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-1799/UKB-b-1799_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1799/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1799/UKB-b-1799_data.vcf.gz ...
Read summary statistics for 5569472 SNPs.
Dropped 2115 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, 1179770 SNPs remain.
After merging with regression SNP LD, 1179770 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0048 (0.0011)
Lambda GC: 1.0745
Mean Chi^2: 1.0766
Intercept: 1.032 (0.0076)
Ratio: 0.4183 (0.0995)
Analysis finished at Thu Oct 17 14:41:27 2019
Total time elapsed: 1.0m:9.02s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9178,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -3.5949e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 17,
    "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": 49073,
    "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": 1179770,
    "ldsc_nsnp_merge_regression_ld": 1179770,
    "ldsc_observed_scale_h2_beta": 0.0048,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.032,
    "ldsc_intercept_se": 0.0076,
    "ldsc_lambda_gc": 1.0745,
    "ldsc_mean_chisq": 1.0766,
    "ldsc_ratio": 0.4178
}

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 5567373 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 5569472 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 8.672096e+00 5.763336e+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 7.859310e+07 5.656175e+07 828.0000000 3.199473e+07 6.902693e+07 1.145305e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -4.000000e-07 3.974000e-04 -0.0032350 -2.448000e-04 -8.000000e-07 2.432000e-04 3.359300e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.685000e-04 1.047000e-04 0.0002566 2.812000e-04 3.291000e-04 4.317000e-04 1.213600e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.881693e-01 2.921478e-01 0.0000000 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.881684e-01 2.921218e-01 0.0000000 2.321216e-01 4.840718e-01 7.413348e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.285361e-01 2.480750e-01 0.0454370 1.166360e-01 2.534520e-01 4.952830e-01 9.545630e-01 ▇▃▂▂▁
numeric AF_reference 49073 0.9911889 NA NA NA NA NA NA NA 3.238863e-01 2.423937e-01 0.0000000 1.244010e-01 2.587860e-01 4.852240e-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 0.0005086 0.0004722 0.2800000 0.2814314 0.623763 0.7821490 NA
1 54676 rs2462492 C T 0.0003575 0.0004678 0.4400003 0.4447433 0.400401 NA NA
1 86028 rs114608975 T C 0.0002835 0.0007480 0.6999999 0.7046501 0.103552 0.0277556 NA
1 91536 rs6702460 G T 0.0000728 0.0004606 0.8700001 0.8743834 0.456857 0.4207270 NA
1 234313 rs8179466 C T -0.0010524 0.0009082 0.2500000 0.2465413 0.074506 NA NA
1 534192 rs6680723 C T -0.0000626 0.0005261 0.9100000 0.9052821 0.240954 NA NA
1 546697 rs12025928 A G -0.0005036 0.0006564 0.4400003 0.4429903 0.913475 NA NA
1 693731 rs12238997 A G 0.0001560 0.0004409 0.7199992 0.7234617 0.116333 0.1417730 NA
1 705882 rs72631875 G A -0.0004723 0.0006461 0.4600002 0.4647936 0.067294 0.0315495 NA
1 706368 rs55727773 A G -0.0004444 0.0003266 0.1700000 0.1736515 0.515646 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218224 rs9616975 C A -0.0003222 0.0005111 0.5300002 0.5283922 0.073335 0.0619010 NA
22 51218377 rs2519461 G C -0.0002641 0.0005104 0.5999997 0.6049382 0.073623 0.0826677 NA
22 51219006 rs28729663 G A -0.0003015 0.0003940 0.4400003 0.4441685 0.137953 0.2052720 NA
22 51219387 rs9616832 T C -0.0003116 0.0005115 0.5400003 0.5423226 0.073746 0.0654952 NA
22 51221190 rs369304721 G A -0.0007233 0.0006842 0.2900000 0.2904387 0.049735 NA NA
22 51221731 rs115055839 T C -0.0003143 0.0005118 0.5400003 0.5391501 0.073237 0.0625000 NA
22 51222100 rs114553188 G T -0.0002348 0.0006025 0.6999999 0.6967295 0.054463 0.0880591 NA
22 51223637 rs375798137 G A -0.0002424 0.0006054 0.6899999 0.6889008 0.054091 0.0788738 NA
22 51229805 rs9616985 T C -0.0002846 0.0005136 0.5800000 0.5794970 0.073072 0.0730831 NA
22 51237063 rs3896457 T C 0.0001858 0.0003142 0.5500004 0.5542334 0.297982 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  0.000508611:0.0004722:0.552842:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  0.000357508:0.000467815:0.356547:0.400401:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103552 ES:SE:LP:AF:ID  0.000283527:0.000747992:0.154902:0.103552:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456857 ES:SE:LP:AF:ID  7.28212e-05:0.000460622:0.0604807:0.456857:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074506 ES:SE:LP:AF:ID  -0.00105245:0.000908231:0.60206:0.074506:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240954 ES:SE:LP:AF:ID  -6.26068e-05:0.000526145:0.0409586:0.240954:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913475 ES:SE:LP:AF:ID  -0.000503561:0.000656402:0.356547:0.913475:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116333 ES:SE:LP:AF:ID  0.000156012:0.000440916:0.142668:0.116333:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067294 ES:SE:LP:AF:ID  -0.000472294:0.000646114:0.337242:0.067294:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515646 ES:SE:LP:AF:ID  -0.000444382:0.000326616:0.769551:0.515646:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.10121  ES:SE:LP:AF:ID  0.000113223:0.000538875:0.0809219:0.10121:rs116030099
1   725060  rs865924913 A   T   .   PASS    AF=0.053255 ES:SE:LP:AF:ID  -0.00170086:0.00103028:1.00436:0.053255:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.843208 ES:SE:LP:AF:ID  -0.000359906:0.000382111:0.455932:0.843208:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055921 ES:SE:LP:AF:ID  -0.000266207:0.000618646:0.173925:0.055921:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122316 ES:SE:LP:AF:ID  -7.65865e-06:0.000418252:0.00436481:0.122316:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121559 ES:SE:LP:AF:ID  3.76532e-05:0.000418427:0.0315171:0.121559:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132333 ES:SE:LP:AF:ID  0.000393542:0.000412401:0.468521:0.132333:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838948 ES:SE:LP:AF:ID  -0.00026293:0.000370048:0.318759:0.838948:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838576 ES:SE:LP:AF:ID  -0.000275633:0.00036965:0.337242:0.838576:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869772 ES:SE:LP:AF:ID  2.33816e-05:0.000396648:0.0222764:0.869772:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12988  ES:SE:LP:AF:ID  -5.90713e-05:0.000397459:0.0555173:0.12988:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869114 ES:SE:LP:AF:ID  1.0611e-05:0.00039587:0.00877392:0.869114:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869212 ES:SE:LP:AF:ID  1.44435e-05:0.000396027:0.0132283:0.869212:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869117 ES:SE:LP:AF:ID  8.71586e-06:0.000395863:0.00877392:0.869117:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838029 ES:SE:LP:AF:ID  -0.000280859:0.000368624:0.346787:0.838029:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.83866  ES:SE:LP:AF:ID  -0.000291722:0.000369661:0.366532:0.83866:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839772 ES:SE:LP:AF:ID  -0.000300658:0.000374659:0.376751:0.839772:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869397 ES:SE:LP:AF:ID  1.64107e-05:0.000395405:0.0132283:0.869397:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868944 ES:SE:LP:AF:ID  1.00408e-05:0.00039441:0.00877392:0.868944:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867896 ES:SE:LP:AF:ID  3.91274e-05:0.000393654:0.0362122:0.867896:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869087 ES:SE:LP:AF:ID  8.79374e-06:0.000394733:0.00877392:0.869087:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869096 ES:SE:LP:AF:ID  8.12524e-06:0.000394764:0.00877392:0.869096:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869103 ES:SE:LP:AF:ID  8.02918e-06:0.000394773:0.00877392:0.869103:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869581 ES:SE:LP:AF:ID  1.22103e-06:0.000395857:-0:0.869581:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838308 ES:SE:LP:AF:ID  -0.00024935:0.000367926:0.30103:0.838308:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838429 ES:SE:LP:AF:ID  -0.000240552:0.000368186:0.29243:0.838429:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862253 ES:SE:LP:AF:ID  -9.93238e-06:0.000393344:0.00877392:0.862253:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706733 ES:SE:LP:AF:ID  -0.000236308:0.000382926:0.267606:0.706733:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105147 ES:SE:LP:AF:ID  0.000127438:0.000441115:0.113509:0.105147:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761312 ES:SE:LP:AF:ID  2.17722e-05:0.000312538:0.0268721:0.761312:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106471 ES:SE:LP:AF:ID  2.49122e-05:0.000430805:0.0222764:0.106471:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129586 ES:SE:LP:AF:ID  -3.73772e-05:0.000397222:0.0315171:0.129586:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868903 ES:SE:LP:AF:ID  2.72395e-05:0.000395101:0.0222764:0.868903:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129685 ES:SE:LP:AF:ID  -4.8851e-05:0.000396967:0.0457575:0.129685:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868912 ES:SE:LP:AF:ID  3.41067e-05:0.000395107:0.0315171:0.868912:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265388 ES:SE:LP:AF:ID  0.000134057:0.00034911:0.154902:0.265388:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870036 ES:SE:LP:AF:ID  8.17316e-06:0.000395915:0.00877392:0.870036:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095137 ES:SE:LP:AF:ID  0.000100788:0.000458881:0.0809219:0.095137:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128584 ES:SE:LP:AF:ID  -3.03291e-05:0.000397478:0.0268721:0.128584:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128881 ES:SE:LP:AF:ID  -3.51205e-05:0.000396803:0.0315171:0.128881:rs4040617