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-12938/UKB-b-12938_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12938/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:07 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12938/UKB-b-12938_data.vcf.gz ...
Read summary statistics for 5783850 SNPs.
Dropped 2454 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, 1198557 SNPs remain.
After merging with regression SNP LD, 1198557 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0035 (0.0013)
Lambda GC: 1.0761
Mean Chi^2: 1.0795
Intercept: 1.0537 (0.007)
Ratio: 0.6759 (0.0881)
Analysis finished at Thu Oct 17 14:43:20 2019
Total time elapsed: 1.0m:12.87s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9213,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 1.2495e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 51692,
    "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": 1198557,
    "ldsc_nsnp_merge_regression_ld": 1198557,
    "ldsc_observed_scale_h2_beta": 0.0035,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0537,
    "ldsc_intercept_se": 0.007,
    "ldsc_lambda_gc": 1.0761,
    "ldsc_mean_chisq": 1.0795,
    "ldsc_ratio": 0.6755
}

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 TRUE
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 5781412 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 5783850 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 8.670419e+00 5.762433e+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 7.859623e+07 5.654454e+07 828.0000000 3.199451e+07 6.903534e+07 1.145152e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.000000e-07 5.634000e-04 -0.0048045 -3.418000e-04 -1.400000e-06 3.397000e-04 4.721900e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.208000e-04 1.611000e-04 0.0003520 3.874000e-04 4.590000e-04 6.163000e-04 1.685500e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.888990e-01 2.919804e-01 0.0000007 2.300001e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.888976e-01 2.919529e-01 0.0000007 2.330374e-01 4.851977e-01 7.415075e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.200446e-01 2.508930e-01 0.0392380 1.065700e-01 2.415140e-01 4.862550e-01 9.607620e-01 ▇▃▂▂▁
numeric AF_reference 51692 0.9910627 NA NA NA NA NA NA NA 3.159873e-01 2.445732e-01 0.0000000 1.148160e-01 2.480030e-01 4.762380e-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 -0.0003577 0.0006479 0.5800000 0.5808727 0.623845 0.7821490 NA
1 54676 rs2462492 C T -0.0004945 0.0006413 0.4400003 0.4405885 0.400335 NA NA
1 86028 rs114608975 T C 0.0001873 0.0010262 0.8600001 0.8551474 0.103505 0.0277556 NA
1 91536 rs6702460 G T -0.0004510 0.0006320 0.4799997 0.4754668 0.456749 0.4207270 NA
1 234313 rs8179466 C T 0.0008285 0.0012438 0.5099998 0.5053411 0.074544 NA NA
1 534192 rs6680723 C T -0.0001830 0.0007220 0.8000000 0.7999621 0.240901 NA NA
1 546697 rs12025928 A G -0.0009214 0.0009016 0.3100002 0.3067843 0.913575 NA NA
1 693731 rs12238997 A G -0.0002687 0.0006052 0.6600001 0.6571343 0.116101 0.1417730 NA
1 705882 rs72631875 G A 0.0012859 0.0008888 0.1499999 0.1479716 0.067037 0.0315495 NA
1 706368 rs55727773 A G 0.0006242 0.0004481 0.1600000 0.1636656 0.515745 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0003832 0.0006993 0.5800000 0.5837530 0.073843 0.0826677 NA
22 51219006 rs28729663 G A 0.0007341 0.0005411 0.1700000 0.1748789 0.137837 0.2052720 NA
22 51219387 rs9616832 T C 0.0005104 0.0007008 0.4700002 0.4664320 0.073971 0.0654952 NA
22 51219704 rs147475742 G A 0.0008632 0.0009392 0.3599996 0.3580611 0.042082 0.0473243 NA
22 51221190 rs369304721 G A 0.0001828 0.0009376 0.8499999 0.8454614 0.049824 NA NA
22 51221731 rs115055839 T C 0.0003773 0.0007012 0.5900000 0.5905051 0.073450 0.0625000 NA
22 51222100 rs114553188 G T 0.0014344 0.0008295 0.0840001 0.0837733 0.054171 0.0880591 NA
22 51223637 rs375798137 G A 0.0014153 0.0008335 0.0890000 0.0894910 0.053804 0.0788738 NA
22 51229805 rs9616985 T C 0.0002698 0.0007037 0.6999999 0.7013791 0.073298 0.0730831 NA
22 51237063 rs3896457 T C -0.0000180 0.0004310 0.9699999 0.9667364 0.298052 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623845 ES:SE:LP:AF:ID  -0.000357693:0.000647865:0.236572:0.623845:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400335 ES:SE:LP:AF:ID  -0.000494545:0.000641267:0.356547:0.400335:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103505 ES:SE:LP:AF:ID  0.000187345:0.00102624:0.0655015:0.103505:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456749 ES:SE:LP:AF:ID  -0.000451026:0.000632032:0.318759:0.456749:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074544 ES:SE:LP:AF:ID  0.000828527:0.00124383:0.29243:0.074544:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240901 ES:SE:LP:AF:ID  -0.000182951:0.000721996:0.09691:0.240901:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913575 ES:SE:LP:AF:ID  -0.000921399:0.000901571:0.508638:0.913575:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116101 ES:SE:LP:AF:ID  -0.000268652:0.000605245:0.180456:0.116101:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067037 ES:SE:LP:AF:ID  0.0012859:0.00088883:0.823909:0.067037:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515745 ES:SE:LP:AF:ID  0.000624187:0.000448137:0.79588:0.515745:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.10121  ES:SE:LP:AF:ID  -0.000253993:0.000739551:0.136677:0.10121:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959075 ES:SE:LP:AF:ID  0.001703:0.000978144:1.08619:0.959075:rs2977670
1   725060  rs865924913 A   T   .   PASS    AF=0.053301 ES:SE:LP:AF:ID  -0.000613807:0.00141178:0.180456:0.053301:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.843362 ES:SE:LP:AF:ID  0.000535091:0.000524414:0.508638:0.843362:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055664 ES:SE:LP:AF:ID  7.55075e-05:0.000850475:0.0315171:0.055664:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122076 ES:SE:LP:AF:ID  -0.000284588:0.000574154:0.207608:0.122076:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121315 ES:SE:LP:AF:ID  -0.000260443:0.000574391:0.187087:0.121315:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132134 ES:SE:LP:AF:ID  -0.000666754:0.000566086:0.619789:0.132134:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838997 ES:SE:LP:AF:ID  0.000444635:0.000507691:0.420216:0.838997:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838635 ES:SE:LP:AF:ID  0.000417722:0.000507161:0.387216:0.838635:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.8699   ES:SE:LP:AF:ID  0.000144385:0.000544279:0.102373:0.8699:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129748 ES:SE:LP:AF:ID  -0.000173823:0.00054536:0.124939:0.129748:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869251 ES:SE:LP:AF:ID  0.000124453:0.000543235:0.0861861:0.869251:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869352 ES:SE:LP:AF:ID  0.000101084:0.000543462:0.0705811:0.869352:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869254 ES:SE:LP:AF:ID  0.000120834:0.000543231:0.0861861:0.869254:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838082 ES:SE:LP:AF:ID  0.000420692:0.000505755:0.387216:0.838082:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838708 ES:SE:LP:AF:ID  0.00041697:0.000507188:0.387216:0.838708:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839802 ES:SE:LP:AF:ID  0.000371119:0.000513979:0.327902:0.839802:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869531 ES:SE:LP:AF:ID  0.00013771:0.000542585:0.09691:0.869531:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.869056 ES:SE:LP:AF:ID  0.000158116:0.000541177:0.113509:0.869056:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868032 ES:SE:LP:AF:ID  0.000170402:0.000540181:0.124939:0.868032:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869215 ES:SE:LP:AF:ID  0.000150955:0.000541645:0.107905:0.869215:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869224 ES:SE:LP:AF:ID  0.000151279:0.000541687:0.107905:0.869224:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869232 ES:SE:LP:AF:ID  0.000149415:0.000541698:0.107905:0.869232:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869716 ES:SE:LP:AF:ID  0.000131118:0.000543204:0.091515:0.869716:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838333 ES:SE:LP:AF:ID  0.000439407:0.000504758:0.420216:0.838333:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838447 ES:SE:LP:AF:ID  0.000426385:0.000505098:0.39794:0.838447:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862403 ES:SE:LP:AF:ID  0.000252002:0.000539778:0.19382:0.862403:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706837 ES:SE:LP:AF:ID  6.62846e-05:0.000525291:0.0457575:0.706837:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.104949 ES:SE:LP:AF:ID  -0.000416645:0.000605447:0.309804:0.104949:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761412 ES:SE:LP:AF:ID  0.000632453:0.000428871:0.853872:0.761412:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106514 ES:SE:LP:AF:ID  -0.001021:0.000591224:1.07572:0.106514:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129444 ES:SE:LP:AF:ID  -0.000311711:0.000545014:0.244125:0.129444:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.869051 ES:SE:LP:AF:ID  0.000223274:0.000542169:0.167491:0.869051:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129537 ES:SE:LP:AF:ID  -0.000298901:0.000544687:0.236572:0.129537:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.869069 ES:SE:LP:AF:ID  0.000219438:0.000542188:0.161151:0.869069:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.26539  ES:SE:LP:AF:ID  0.000256809:0.000479001:0.229148:0.26539:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870213 ES:SE:LP:AF:ID  0.000314932:0.000543312:0.251812:0.870213:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095235 ES:SE:LP:AF:ID  -0.000740642:0.000629398:0.619789:0.095235:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128412 ES:SE:LP:AF:ID  -0.000422317:0.000545425:0.356547:0.128412:rs1055606