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/public/UKB-b-4667/UKB-b-4667_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4667/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:33 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-4667/UKB-b-4667_data.vcf.gz ...
Read summary statistics for 8686045 SNPs.
Dropped 7521 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, 1285914 SNPs remain.
After merging with regression SNP LD, 1285914 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0468 (0.0021)
Lambda GC: 1.4175
Mean Chi^2: 1.5029
Intercept: 1.0787 (0.0084)
Ratio: 0.1564 (0.0167)
Analysis finished at Thu Oct 17 14:46:08 2019
Total time elapsed: 1.0m:34.94s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9464,
    "inflation_factor": 1.3107,
    "mean_EFFECT": -6.1609e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 23,
    "n_p_sig": 851,
    "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": 84332,
    "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": 1285914,
    "ldsc_nsnp_merge_regression_ld": 1285914,
    "ldsc_observed_scale_h2_beta": 0.0468,
    "ldsc_observed_scale_h2_se": 0.0021,
    "ldsc_intercept_beta": 1.0787,
    "ldsc_intercept_se": 0.0084,
    "ldsc_lambda_gc": 1.4175,
    "ldsc_mean_chisq": 1.5029,
    "ldsc_ratio": 0.1565
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
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 8678558 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 8686045 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 8.650324e+00 5.761123e+00 1.000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.877279e+07 5.636647e+07 8.280e+02 3.239170e+07 6.929926e+07 1.145649e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -6.200000e-06 2.377700e-03 -2.462e-02 -1.061300e-03 -6.900000e-06 1.051800e-03 2.515150e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.801400e-03 1.243600e-03 7.052e-04 8.323000e-04 1.234700e-03 2.441900e-03 1.251830e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.542915e-01 3.006941e-01 0.000e+00 1.800002e-01 4.400003e-01 7.099994e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.542944e-01 3.006700e-01 0.000e+00 1.818697e-01 4.371326e-01 7.149288e-01 9.999999e-01 ▇▆▆▅▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.276099e-01 2.593395e-01 5.157e-03 2.440500e-02 1.117770e-01 3.600330e-01 9.948430e-01 ▇▂▁▁▁
numeric AF_reference 84332 0.9902911 NA NA NA NA NA NA NA 2.273973e-01 2.513197e-01 0.000e+00 2.216450e-02 1.283950e-01 3.572280e-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 -0.0011560 0.0012971 0.3700002 0.3728435 0.623739 0.7821490 NA
1 54676 rs2462492 C T 0.0006130 0.0012848 0.6300007 0.6332704 0.400447 NA NA
1 86028 rs114608975 T C 0.0013531 0.0020545 0.5099998 0.5101662 0.103563 0.0277556 NA
1 91536 rs6702460 G T 0.0012220 0.0012653 0.3300000 0.3341625 0.456854 0.4207270 NA
1 234313 rs8179466 C T -0.0027182 0.0024945 0.2800000 0.2758426 0.074518 NA NA
1 534192 rs6680723 C T -0.0032956 0.0014452 0.0230001 0.0225813 0.240965 NA NA
1 546697 rs12025928 A G 0.0025823 0.0018029 0.1499999 0.1520686 0.913474 NA NA
1 693731 rs12238997 A G 0.0000765 0.0012110 0.9500000 0.9496359 0.116340 0.1417730 NA
1 705882 rs72631875 G A 0.0015726 0.0017750 0.3800004 0.3756041 0.067265 0.0315495 NA
1 706368 rs55727773 A G -0.0012239 0.0008972 0.1700000 0.1724983 0.515686 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0010715 0.0010830 0.3200000 0.3224764 0.137953 0.2052720 NA
22 51219387 rs9616832 T C 0.0011378 0.0014059 0.4199997 0.4183347 0.073751 0.0654952 NA
22 51219704 rs147475742 G A -0.0004335 0.0018841 0.8200001 0.8180301 0.041948 0.0473243 NA
22 51221190 rs369304721 G A 0.0001559 0.0018810 0.9299999 0.9339384 0.049729 NA NA
22 51221731 rs115055839 T C 0.0010933 0.0014068 0.4400003 0.4370517 0.073243 0.0625000 NA
22 51222100 rs114553188 G T -0.0046676 0.0016562 0.0048000 0.0048276 0.054458 0.0880591 NA
22 51223637 rs375798137 G A -0.0045498 0.0016642 0.0063000 0.0062578 0.054088 0.0788738 NA
22 51229805 rs9616985 T C 0.0010756 0.0014119 0.4500005 0.4461772 0.073077 0.0730831 NA
22 51232488 rs376461333 A G -0.0083097 0.0033259 0.0120000 0.0124732 0.020040 NA NA
22 51237063 rs3896457 T C -0.0005002 0.0008636 0.5600000 0.5624002 0.297987 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623739 ES:SE:LP:AF:ID  -0.00115595:0.00129713:0.431798:0.623739:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400447 ES:SE:LP:AF:ID  0.000613039:0.00128485:0.200659:0.400447:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103563 ES:SE:LP:AF:ID  0.00135307:0.00205453:0.29243:0.103563:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456854 ES:SE:LP:AF:ID  0.001222:0.00126532:0.481486:0.456854:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074518 ES:SE:LP:AF:ID  -0.00271825:0.00249448:0.552842:0.074518:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240965 ES:SE:LP:AF:ID  -0.00329563:0.00144517:1.63827:0.240965:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913474 ES:SE:LP:AF:ID  0.00258227:0.00180293:0.823909:0.913474:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11634  ES:SE:LP:AF:ID  7.64942e-05:0.00121104:0.0222764:0.11634:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067265 ES:SE:LP:AF:ID  0.00157265:0.00177495:0.420216:0.067265:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515686 ES:SE:LP:AF:ID  -0.00122391:0.00089715:0.769551:0.515686:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032994 ES:SE:LP:AF:ID  0.0011732:0.00226214:0.221849:0.032994:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036606 ES:SE:LP:AF:ID  0.000649627:0.00205485:0.124939:0.036606:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036723 ES:SE:LP:AF:ID  0.000412099:0.00204707:0.0757207:0.036723:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036422 ES:SE:LP:AF:ID  0.000744408:0.00206182:0.142668:0.036422:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016422 ES:SE:LP:AF:ID  -0.0010704:0.00317247:0.130768:0.016422:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036962 ES:SE:LP:AF:ID  0.000506988:0.00203893:0.09691:0.036962:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037058 ES:SE:LP:AF:ID  0.000643077:0.002032:0.124939:0.037058:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10117  ES:SE:LP:AF:ID  0.00393461:0.00148039:2.10237:0.10117:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959116 ES:SE:LP:AF:ID  -0.000897542:0.00195995:0.187087:0.959116:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031456 ES:SE:LP:AF:ID  -0.00170802:0.00355665:0.200659:0.031456:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053258 ES:SE:LP:AF:ID  0.00163147:0.00282965:0.251812:0.053258:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036575 ES:SE:LP:AF:ID  0.000712791:0.00204518:0.136677:0.036575:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036891 ES:SE:LP:AF:ID  0.000945211:0.00202657:0.19382:0.036891:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843218 ES:SE:LP:AF:ID  -0.000118246:0.00104967:0.0409586:0.843218:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055922 ES:SE:LP:AF:ID  0.00193891:0.00169941:0.60206:0.055922:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122325 ES:SE:LP:AF:ID  -0.000243979:0.00114883:0.0809219:0.122325:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025716 ES:SE:LP:AF:ID  -0.00229166:0.00282589:0.376751:0.025716:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121567 ES:SE:LP:AF:ID  -0.000256552:0.00114932:0.0861861:0.121567:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132324 ES:SE:LP:AF:ID  0.00030426:0.00113286:0.102373:0.132324:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.01113  ES:SE:LP:AF:ID  -0.00232424:0.00411924:0.244125:0.01113:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005703 ES:SE:LP:AF:ID  -0.00514814:0.00531527:0.481486:0.005703:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036808 ES:SE:LP:AF:ID  0.000703107:0.00200601:0.136677:0.036808:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838956 ES:SE:LP:AF:ID  -0.000702852:0.00101653:0.309804:0.838956:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838586 ES:SE:LP:AF:ID  -0.000737085:0.00101544:0.327902:0.838586:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86977  ES:SE:LP:AF:ID  -0.000612236:0.00108956:0.244125:0.86977:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129879 ES:SE:LP:AF:ID  0.000633043:0.00109179:0.251812:0.129879:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037318 ES:SE:LP:AF:ID  0.000868101:0.00197206:0.180456:0.037318:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037561 ES:SE:LP:AF:ID  0.000877865:0.00195963:0.187087:0.037561:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869116 ES:SE:LP:AF:ID  -0.000678482:0.00108744:0.275724:0.869116:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869214 ES:SE:LP:AF:ID  -0.000641072:0.00108787:0.251812:0.869214:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037519 ES:SE:LP:AF:ID  0.000821625:0.00196809:0.167491:0.037519:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869119 ES:SE:LP:AF:ID  -0.00065157:0.00108742:0.259637:0.869119:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.83804  ES:SE:LP:AF:ID  -0.000764984:0.00101263:0.346787:0.83804:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03753  ES:SE:LP:AF:ID  0.000869127:0.00197089:0.180456:0.03753:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838671 ES:SE:LP:AF:ID  -0.000764561:0.00101548:0.346787:0.838671:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013766 ES:SE:LP:AF:ID  -0.00589403:0.0035456:1.01773:0.013766:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005545 ES:SE:LP:AF:ID  -0.00466044:0.00546995:0.408935:0.005545:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839782 ES:SE:LP:AF:ID  -0.000803796:0.0010292:0.366532:0.839782:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869394 ES:SE:LP:AF:ID  -0.000604461:0.00108615:0.236572:0.869394:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.86894  ES:SE:LP:AF:ID  -0.000705828:0.00108341:0.29243:0.86894:rs3131962