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-7189/UKB-b-7189_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7189/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-7189/UKB-b-7189_data.vcf.gz ...
Read summary statistics for 5267088 SNPs.
Dropped 1700 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, 1148255 SNPs remain.
After merging with regression SNP LD, 1148255 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.001 (0.0011)
Lambda GC: 1.0408
Mean Chi^2: 1.0372
Intercept: 1.0278 (0.0077)
Ratio: 0.7471 (0.2069)
Analysis finished at Thu Oct 17 14:41:56 2019
Total time elapsed: 1.0m:37.22s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9121,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 6.6309e-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": 45569,
    "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": 1148255,
    "ldsc_nsnp_merge_regression_ld": 1148255,
    "ldsc_observed_scale_h2_beta": 0.001,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0278,
    "ldsc_intercept_se": 0.0077,
    "ldsc_lambda_gc": 1.0408,
    "ldsc_mean_chisq": 1.0372,
    "ldsc_ratio": 0.7473
}

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 5265401 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 5267088 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 8.672629e+00 5.763379e+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 7.853161e+07 5.658713e+07 828.0000000 3.190913e+07 6.891536e+07 1.144907e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 7.000000e-07 3.509000e-04 -0.0026510 -2.198000e-04 9.000000e-07 2.207000e-04 2.513400e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.343000e-04 8.380000e-05 0.0002420 2.637000e-04 3.035000e-04 3.863000e-04 1.111600e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.937108e-01 2.902392e-01 0.0000001 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.937114e-01 2.902136e-01 0.0000001 2.406431e-01 4.911160e-01 7.457904e-01 9.999994e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.406013e-01 2.432197e-01 0.0555830 1.317530e-01 2.706310e-01 5.074390e-01 9.444170e-01 ▇▃▂▂▂
numeric AF_reference 45569 0.9913484 NA NA NA NA NA NA NA 3.349416e-01 2.387274e-01 0.0000000 1.381790e-01 2.743610e-01 4.970050e-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 -0.0002347 0.0004452 0.5999997 0.5980458 0.623754 0.7821490 NA
1 54676 rs2462492 C T -0.0003757 0.0004411 0.3900004 0.3944428 0.400421 NA NA
1 86028 rs114608975 T C 0.0006356 0.0007053 0.3700002 0.3674381 0.103544 0.0277556 NA
1 91536 rs6702460 G T -0.0000777 0.0004343 0.8600001 0.8579668 0.456851 0.4207270 NA
1 234313 rs8179466 C T -0.0016276 0.0008570 0.0580003 0.0575310 0.074438 NA NA
1 534192 rs6680723 C T 0.0003077 0.0004962 0.5400003 0.5351949 0.240901 NA NA
1 546697 rs12025928 A G -0.0007489 0.0006190 0.2300001 0.2262929 0.913475 NA NA
1 693731 rs12238997 A G -0.0000069 0.0004159 0.9900000 0.9867165 0.116360 0.1417730 NA
1 705882 rs72631875 G A 0.0004317 0.0006093 0.4799997 0.4786154 0.067332 0.0315495 NA
1 706368 rs55727773 A G -0.0003033 0.0003080 0.3200000 0.3248464 0.515713 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51213613 rs34726907 C T -0.0003196 0.0003811 0.4000000 0.4017341 0.127896 0.1727240 NA
22 51216564 rs9616970 T C -0.0003074 0.0003795 0.4199997 0.4179521 0.128420 0.1563500 NA
22 51217954 rs9616974 G A 0.0000973 0.0004814 0.8400000 0.8398095 0.073360 0.0621006 NA
22 51218224 rs9616975 C A 0.0000897 0.0004817 0.8499999 0.8523224 0.073382 0.0619010 NA
22 51218377 rs2519461 G C 0.0001378 0.0004811 0.7700005 0.7745646 0.073664 0.0826677 NA
22 51219006 rs28729663 G A -0.0002810 0.0003714 0.4500005 0.4492988 0.138025 0.2052720 NA
22 51219387 rs9616832 T C 0.0000989 0.0004820 0.8400000 0.8373821 0.073791 0.0654952 NA
22 51221731 rs115055839 T C 0.0000946 0.0004823 0.8400000 0.8444835 0.073286 0.0625000 NA
22 51229805 rs9616985 T C 0.0000926 0.0004841 0.8499999 0.8483396 0.073123 0.0730831 NA
22 51237063 rs3896457 T C 0.0001585 0.0002962 0.5900000 0.5926576 0.298148 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623754 ES:SE:LP:AF:ID  -0.000234741:0.000445249:0.221849:0.623754:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400421 ES:SE:LP:AF:ID  -0.000375667:0.000441137:0.408935:0.400421:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103544 ES:SE:LP:AF:ID  0.000635643:0.000705265:0.431798:0.103544:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  -7.77236e-05:0.0004343:0.0655015:0.456851:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074438 ES:SE:LP:AF:ID  -0.00162757:0.000856952:1.23657:0.074438:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240901 ES:SE:LP:AF:ID  0.00030771:0.00049623:0.267606:0.240901:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913475 ES:SE:LP:AF:ID  -0.000748913:0.000618955:0.638272:0.913475:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11636  ES:SE:LP:AF:ID  -6.924e-06:0.000415876:0.00436481:0.11636:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067332 ES:SE:LP:AF:ID  0.000431723:0.000609321:0.318759:0.067332:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515713 ES:SE:LP:AF:ID  -0.000303281:0.000308041:0.49485:0.515713:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101245 ES:SE:LP:AF:ID  0.000755532:0.000508211:0.853872:0.101245:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.843126 ES:SE:LP:AF:ID  -0.000188198:0.000360375:0.221849:0.843126:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055914 ES:SE:LP:AF:ID  0.000598487:0.000583542:0.508638:0.055914:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122346 ES:SE:LP:AF:ID  0.000105804:0.000394457:0.102373:0.122346:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121588 ES:SE:LP:AF:ID  0.000130402:0.00039462:0.130768:0.121588:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132416 ES:SE:LP:AF:ID  0.000280629:0.000388872:0.327902:0.132416:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838824 ES:SE:LP:AF:ID  -6.90588e-05:0.000348919:0.0757207:0.838824:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838445 ES:SE:LP:AF:ID  -0.000107553:0.000348529:0.119186:0.838445:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869706 ES:SE:LP:AF:ID  -6.23002e-05:0.000374011:0.0604807:0.869706:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.12996  ES:SE:LP:AF:ID  0.000126519:0.000374753:0.130768:0.12996:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869045 ES:SE:LP:AF:ID  -0.000110679:0.000373268:0.113509:0.869045:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869146 ES:SE:LP:AF:ID  -0.000124226:0.00037342:0.130768:0.869146:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869049 ES:SE:LP:AF:ID  -0.000102558:0.000373261:0.107905:0.869049:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837894 ES:SE:LP:AF:ID  -9.1644e-05:0.000347559:0.102373:0.837894:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838527 ES:SE:LP:AF:ID  -7.05422e-05:0.000348536:0.0757207:0.838527:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839644 ES:SE:LP:AF:ID  -4.1946e-05:0.000353268:0.0409586:0.839644:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869335 ES:SE:LP:AF:ID  -6.35916e-05:0.00037285:0.0655015:0.869335:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868886 ES:SE:LP:AF:ID  -8.13631e-05:0.000371928:0.0809219:0.868886:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867827 ES:SE:LP:AF:ID  -0.000153372:0.000371191:0.167491:0.867827:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869025 ES:SE:LP:AF:ID  -7.85573e-05:0.000372225:0.0809219:0.869025:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869034 ES:SE:LP:AF:ID  -7.95403e-05:0.000372253:0.0809219:0.869034:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869041 ES:SE:LP:AF:ID  -7.9359e-05:0.000372262:0.0809219:0.869041:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869518 ES:SE:LP:AF:ID  -6.67496e-05:0.000373272:0.0655015:0.869518:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838181 ES:SE:LP:AF:ID  -1.70791e-05:0.000346916:0.0177288:0.838181:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838302 ES:SE:LP:AF:ID  -1.13449e-05:0.000347162:0.0132283:0.838302:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862185 ES:SE:LP:AF:ID  -2.94124e-05:0.000370929:0.0268721:0.862185:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.70666  ES:SE:LP:AF:ID  -0.000205099:0.00036112:0.244125:0.70666:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105168 ES:SE:LP:AF:ID  0.00024606:0.000416022:0.259637:0.105168:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.76133  ES:SE:LP:AF:ID  -0.000375304:0.000294877:0.69897:0.76133:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106402 ES:SE:LP:AF:ID  0.000596288:0.000406488:0.853872:0.106402:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129648 ES:SE:LP:AF:ID  0.000106435:0.000374574:0.107905:0.129648:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868848 ES:SE:LP:AF:ID  -7.65225e-05:0.000372578:0.0757207:0.868848:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129748 ES:SE:LP:AF:ID  0.000101423:0.000374331:0.102373:0.129748:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868858 ES:SE:LP:AF:ID  -5.94584e-05:0.000372586:0.0604807:0.868858:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265296 ES:SE:LP:AF:ID  -4.12135e-05:0.000329297:0.0457575:0.265296:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870004 ES:SE:LP:AF:ID  -5.0938e-05:0.000373371:0.05061:0.870004:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095081 ES:SE:LP:AF:ID  0.00046576:0.00043293:0.552842:0.095081:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128618 ES:SE:LP:AF:ID  6.79543e-05:0.000374843:0.0655015:0.128618:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128913 ES:SE:LP:AF:ID  6.11011e-05:0.000374214:0.0604807:0.128913:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868741 ES:SE:LP:AF:ID  -8.97336e-05:0.000372376:0.091515:0.868741:rs2977612