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/dev/ieu-a-import/processed/ieu-a-293/ieu-a-293.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-293/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Tue Feb  4 20:11:16 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-293/ieu-a-293.vcf.gz ...
Read summary statistics for 105904 SNPs.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 48029 SNPs remain.
After merging with regression SNP LD, 48029 SNPs remain.
WARNING: number of SNPs less than 200k; this is almost always bad.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 1.8295 (0.5279)
Lambda GC: 1.3161
Mean Chi^2: 1.4178
Intercept: 1.1678 (0.0359)
Ratio: 0.4017 (0.086)
Analysis finished at Tue Feb  4 20:11:27 2020
Total time elapsed: 11.0s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.7588,
    "inflation_factor": 1.5447,
    "mean_EFFECT": -0.033,
    "n": 6543,
    "n_snps": 105904,
    "n_clumped_hits": 11,
    "n_p_sig": 268,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 5536,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 3740,
    "n_miss_AF_reference": 737,
    "n_est": 6478.4279,
    "ratio_se_n": 0.9951,
    "mean_diff": 0.0876,
    "ratio_diff": 2.4034,
    "sd_y_est1": 2.0417,
    "sd_y_est2": 2.0316,
    "r2_sum1": 0.469,
    "r2_sum2": 0.1125,
    "r2_sum3": 0.1136,
    "r2_sum4": 0.101,
    "ldsc_nsnp_merge_refpanel_ld": 48029,
    "ldsc_nsnp_merge_regression_ld": 48029,
    "ldsc_observed_scale_h2_beta": 1.8295,
    "ldsc_observed_scale_h2_se": 0.5279,
    "ldsc_intercept_beta": 1.1678,
    "ldsc_intercept_se": 0.0359,
    "ldsc_lambda_gc": 1.3161,
    "ldsc_mean_chisq": 1.4178,
    "ldsc_ratio": 0.4016
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 5 25 0 105904 0 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
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.143082e+00 5.782781e+00 1.00000e+00 3.000000e+00 6.000000e+00 1.200000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.867000e+07 5.784617e+07 6.34110e+04 3.270455e+07 6.217320e+07 1.173609e+08 2.492107e+08 ▇▅▃▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.301550e-02 2.083430e+00 -4.00903e+02 -4.686230e-02 -6.526000e-04 4.852560e-02 1.232140e+02 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.047675e-01 1.438244e+00 3.34868e-02 3.801830e-02 4.677980e-02 8.305070e-02 2.598160e+02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.365174e-01 2.974823e-01 0.00000e+00 1.762147e-01 4.018718e-01 6.885381e-01 9.999950e-01 ▇▆▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.365038e-01 2.974928e-01 0.00000e+00 1.761944e-01 4.018674e-01 6.885353e-01 9.999934e-01 ▇▆▅▅▅
numeric AF 3740 0.9646850 NA NA NA NA NA 3.562987e-01 3.023070e-01 1.34000e-04 8.510000e-02 2.852000e-01 5.854000e-01 9.998660e-01 ▇▃▃▂▂
numeric AF_reference 737 0.9930409 NA NA NA NA NA 3.200214e-01 2.486206e-01 1.99700e-04 1.152160e-01 2.517970e-01 4.840260e-01 1.000000e+00 ▇▅▃▂▁
numeric N 0 1.0000000 NA NA NA NA NA 6.543000e+03 0.000000e+00 6.54300e+03 6.543000e+03 6.543000e+03 6.543000e+03 6.543000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 1118275 rs61733845 C T -0.1473040 0.0764224 0.0539523 0.0539176 0.059290 0.185703 6543
1 1120431 rs1320571 G A 0.0467260 0.0493890 0.3441082 0.3441072 0.161100 0.185304 6543
1 1135242 rs9729550 A C 0.1521630 0.0542741 0.0050658 0.0050535 0.875200 0.551917 6543
1 1140435 rs1815606 G T 0.1833880 0.0786739 0.0197756 0.0197539 0.943800 0.712061 6543
1 1163804 rs7515488 C T 0.0785316 0.0438666 0.0734480 0.0734159 0.197100 0.186901 6543
1 1165310 rs11260562 G A -0.0000853 0.1126260 0.9993960 0.9993957 0.024330 0.101837 6543
1 1173611 rs6697886 G A 0.0805256 0.0454806 0.0766673 0.0766358 0.177500 0.220647 6543
1 1186502 rs6603785 A T 0.0735698 0.0409197 0.0722237 0.0721918 0.226000 0.246206 6543
1 1194804 rs11804831 T C -0.7625160 0.3315470 0.0214763 0.0214554 0.998387 0.685903 6543
1 1218086 rs6603788 C T -0.0462073 0.0365991 0.2067859 0.2067597 0.634200 0.469449 6543
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 50960682 rs140524 C T 0.0184483 0.0416857 0.6580896 0.6580862 0.22820 0.230232 6543
22 50966914 rs470119 T C -0.0212828 0.0395447 0.5904485 0.5904417 0.72920 0.554712 6543
22 50971752 rs131794 A C -0.0707653 0.0785954 0.3679366 0.3679209 0.95066 0.832668 6543
22 50988193 rs131779 A G -0.0602363 0.0374811 0.1080570 0.1080300 0.62410 0.580272 6543
22 50999182 rs140518 C T 0.1368710 0.0854370 0.1091900 0.1091532 0.95308 0.765575 6543
22 51078251 rs4040041 C T 0.0771944 0.0411566 0.0607463 0.0607066 0.74760 0.466653 6543
22 51094926 rs9616810 C T 0.0094711 0.0365473 0.7955209 0.7955219 0.46100 0.222444 6543
22 51105556 rs9616812 C T -0.1051160 0.0539749 0.0515169 0.0514751 0.13750 0.362819 6543
22 51109992 rs9628185 T C -0.1109260 0.0475190 0.0196209 0.0195774 0.18100 0.405351 6543
22 51156666 rs9628187 C T 0.0053517 0.1435930 0.9702700 0.9702698 0.01492 0.129992 6543

bcf preview

1   1118275 rs61733845  C   T   .   PASS    AF=0.05929  ES:SE:LP:AF:SS:ID   -0.147304:0.0764224:1.26799:0.05929:6543:rs61733845
1   1120431 rs1320571   G   A   .   PASS    AF=0.1611   ES:SE:LP:AF:SS:ID   0.046726:0.049389:0.463305:0.1611:6543:rs1320571
1   1135242 rs9729550   A   C   .   PASS    AF=0.8752   ES:SE:LP:AF:SS:ID   0.152163:0.0542741:2.29535:0.8752:6543:rs9729550
1   1140435 rs1815606   G   T   .   PASS    AF=0.9438   ES:SE:LP:AF:SS:ID   0.183388:0.0786739:1.70387:0.9438:6543:rs1815606
1   1163804 rs7515488   C   T   .   PASS    AF=0.1971   ES:SE:LP:AF:SS:ID   0.0785316:0.0438666:1.13402:0.1971:6543:rs7515488
1   1165310 rs11260562  G   A   .   PASS    AF=0.02433  ES:SE:LP:AF:SS:ID   -8.53e-05:0.112626:0.000262393:0.02433:6543:rs11260562
1   1173611 rs6697886   G   A   .   PASS    AF=0.1775   ES:SE:LP:AF:SS:ID   0.0805256:0.0454806:1.11539:0.1775:6543:rs6697886
1   1186502 rs6603785   A   T   .   PASS    AF=0.226    ES:SE:LP:AF:SS:ID   0.0735698:0.0409197:1.14132:0.226:6543:rs6603785
1   1194804 rs11804831  T   C   .   PASS    AF=0.998387 ES:SE:LP:AF:SS:ID   -0.762516:0.331547:1.66804:0.998387:6543:rs11804831
1   1218086 rs6603788   C   T   .   PASS    AF=0.6342   ES:SE:LP:AF:SS:ID   -0.0462073:0.0365991:0.684479:0.6342:6543:rs6603788
1   1227897 rs3737721   A   G   .   PASS    AF=0.5565   ES:SE:LP:AF:SS:ID   -0.0428162:0.0360064:0.630011:0.5565:6543:rs3737721
1   1231656 rs1749951   G   A   .   PASS    AF=0.1202   ES:SE:LP:AF:SS:ID   0.0304384:0.0560476:0.231314:0.1202:6543:rs1749951
1   1233941 rs1739855   T   C   .   PASS    AF=0.6959   ES:SE:LP:AF:SS:ID   -0.0592382:0.0397565:0.865788:0.6959:6543:rs1739855
1   1241529 rs1536168   A   G   .   PASS    AF=0.8227   ES:SE:LP:AF:SS:ID   0.0416447:0.047012:0.425145:0.8227:6543:rs1536168
1   1242468 rs2274264   G   A   .   PASS    AF=0.5043   ES:SE:LP:AF:SS:ID   -0.0287189:0.0358181:0.37399:0.5043:6543:rs2274264
1   1247494 rs12103 T   C   .   PASS    AF=0.008604 ES:SE:LP:AF:SS:ID   -0.57994:0.215319:2.14954:0.008604:6543:rs12103
1   1249187 rs12142199  G   A   .   PASS    AF=0.008067 ES:SE:LP:AF:SS:ID   -0.50885:0.217646:1.71197:0.008067:6543:rs12142199
1   1254255 rs62623580  G   A   .   PASS    AF=0.06319  ES:SE:LP:AF:SS:ID   -0.129877:0.0733573:1.11526:0.06319:6543:rs62623580
1   1335790 rs1240708   A   G   .   PASS    AF=0.991799 ES:SE:LP:AF:SS:ID   0.517444:0.216846:1.76848:0.991799:6543:rs1240708
1   1493727 rs880051    G   A   .   PASS    AF=0.7324   ES:SE:LP:AF:SS:ID   0.110623:0.0399213:2.25188:0.7324:6543:rs880051
1   1497824 rs2296716   C   T   .   PASS    AF=0.3606   ES:SE:LP:AF:SS:ID   0.136144:0.0351477:3.96648:0.3606:6543:rs2296716
1   1611995 rs4074196   A   G   .   PASS    AF=0.6309   ES:SE:LP:AF:SS:ID   -0.0638152:0.0373276:1.05826:0.6309:6543:rs4074196
1   1706160 rs7531583   A   G   .   PASS    AF=0.7006   ES:SE:LP:AF:SS:ID   -0.0300084:0.0382334:0.36397:0.7006:6543:rs7531583
1   1721479 rs2272908   C   T   .   PASS    AF=0.5008   ES:SE:LP:AF:SS:ID   -0.0476858:0.0355818:0.744163:0.5008:6543:rs2272908
1   1723031 rs9660180   G   A   .   PASS    AF=0.5003   ES:SE:LP:AF:SS:ID   -0.0470707:0.0355747:0.730887:0.5003:6543:rs9660180
1   1781220 rs6681938   T   C   .   PASS    AF=0.167    ES:SE:LP:AF:SS:ID   -0.0564974:0.0493996:0.597192:0.167:6543:rs6681938
1   1838516 rs2377037   C   A   .   PASS    AF=0.2084   ES:SE:LP:AF:SS:ID   0.00257386:0.0432169:0.0211309:0.2084:6543:rs2377037
1   1840038 rs2474461   T   C   .   PASS    AF=0.8669   ES:SE:LP:AF:SS:ID   -0.0395665:0.0517825:0.351809:0.8669:6543:rs2474461
1   1853288 rs1884454   G   T   .   PASS    AF=0.2116   ES:SE:LP:AF:SS:ID   0.0191301:0.0430715:0.182478:0.2116:6543:rs1884454
1   1855319 rs2295362   C   T   .   PASS    AF=0.1342   ES:SE:LP:AF:SS:ID   0.0109629:0.0524567:0.0785955:0.1342:6543:rs2295362
1   1871337 rs16824543  G   A   .   PASS    AF=0.1354   ES:SE:LP:AF:SS:ID   0.00360636:0.0522953:0.0245585:0.1354:6543:rs16824543
1   1873625 rs12758705  G   A   .   PASS    AF=0.2123   ES:SE:LP:AF:SS:ID   0.0160472:0.0430521:0.149144:0.2123:6543:rs12758705
1   1881070 rs4648596   G   A   .   PASS    AF=0.08483  ES:SE:LP:AF:SS:ID   -0.0790391:0.064085:0.662605:0.08483:6543:rs4648596
1   1888193 rs3820011   C   A   .   PASS    AF=0.299    ES:SE:LP:AF:SS:ID   0.00828347:0.0392559:0.0794197:0.299:6543:rs3820011
1   2024064 rs2459994   C   T   .   PASS    AF=0.556    ES:SE:LP:AF:SS:ID   0.0271067:0.0370816:0.332726:0.556:6543:rs2459994
1   2146966 rs7512482   T   C   .   PASS    AF=0.1026   ES:SE:LP:AF:SS:ID   -0.00833152:0.0596079:0.0511764:0.1026:6543:rs7512482
1   2202774 rs6673129   C   T   .   PASS    AF=0.014    ES:SE:LP:AF:SS:ID   -0.0480971:0.147588:0.128131:0.014:6543:rs6673129
1   2229478 rs12562937  C   T   .   PASS    AF=0.4442   ES:SE:LP:AF:SS:ID   -0.00666453:0.0372121:0.0665805:0.4442:6543:rs12562937
1   2283896 rs2840528   A   G   .   PASS    AF=0.4063   ES:SE:LP:AF:SS:ID   -0.0164759:0.037226:0.181738:0.4063:6543:rs2840528
1   2404256 rs2494626   C   T   .   PASS    AF=0.2058   ES:SE:LP:AF:SS:ID   0.0278548:0.0450145:0.270783:0.2058:6543:rs2494626
1   2407781 rs78504402  C   T   .   PASS    AF=0.000269 ES:SE:LP:AF:SS:ID   -0.260402:1.1736:0.0838594:0.000269:6543:rs78504402
1   2408471 rs115996655 G   A   .   PASS    AF=0.02097  ES:SE:LP:AF:SS:ID   0.108344:0.118715:0.441957:0.02097:6543:rs115996655
1   2408834 rs11588930  G   A   .   PASS    .   ES:SE:LP:SS:ID  2.06512:2.3088:0.430524:6543:rs11588930
1   2409892 rs12727342  A   G   .   PASS    AF=0.864    ES:SE:LP:AF:SS:ID   0.0124819:0.0521407:0.0910847:0.864:6543:rs12727342
1   2410789 rs11799501  C   T   .   PASS    AF=0.8453   ES:SE:LP:AF:SS:ID   -0.0327137:0.0485661:0.300529:0.8453:6543:rs11799501
1   2412279 rs4648638   A   T   .   PASS    AF=0.1592   ES:SE:LP:AF:SS:ID   0.0370578:0.0478423:0.357933:0.1592:6543:rs4648638
1   2412293 rs12731186  C   T   .   PASS    AF=0.1108   ES:SE:LP:AF:SS:ID   -0.00729088:0.0573027:0.0463592:0.1108:6543:rs12731186
1   2413464 rs114424485 G   C   .   PASS    AF=0.01143  ES:SE:LP:AF:SS:ID   0.280168:0.152432:1.1798:0.01143:6543:rs114424485
1   2413634 rs942817    G   C   .   PASS    AF=0.8471   ES:SE:LP:AF:SS:ID   -0.0250938:0.0487163:0.217178:0.8471:6543:rs942817
1   2414928 rs4995304   G   A   .   PASS    AF=0.8415   ES:SE:LP:AF:SS:ID   -0.0236428:0.0480086:0.205937:0.8415:6543:rs4995304