001e-01 3.949999e-01 6.899999e-01 1.000000e+00 ▇▅▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.242206e-01 3.083998e-01 0.00000e+00 1.371123e-01 3.954691e-01 6.906863e-01 1.000000e+00 ▇▅▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.952060e-01 2.554429e-01 1.70100e-03 1.020000e-02 6.633000e-02 2.993000e-01 9.982990e-01 ▇▂▁▁▁
numeric AF_reference 2369 0.9997644 NA NA NA NA NA 1.968793e-01 2.465400e-01 1.99700e-04 9.584700e-03 8.506390e-02 3.013180e-01 9.996010e-01 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 7.663450e+05 0.000000e+00 7.66345e+05 7.663450e+05 7.663450e+05 7.663450e+05 7.663450e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 713092 rs4565649 G A -0.01119 0.02382 0.6390002 0.6385170 0.008503 0.0249601 766345
1 715205 rs141090730 C G -0.01730 0.02382 0.4680002 0.4676669 0.008503 0.0299521 766345
1 715265 rs12184267 C T 0.00226 0.00574 0.6939992 0.6937817 0.040820 0.0275559 766345
1 715367 rs12184277 A G 0.00369 0.00579 0.5239997 0.5239257 0.040820 0.0281550 766345
1 717474 rs141784362 C T -0.01391 0.02471 0.5730005 0.5734826 0.008503 0.0249601 766345
1 717587 rs144155419 G A 0.00078 0.00846 0.9269999 0.9265403 0.008503 0.0045926 766345
1 720381 rs116801199 G T 0.00400 0.00574 0.4850003 0.4858878 0.040820 0.0359425 766345
1 721290 rs12565286 G C 0.00329 0.00570 0.5639999 0.5638091 0.042520 0.0371406 766345
1 722559 rs150361918 T C -0.01471 0.02409 0.5419996 0.5414467 0.008503 0.0373403 766345
1 722603 rs138029171 T C 0.00191 0.02613 0.9420000 0.9417297 0.008503 0.0177716 766345
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51213613 rs34726907 C T -0.00459 0.00281 0.1029999 0.1023740 0.165000 0.1727240 766345
22 51217556 rs187294336 C T 0.02341 0.01031 0.0232001 0.0231705 0.005102 0.0023962 766345
22 51217954 rs9616974 G A -0.00511 0.00378 0.1769999 0.1764227 0.093540 0.0621006 766345
22 51218224 rs9616975 C A -0.00520 0.00377 0.1679999 0.1677991 0.091840 0.0619010 766345
22 51219006 rs28729663 G A -0.00347 0.00277 0.2099999 0.2103121 0.176900 0.2052720 766345
22 51219387 rs9616832 T C -0.00507 0.00376 0.1780000 0.1775284 0.090140 0.0654952 766345
22 51219704 rs147475742 G A -0.01050 0.00504 0.0371997 0.0372209 0.044220 0.0473243 766345
22 51221731 rs115055839 T C -0.00528 0.00377 0.1610000 0.1613545 0.091840 0.0625000 766345
22 51229805 rs9616985 T C -0.00522 0.00378 0.1669998 0.1672936 0.091840 0.0730831 766345
22 51237063 rs3896457 T C -0.00285 0.00216 0.1880001 0.1870206 0.226200 0.2050720 766345

bcf preview

1   713092  rs4565649   G   A   .   PASS    AF=0.008503 ES:SE:LP:AF:SS:ID   -0.01119:0.02382:0.194499:0.008503:766345:rs4565649
1   715205  rs141090730 C   G   .   PASS    AF=0.008503 ES:SE:LP:AF:SS:ID   -0.0173:0.02382:0.329754:0.008503:766345:rs141090730
1   715265  rs12184267  C   T   .   PASS    AF=0.04082  ES:SE:LP:AF:SS:ID   0.00226:0.00574:0.158641:0.04082:766345:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.04082  ES:SE:LP:AF:SS:ID   0.00369:0.00579:0.280669:0.04082:766345:rs12184277
1   717474  rs141784362 C   T   .   PASS    AF=0.008503 ES:SE:LP:AF:SS:ID   -0.01391:0.02471:0.241845:0.008503:766345:rs141784362
1   717587  rs144155419 G   A   .   PASS    AF=0.008503 ES:SE:LP:AF:SS:ID   0.00078:0.00846:0.0329203:0.008503:766345:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.04082  ES:SE:LP:AF:SS:ID   0.004:0.00574:0.314258:0.04082:766345:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.04252  ES:SE:LP:AF:SS:ID   0.00329:0.0057:0.248721:0.04252:766345:rs12565286
1   722559  rs150361918 T   C   .   PASS    AF=0.008503 ES:SE:LP:AF:SS:ID   -0.01471:0.02409:0.266001:0.008503:766345:rs150361918
1   722603  rs138029171 T   C   .   PASS    AF=0.008503 ES:SE:LP:AF:SS:ID   0.00191:0.02613:0.0259491:0.008503:766345:rs138029171
1   722980  rs114222710 C   T   .   PASS    AF=0.008503 ES:SE:LP:AF:SS:ID   -0.00777:0.02409:0.126679:0.008503:766345:rs114222710
1   723891  rs2977670   G   C   .   PASS    AF=0.95238  ES:SE:LP:AF:SS:ID   -0.00485:0.00555:0.417937:0.95238:766345:rs2977670
1   723918  rs144434834 G   A   .   PASS    AF=0.008503 ES:SE:LP:AF:SS:ID   -0.00624:0.02447:0.0974532:0.008503:766345:rs144434834
1   726794  rs28454925  C   G   .   PASS    AF=0.04082  ES:SE:LP:AF:SS:ID   0.00581:0.00579:0.501689:0.04082:766345:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.001701 ES:SE:LP:AF:SS:ID   0.0036:0.00573:0.275724:0.001701:766345:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.8554   ES:SE:LP:AF:SS:ID   -0.00148:0.00292:0.213249:0.8554:766345:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.05272  ES:SE:LP:AF:SS:ID   0.0014:0.0045:0.120904:0.05272:766345:rs148120343
1   732120  rs114572157 T   C   .   PASS    AF=0.008503 ES:SE:LP:AF:SS:ID   -0.0078:0.02351:0.130768:0.008503:766345:rs114572157
1   732801  rs144022023 A   G   .   PASS    AF=0.008503 ES:SE:LP:AF:SS:ID   -0.00263:0.02409:0.0395292:0.008503:766345:rs144022023
1   734349  rs141242758 T   C   .   PASS    AF=0.1054   ES:SE:LP:AF:SS:ID   0.00176:0.00306:0.247184:0.1054:766345:rs141242758
1   736186  rs147133636 G   A   .   PASS    AF=0.008503 ES:SE:LP:AF:SS:ID   -0.01116:0.02693:0.16877:0.008503:766345:rs147133636
1   736289  rs79010578  T   A   .   PASS    AF=0.1241   ES:SE:LP:AF:SS:ID   0.00162:0.00312:0.218963:0.1241:766345:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.008503 ES:SE:LP:AF:SS:ID   0.00089:0.00994:0.0319843:0.008503:766345:rs181876450
1   738539  rs147999235 T   C   .   PASS    AF=0.008503 ES:SE:LP:AF:SS:ID   -0.00049:0.02459:0.0070049:0.008503:766345:rs147999235
1   739608  rs145267859 T   C   .   PASS    AF=0.001701 ES:SE:LP:AF:SS:ID   0.01903:0.07908:0.091515:0.001701:766345:rs145267859
1   741833  rs148581628 C   T   .   PASS    AF=0.008503 ES:SE:LP:AF:SS:ID   -0.00656:0.02447:0.102923:0.008503:766345:rs148581628
1   746189  rs139221807 A   G   .   PASS    AF=0.001701 ES:SE:LP:AF:SS:ID   0.05698:0.03886:0.844664:0.001701:766345:rs139221807
1   748445  rs183774475 T   C   .   PASS    AF=0.001701 ES:SE:LP:AF:SS:ID   0.03414:0.07908:0.176526:0.001701:766345:rs183774475
1   748446  rs188307914 G   A   .   PASS    AF=0.001701 ES:SE:LP:AF:SS:ID   0.02098:0.07908:0.101824:0.001701:766345:rs188307914
1   752478  rs146277091 G   A   .   PASS    AF=0.03912  ES:SE:LP:AF:SS:ID   0.00286:0.00575:0.208309:0.03912:766345:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.8486   ES:SE:LP:AF:SS:ID   0.00034:0.00264:0.0462403:0.8486:766345:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.8486   ES:SE:LP:AF:SS:ID   0.00041:0.00264:0.0570004:0.8486:766345:rs3131972
1   753541  rs2073813   G   A   .   PASS    AF=0.1156   ES:SE:LP:AF:SS:ID   0.00046:0.00274:0.0624821:0.1156:766345:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.03061  ES:SE:LP:AF:SS:ID   0.00246:0.0057:0.176526:0.03061:766345:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03741  ES:SE:LP:AF:SS:ID   0.00095:0.00571:0.0614803:0.03741:766345:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.8759   ES:SE:LP:AF:SS:ID   -0.00088:0.00275:0.124939:0.8759:766345:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.8759   ES:SE:LP:AF:SS:ID   -0.00098:0.00275:0.142065:0.8759:766345:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.04082  ES:SE:LP:AF:SS:ID   0.00175:0.00571:0.119758:0.04082:766345:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.8759   ES:SE:LP:AF:SS:ID   -0.00166:0.00277:0.260428:0.8759:766345:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005102 ES:SE:LP:AF:SS:ID   -0.00052:0.01513:0.0118872:0.005102:766345:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005102 ES:SE:LP:AF:SS:ID   -0.00045:0.01513:0.0105502:0.005102:766345:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.8486   ES:SE:LP:AF:SS:ID   0.00072:0.00264:0.105684:0.8486:766345:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.04082  ES:SE:LP:AF:SS:ID   0.00193:0.0057:0.133713:0.04082:766345:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.8469   ES:SE:LP:AF:SS:ID   -0.00035:0.0027:0.0467237:0.8469:766345:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.0119   ES:SE:LP:AF:SS:ID   -0.0062:0.00911:0.303644:0.0119:766345:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005102 ES:SE:LP:AF:SS:ID   -0.00664:0.01442:0.19044:0.005102:766345:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.8759   ES:SE:LP:AF:SS:ID   -0.00119:0.00276:0.175874:0.8759:766345:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.8724   ES:SE:LP:AF:SS:ID   -0.00068:0.00275:0.0942041:0.8724:766345:rs3131962
1   756838  rs77239421  C   G   .   PASS    AF=0.001701 ES:SE:LP:AF:SS:ID   0.02399:0.07908:0.118045:0.001701:766345:rs77239421
1   757640  rs3115853   G   A   .   PASS    AF=0.8759   ES:SE:LP:AF:SS:ID   6e-05:0.00286:0.00744648:0.8759:766345:rs3115853