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-15904/UKB-b-15904_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15904/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-15904/UKB-b-15904_data.vcf.gz ...
Read summary statistics for 5579971 SNPs.
Dropped 2123 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, 1180715 SNPs remain.
After merging with regression SNP LD, 1180715 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0064 (0.0014)
Lambda GC: 1.0647
Mean Chi^2: 1.0824
Intercept: 1.0206 (0.0076)
Ratio: 0.2504 (0.0924)
Analysis finished at Thu Oct 17 14:45:40 2019
Total time elapsed: 1.0m:6.33s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.918,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 1.5377e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 4,
    "n_p_sig": 269,
    "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": 49174,
    "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": 1180715,
    "ldsc_nsnp_merge_regression_ld": 1180715,
    "ldsc_observed_scale_h2_beta": 0.0064,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0206,
    "ldsc_intercept_se": 0.0076,
    "ldsc_lambda_gc": 1.0647,
    "ldsc_mean_chisq": 1.0824,
    "ldsc_ratio": 0.25
}

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 5577864 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 5579971 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 8.672279e+00 5.763307e+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 7.858783e+07 5.656131e+07 828.0000000 3.198960e+07 6.901533e+07 1.145250e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.500000e-06 3.958000e-04 -0.0029362 -2.428000e-04 -9.000000e-07 2.450000e-04 3.058800e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.702000e-04 1.056000e-04 0.0002574 2.822000e-04 3.305000e-04 4.339000e-04 1.217300e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.901653e-01 2.917619e-01 0.0000000 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 4.901651e-01 2.917346e-01 0.0000000 2.347672e-01 4.866002e-01 7.434996e-01 9.999996e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.280959e-01 2.482093e-01 0.0451330 1.161560e-01 2.528170e-01 4.948270e-01 9.548660e-01 ▇▃▂▂▁
numeric AF_reference 49174 0.9911874 NA NA NA NA NA NA NA 3.234787e-01 2.424953e-01 0.0000000 1.240020e-01 2.583870e-01 4.848240e-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 0.0003600 0.0004738 0.4500005 0.4473122 0.623763 0.7821490 NA
1 54676 rs2462492 C T -0.0004458 0.0004694 0.3400001 0.3422026 0.400401 NA NA
1 86028 rs114608975 T C -0.0006811 0.0007504 0.3599996 0.3640516 0.103556 0.0277556 NA
1 91536 rs6702460 G T -0.0004678 0.0004621 0.3100002 0.3114312 0.456851 0.4207270 NA
1 234313 rs8179466 C T -0.0008054 0.0009112 0.3800004 0.3767527 0.074508 NA NA
1 534192 rs6680723 C T 0.0007385 0.0005279 0.1600000 0.1618390 0.240960 NA NA
1 546697 rs12025928 A G 0.0003927 0.0006586 0.5500004 0.5509502 0.913473 NA NA
1 693731 rs12238997 A G 0.0000831 0.0004424 0.8499999 0.8510328 0.116325 0.1417730 NA
1 705882 rs72631875 G A -0.0005305 0.0006483 0.4100001 0.4131684 0.067285 0.0315495 NA
1 706368 rs55727773 A G -0.0001228 0.0003277 0.7099994 0.7078009 0.515650 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218224 rs9616975 C A 0.0014958 0.0005127 0.0035000 0.0035274 0.073336 0.0619010 NA
22 51218377 rs2519461 G C 0.0015625 0.0005121 0.0023000 0.0022793 0.073625 0.0826677 NA
22 51219006 rs28729663 G A 0.0011598 0.0003953 0.0033000 0.0033467 0.137953 0.2052720 NA
22 51219387 rs9616832 T C 0.0015311 0.0005131 0.0028000 0.0028463 0.073747 0.0654952 NA
22 51221190 rs369304721 G A 0.0019576 0.0006865 0.0043000 0.0043493 0.049731 NA NA
22 51221731 rs115055839 T C 0.0015291 0.0005134 0.0029000 0.0028996 0.073238 0.0625000 NA
22 51222100 rs114553188 G T 0.0004323 0.0006045 0.4700002 0.4745482 0.054459 0.0880591 NA
22 51223637 rs375798137 G A 0.0004467 0.0006074 0.4600002 0.4620388 0.054088 0.0788738 NA
22 51229805 rs9616985 T C 0.0015800 0.0005153 0.0022000 0.0021681 0.073073 0.0730831 NA
22 51237063 rs3896457 T C -0.0007985 0.0003152 0.0109999 0.0112883 0.297971 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  0.000360015:0.000473764:0.346787:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  -0.0004458:0.000469351:0.468521:0.400401:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103556 ES:SE:LP:AF:ID  -0.000681117:0.0007504:0.443698:0.103556:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  -0.00046779:0.000462141:0.508638:0.456851:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074508 ES:SE:LP:AF:ID  -0.000805417:0.000911213:0.420216:0.074508:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.24096  ES:SE:LP:AF:ID  0.000738457:0.000527879:0.79588:0.24096:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913473 ES:SE:LP:AF:ID  0.000392723:0.000658559:0.259637:0.913473:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116325 ES:SE:LP:AF:ID  8.30812e-05:0.00044239:0.0705811:0.116325:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067285 ES:SE:LP:AF:ID  -0.0005305:0.000648271:0.387216:0.067285:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  -0.000122826:0.000327701:0.148742:0.51565:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101199 ES:SE:LP:AF:ID  0.000116855:0.000540686:0.0809219:0.101199:rs116030099
1   725060  rs865924913 A   T   .   PASS    AF=0.053254 ES:SE:LP:AF:ID  -0.00124524:0.0010336:0.638272:0.053254:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.843212 ES:SE:LP:AF:ID  5.94332e-05:0.000383387:0.0555173:0.843212:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055911 ES:SE:LP:AF:ID  -0.000735091:0.000620764:0.619789:0.055911:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122307 ES:SE:LP:AF:ID  7.84481e-05:0.000419651:0.0705811:0.122307:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121549 ES:SE:LP:AF:ID  0.000102656:0.000419827:0.091515:0.121549:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.13233  ES:SE:LP:AF:ID  -0.000197814:0.000413781:0.200659:0.13233:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838951 ES:SE:LP:AF:ID  0.00019131:0.000371283:0.21467:0.838951:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83858  ES:SE:LP:AF:ID  0.000188203:0.000370884:0.21467:0.83858:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869781 ES:SE:LP:AF:ID  3.24342e-05:0.000397973:0.0268721:0.869781:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129871 ES:SE:LP:AF:ID  -3.06173e-05:0.000398788:0.0268721:0.129871:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869123 ES:SE:LP:AF:ID  2.97393e-05:0.000397194:0.0268721:0.869123:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869221 ES:SE:LP:AF:ID  3.44998e-05:0.000397351:0.0315171:0.869221:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869126 ES:SE:LP:AF:ID  2.89118e-05:0.000397186:0.0268721:0.869126:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838033 ES:SE:LP:AF:ID  0.000190614:0.000369854:0.21467:0.838033:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838664 ES:SE:LP:AF:ID  0.000182382:0.000370894:0.207608:0.838664:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839777 ES:SE:LP:AF:ID  0.000111633:0.00037591:0.113509:0.839777:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869405 ES:SE:LP:AF:ID  1.4173e-05:0.000396726:0.0132283:0.869405:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868952 ES:SE:LP:AF:ID  4.1509e-05:0.000395728:0.0362122:0.868952:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867905 ES:SE:LP:AF:ID  4.68141e-05:0.00039497:0.0409586:0.867905:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869095 ES:SE:LP:AF:ID  2.52678e-05:0.000396052:0.0222764:0.869095:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  2.54128e-05:0.000396083:0.0222764:0.869104:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869112 ES:SE:LP:AF:ID  2.43384e-05:0.000396092:0.0222764:0.869112:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869589 ES:SE:LP:AF:ID  3.8765e-05:0.000397179:0.0362122:0.869589:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838313 ES:SE:LP:AF:ID  0.000192956:0.000369153:0.221849:0.838313:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838434 ES:SE:LP:AF:ID  0.000187726:0.000369413:0.21467:0.838434:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862261 ES:SE:LP:AF:ID  0.000123091:0.000394659:0.119186:0.862261:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  -0.000203442:0.000384198:0.221849:0.706753:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105142 ES:SE:LP:AF:ID  2.42199e-05:0.000442593:0.0177288:0.105142:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761304 ES:SE:LP:AF:ID  -0.000132462:0.000313574:0.173925:0.761304:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106488 ES:SE:LP:AF:ID  0.00037715:0.000432201:0.420216:0.106488:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129576 ES:SE:LP:AF:ID  -6.10724e-05:0.00039855:0.0555173:0.129576:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868911 ES:SE:LP:AF:ID  6.08957e-05:0.000396421:0.0555173:0.868911:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129677 ES:SE:LP:AF:ID  -6.14623e-05:0.000398292:0.0555173:0.129677:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868921 ES:SE:LP:AF:ID  7.16419e-05:0.000396429:0.0655015:0.868921:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.26539  ES:SE:LP:AF:ID  -5.53912e-06:0.000350267:0.00436481:0.26539:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870044 ES:SE:LP:AF:ID  5.35804e-05:0.000397238:0.05061:0.870044:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095139 ES:SE:LP:AF:ID  0.000333041:0.000460382:0.327902:0.095139:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128576 ES:SE:LP:AF:ID  -6.37247e-05:0.000398805:0.0604807:0.128576:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128873 ES:SE:LP:AF:ID  -7.26937e-05:0.000398129:0.0655015:0.128873:rs4040617