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-6806/UKB-b-6806_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6806/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-6806/UKB-b-6806_data.vcf.gz ...
Read summary statistics for 1853086 SNPs.
Dropped 178 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, 476503 SNPs remain.
After merging with regression SNP LD, 476503 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0002 (0.0015)
Lambda GC: 1.1316
Mean Chi^2: 1.1366
Intercept: 1.1388 (0.0118)
Ratio: 1.0161 (0.0863)
Analysis finished at Thu Oct 17 14:40:41 2019
Total time elapsed: 23.18s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.6688,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 6.0952e-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": 14669,
    "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": 476503,
    "ldsc_nsnp_merge_regression_ld": 476503,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.1388,
    "ldsc_intercept_se": 0.0118,
    "ldsc_lambda_gc": 1.1316,
    "ldsc_mean_chisq": 1.1366,
    "ldsc_ratio": 1.0161
}
 

Flags

name value
af_correlation TRUE
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 1.000000 4 58 0 1852910 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 1853086 0.000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA NA NA 8.652252e+00 5.765471e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.871697e+07 5.664065e+07 1.23330e+04 3.185330e+07 6.932034e+07 1.148308e+08 2.491722e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA 6.000000e-07 1.165000e-04 -5.59600e-04 -7.750000e-05 3.000000e-07 7.890000e-05 5.251000e-04 ▁▂▇▂▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 1.090000e-04 3.700000e-06 1.01500e-04 1.062000e-04 1.081000e-04 1.112000e-04 2.083000e-04 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.803088e-01 2.947397e-01 3.00000e-07 2.200002e-01 4.700002e-01 7.400005e-01 1.000000e+00 ▇▇▆▆▆
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.803114e-01 2.947198e-01 3.00000e-07 2.197799e-01 4.726975e-01 7.363467e-01 9.999999e-01 ▇▇▇▆▆
numeric AF 0 1.000000 NA NA NA NA NA NA NA 4.734964e-01 1.170109e-01 2.95858e-01 3.706082e-01 4.600930e-01 5.697980e-01 7.041420e-01 ▇▇▆▅▅
numeric AF_reference 14669 0.992084 NA NA NA NA NA NA NA 4.526888e-01 1.558787e-01 1.99700e-04 3.334660e-01 4.444890e-01 5.652960e-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 -0.0001326 0.0001868 0.4799997 0.4779186 0.623762 0.782149 NA
1 54676 rs2462492 C T 0.0001284 0.0001851 0.4899999 0.4876858 0.400374 NA NA
1 91536 rs6702460 G T -0.0001526 0.0001822 0.4000000 0.4022462 0.456837 0.420727 NA
1 706368 rs55727773 A G -0.0000205 0.0001292 0.8700001 0.8739304 0.515612 0.275160 NA
1 814495 rs74461805 C A -0.0002394 0.0001772 0.1800002 0.1766624 0.340372 NA NA
1 830181 rs28444699 A G 0.0000264 0.0001185 0.8200001 0.8235826 0.697211 0.691294 NA
1 840753 rs4970382 T C -0.0001030 0.0001073 0.3400001 0.3373749 0.400158 0.468850 NA
1 843405 rs11516185 A G -0.0002271 0.0001333 0.0879995 0.0883455 0.362554 0.375399 NA
1 850218 rs6664536 T A -0.0000027 0.0001070 0.9800000 0.9795991 0.590378 0.345248 NA
1 850371 rs6679046 G T -0.0000297 0.0001076 0.7800007 0.7827965 0.603772 0.508786 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51164115 rs5770996 C T -0.0001298 0.0001062 0.2200002 0.2219234 0.456847 0.514776 NA
22 51164287 rs6009957 T C 0.0000315 0.0001143 0.7800007 0.7831655 0.306506 0.415535 NA
22 51165664 rs8137951 G A 0.0000277 0.0001146 0.8100000 0.8087579 0.301510 0.406350 NA
22 51174048 rs9628245 G C 0.0000956 0.0001200 0.4299995 0.4258656 0.380095 0.433107 NA
22 51181919 rs9616825 G C -0.0000685 0.0001210 0.5700002 0.5711782 0.695449 0.619409 NA
22 51186143 rs2879914 T C 0.0002630 0.0001131 0.0200000 0.0200854 0.381787 0.273363 NA
22 51186228 rs3865766 C T 0.0001242 0.0001103 0.2599998 0.2600683 0.451012 0.453275 NA
22 51197266 rs61290853 A G 0.0000015 0.0001139 0.9900000 0.9896608 0.386300 0.422923 NA
22 51212875 rs2238837 A C 0.0002119 0.0001214 0.0810009 0.0809948 0.331442 0.372404 NA
22 51237063 rs3896457 T C 0.0001180 0.0001243 0.3400001 0.3425756 0.297971 0.205072 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623762 ES:SE:LP:AF:ID  -0.000132562:0.000186798:0.318759:0.623762:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400374 ES:SE:LP:AF:ID  0.000128441:0.000185075:0.309804:0.400374:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456837 ES:SE:LP:AF:ID  -0.000152607:0.000182192:0.39794:0.456837:rs6702460
1   706368  rs12029736  A   G   .   PASS    AF=0.515612 ES:SE:LP:AF:ID  -2.04988e-05:0.000129193:0.0604807:0.515612:rs12029736
1   814495  rs74461805  C   A   .   PASS    AF=0.340372 ES:SE:LP:AF:ID  -0.000239379:0.000177173:0.744727:0.340372:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697211 ES:SE:LP:AF:ID  2.6421e-05:0.000118512:0.0861861:0.697211:rs28444699
1   840753  rs4970382   T   C   .   PASS    AF=0.400158 ES:SE:LP:AF:ID  -0.000102984:0.000107346:0.468521:0.400158:rs4970382
1   843405  rs11516185  A   G   .   PASS    AF=0.362554 ES:SE:LP:AF:ID  -0.000227143:0.000133285:1.05552:0.362554:rs11516185
1   850218  rs6664536   T   A   .   PASS    AF=0.590378 ES:SE:LP:AF:ID  -2.73728e-06:0.000107044:0.00877392:0.590378:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603772 ES:SE:LP:AF:ID  -2.96752e-05:0.000107645:0.107905:0.603772:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.603992 ES:SE:LP:AF:ID  -1.94382e-05:0.00010763:0.0655015:0.603992:rs6657440
1   852037  rs4970463   G   A   .   PASS    AF=0.58974  ES:SE:LP:AF:ID  -2.08133e-06:0.000107218:0.00877392:0.58974:rs4970463
1   852063  rs28436996  G   A   .   PASS    AF=0.589718 ES:SE:LP:AF:ID  -3.3877e-06:0.00010717:0.0132283:0.589718:rs28436996
1   852875  rs13303369  C   T   .   PASS    AF=0.607721 ES:SE:LP:AF:ID  -4.17597e-05:0.000107869:0.154902:0.607721:rs13303369
1   853954  rs1806509   C   A   .   PASS    AF=0.60788  ES:SE:LP:AF:ID  -4.25508e-05:0.000107884:0.161151:0.60788:rs1806509
1   854777  rs13303019  A   G   .   PASS    AF=0.610365 ES:SE:LP:AF:ID  -3.83005e-05:0.000107987:0.142668:0.610365:rs13303019
1   854978  rs13303057  A   C   .   PASS    AF=0.603334 ES:SE:LP:AF:ID  -3.2385e-05:0.000107671:0.119186:0.603334:rs13303057
1   855075  rs6673914   C   G   .   PASS    AF=0.610384 ES:SE:LP:AF:ID  -3.94108e-05:0.00010799:0.142668:0.610384:rs6673914
1   856099  rs28534711  T   G   .   PASS    AF=0.389888 ES:SE:LP:AF:ID  3.55031e-05:0.000108011:0.130768:0.389888:rs28534711
1   856108  rs28742275  A   G   .   PASS    AF=0.389871 ES:SE:LP:AF:ID  3.55283e-05:0.000108016:0.130768:0.389871:rs28742275
1   856476  rs4040605   A   G   .   PASS    AF=0.350338 ES:SE:LP:AF:ID  1.65609e-05:0.00011096:0.0555173:0.350338:rs4040605
1   866893  rs2880024   T   C   .   PASS    AF=0.610538 ES:SE:LP:AF:ID  4.81965e-05:0.000108587:0.180456:0.610538:rs2880024
1   868418  rs28546443  C   T   .   PASS    AF=0.297956 ES:SE:LP:AF:ID  -1.78798e-05:0.000119297:0.0555173:0.297956:rs28546443
1   875770  rs4970379   A   G   .   PASS    AF=0.60008  ES:SE:LP:AF:ID  3.99484e-05:0.000109499:0.142668:0.60008:rs4970379
1   881627  rs2272757   G   A   .   PASS    AF=0.652381 ES:SE:LP:AF:ID  -5.66218e-05:0.000110613:0.21467:0.652381:rs2272757
1   891059  rs13303065  C   T   .   PASS    AF=0.652417 ES:SE:LP:AF:ID  -6.31722e-05:0.000110596:0.244125:0.652417:rs13303065
1   891945  rs13303106  A   G   .   PASS    AF=0.65248  ES:SE:LP:AF:ID  -6.48218e-05:0.000110725:0.251812:0.65248:rs13303106
1   903245  rs28690976  A   G   .   PASS    AF=0.566954 ES:SE:LP:AF:ID  -0.000118932:0.000109974:0.552842:0.566954:rs28690976
1   909073  rs3892467   C   T   .   PASS    AF=0.386707 ES:SE:LP:AF:ID  1.77205e-06:0.000109673:0.00436481:0.386707:rs3892467
1   909238  rs3829740   G   C   .   PASS    AF=0.571441 ES:SE:LP:AF:ID  -8.25659e-06:0.000106224:0.0268721:0.571441:rs3829740
1   910394  rs28477686  C   T   .   PASS    AF=0.324429 ES:SE:LP:AF:ID  9.57858e-05:0.000115127:0.387216:0.324429:rs28477686
1   912049  rs7367995   T   C   .   PASS    AF=0.585283 ES:SE:LP:AF:ID  -0.000101219:0.000107289:0.455932:0.585283:rs7367995
1   913889  rs2340596   G   A   .   PASS    AF=0.599256 ES:SE:LP:AF:ID  -0.000128555:0.000107465:0.638272:0.599256:rs2340596
1   914333  rs13302979  C   G   .   PASS    AF=0.60256  ES:SE:LP:AF:ID  -0.000131501:0.000107791:0.657577:0.60256:rs13302979
1   914852  rs13303368  G   C   .   PASS    AF=0.600122 ES:SE:LP:AF:ID  -0.000124116:0.000107583:0.60206:0.600122:rs13303368
1   914940  rs13303033  T   C   .   PASS    AF=0.584344 ES:SE:LP:AF:ID  -0.000131678:0.000106983:0.657577:0.584344:rs13303033
1   916834  rs6694632   G   A   .   PASS    AF=0.589154 ES:SE:LP:AF:ID  -0.00014634:0.000107146:0.769551:0.589154:rs6694632
1   918384  rs13303118  G   T   .   PASS    AF=0.584256 ES:SE:LP:AF:ID  -0.000135709:0.000106933:0.69897:0.584256:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.589378 ES:SE:LP:AF:ID  -0.000150994:0.000107064:0.79588:0.589378:rs2341354
1   919501  rs4970414   G   T   .   PASS    AF=0.583961 ES:SE:LP:AF:ID  -0.000118464:0.000110724:0.552842:0.583961:rs4970414
1   921716  rs13303278  C   A   .   PASS    AF=0.567942 ES:SE:LP:AF:ID  -3.33604e-05:0.000106841:0.124939:0.567942:rs13303278
1   924528  rs34712273  C   A   .   PASS    AF=0.578551 ES:SE:LP:AF:ID  -3.20519e-05:0.000107146:0.119186:0.578551:rs34712273
1   930533  rs3128110   C   G   .   PASS    AF=0.386003 ES:SE:LP:AF:ID  -2.22567e-05:0.000108523:0.0757207:0.386003:rs3128110
1   930567  rs3121574   A   G   .   PASS    AF=0.386046 ES:SE:LP:AF:ID  -2.26066e-05:0.000108526:0.0809219:0.386046:rs3121574
1   930751  rs3128111   C   G   .   PASS    AF=0.384998 ES:SE:LP:AF:ID  -1.78933e-05:0.000108592:0.0604807:0.384998:rs3128111
1   931166  rs2710880   A   G   .   PASS    AF=0.386688 ES:SE:LP:AF:ID  -2.2904e-05:0.000108544:0.0809219:0.386688:rs2710880
1   931362  rs2799060   G   A   .   PASS    AF=0.385491 ES:SE:LP:AF:ID  -1.64346e-05:0.000108597:0.0555173:0.385491:rs2799060
1   933790  rs9442392   G   A   .   PASS    AF=0.578675 ES:SE:LP:AF:ID  6.7038e-06:0.000107111:0.0222764:0.578675:rs9442392
1   936111  rs1936360   C   T   .   PASS    AF=0.573616 ES:SE:LP:AF:ID  5.89063e-06:0.000107084:0.0177288:0.573616:rs1936360
1   940005  rs2799056   A   G   .   PASS    AF=0.39919  ES:SE:LP:AF:ID  4.50884e-05:0.000108145:0.167491:0.39919:rs2799056