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-12/ieu-a-12.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-12/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Wed Feb  5 11:41:45 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-12/ieu-a-12.vcf.gz ...
Read summary statistics for 124047 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, 50575 SNPs remain.
After merging with regression SNP LD, 50575 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: 4.3438 (0.612)
Lambda GC: 2.4421
Mean Chi^2: 6.1972
Intercept: 1.4396 (0.0638)
Ratio: 0.0846 (0.0123)
Analysis finished at Wed Feb  5 11:41:54 2020
Total time elapsed: 8.78s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.7663,
    "inflation_factor": 2.9586,
    "mean_EFFECT": 0.0019,
    "n": 51874,
    "n_snps": 124047,
    "n_clumped_hits": 122,
    "n_p_sig": 7134,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 13,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 830,
    "n_est": 52130.8113,
    "ratio_se_n": 1.0025,
    "mean_diff": -0.0005,
    "ratio_diff": 1.0563,
    "sd_y_est1": 1.9872,
    "sd_y_est2": 1.9921,
    "r2_sum1": 0.8221,
    "r2_sum2": 0.2082,
    "r2_sum3": 0.2071,
    "r2_sum4": 0.2111,
    "ldsc_nsnp_merge_refpanel_ld": 50575,
    "ldsc_nsnp_merge_regression_ld": 50575,
    "ldsc_observed_scale_h2_beta": 4.3438,
    "ldsc_observed_scale_h2_se": 0.612,
    "ldsc_intercept_beta": 1.4396,
    "ldsc_intercept_se": 0.0638,
    "ldsc_lambda_gc": 2.4421,
    "ldsc_mean_chisq": 6.1972,
    "ldsc_ratio": 0.0846
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio FALSE
ldsc_intercept_beta FALSE
n_clumped_hits FALSE
r2_sum1 TRUE
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 1.000000 5 25 0 124047 0 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
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 8.086854e+00 5.770931e+00 1.00000e+00 3.000000e+00 6.000000e+00 1.200000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.900678e+07 5.780674e+07 6.34110e+04 3.285889e+07 6.220178e+07 1.176445e+08 2.492107e+08 ▇▅▃▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA 1.898400e-03 6.034380e-02 -1.26172e+00 -2.247820e-02 7.310000e-04 2.421810e-02 1.514640e+00 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 2.547520e-02 2.734180e-02 1.18048e-02 1.330840e-02 1.650210e-02 2.592860e-02 8.952510e-01 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 3.347239e-01 3.167052e-01 0.00000e+00 2.817380e-02 2.459869e-01 5.967370e-01 9.999835e-01 ▇▃▂▂▂
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 3.347239e-01 3.167052e-01 0.00000e+00 2.817410e-02 2.459860e-01 5.967376e-01 9.999835e-01 ▇▃▂▂▂
numeric AF 0 1.000000 NA NA NA NA NA 3.135413e-01 2.824889e-01 1.49000e-05 7.389000e-02 2.238000e-01 5.011000e-01 9.999850e-01 ▇▃▂▂▂
numeric AF_reference 830 0.993309 NA NA NA NA NA 2.875278e-01 2.574872e-01 1.99700e-04 7.488020e-02 2.076680e-01 4.476840e-01 1.000000e+00 ▇▃▂▂▁
numeric N 0 1.000000 NA NA NA NA NA 5.187400e+04 0.000000e+00 5.18740e+04 5.187400e+04 5.187400e+04 5.187400e+04 5.187400e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 1118275 rs61733845 C T -0.0294999 0.0307510 0.3374007 0.3374000 0.04416 0.185703 51874
1 1120431 rs1320571 G A -0.0229954 0.0301098 0.4450348 0.4450352 0.04653 0.185304 51874
1 1135242 rs9729550 A C 0.0524943 0.0141053 0.0001980 0.0001980 0.25870 0.551917 51874
1 1140435 rs1815606 G T 0.0432499 0.0136608 0.0015456 0.0015456 0.31790 0.712061 51874
1 1163804 rs7515488 C T 0.0840669 0.0167779 0.0000005 0.0000005 0.14860 0.186901 51874
1 1165310 rs11260562 G A 0.0821914 0.0253050 0.0011621 0.0011621 0.05560 0.101837 51874
1 1173611 rs6697886 G A 0.0872903 0.0174247 0.0000005 0.0000005 0.13730 0.220647 51874
1 1186502 rs6603785 A T 0.0839047 0.0185783 0.0000063 0.0000063 0.11950 0.246206 51874
1 1194804 rs11804831 T C 0.0644855 0.0156228 0.0000366 0.0000366 0.18560 0.685903 51874
1 1218086 rs6603788 C T 0.0278539 0.0227151 0.2201132 0.2201127 0.07697 0.469449 51874
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 50960682 rs140524 C T 0.0213042 0.0161293 0.1865559 0.1865552 0.1709 0.230232 51874
22 50966914 rs470119 T C -0.0445357 0.0123360 0.0003059 0.0003059 0.6098 0.554712 51874
22 50971752 rs131794 A C -0.0455758 0.0146924 0.0019222 0.0019222 0.7919 0.832668 51874
22 50988193 rs131779 A G -0.0241081 0.0131541 0.0668405 0.0668406 0.6579 0.580272 51874
22 50999182 rs140518 C T -0.0176681 0.0132186 0.1813506 0.1813503 0.6966 0.765575 51874
22 51078251 rs4040041 C T -0.0075038 0.0125603 0.5502233 0.5502230 0.3731 0.466653 51874
22 51094926 rs9616810 C T -0.0036593 0.0147696 0.8043223 0.8043215 0.2186 0.222444 51874
22 51105556 rs9616812 C T 0.0053232 0.0124593 0.6692001 0.6692011 0.4832 0.362819 51874
22 51109992 rs9628185 T C 0.0090266 0.0124944 0.4700153 0.4700149 0.4843 0.405351 51874
22 51156666 rs9628187 C T -0.0018783 0.0157831 0.9052720 0.9052718 0.2032 0.129992 51874

bcf preview

1   1118275 rs61733845  C   T   .   PASS    AF=0.04416  ES:SE:LP:AF:SS:ID   -0.0294999:0.030751:0.471854:0.04416:51874:rs61733845
1   1120431 rs1320571   G   A   .   PASS    AF=0.04653  ES:SE:LP:AF:SS:ID   -0.0229954:0.0301098:0.351606:0.04653:51874:rs1320571
1   1135242 rs9729550   A   C   .   PASS    AF=0.2587   ES:SE:LP:AF:SS:ID   0.0524943:0.0141053:3.7034:0.2587:51874:rs9729550
1   1140435 rs1815606   G   T   .   PASS    AF=0.3179   ES:SE:LP:AF:SS:ID   0.0432499:0.0136608:2.81089:0.3179:51874:rs1815606
1   1163804 rs7515488   C   T   .   PASS    AF=0.1486   ES:SE:LP:AF:SS:ID   0.0840669:0.0167779:6.26544:0.1486:51874:rs7515488
1   1165310 rs11260562  G   A   .   PASS    AF=0.0556   ES:SE:LP:AF:SS:ID   0.0821914:0.025305:2.93477:0.0556:51874:rs11260562
1   1173611 rs6697886   G   A   .   PASS    AF=0.1373   ES:SE:LP:AF:SS:ID   0.0872903:0.0174247:6.26323:0.1373:51874:rs6697886
1   1186502 rs6603785   A   T   .   PASS    AF=0.1195   ES:SE:LP:AF:SS:ID   0.0839047:0.0185783:5.20111:0.1195:51874:rs6603785
1   1194804 rs11804831  T   C   .   PASS    AF=0.1856   ES:SE:LP:AF:SS:ID   0.0644855:0.0156228:4.43594:0.1856:51874:rs11804831
1   1218086 rs6603788   C   T   .   PASS    AF=0.07697  ES:SE:LP:AF:SS:ID   0.0278539:0.0227151:0.657354:0.07697:51874:rs6603788
1   1227897 rs3737721   A   G   .   PASS    AF=0.002436 ES:SE:LP:AF:SS:ID   0.108621:0.0906502:0.63672:0.002436:51874:rs3737721
1   1231656 rs1749951   G   A   .   PASS    AF=0.04028  ES:SE:LP:AF:SS:ID   0.0289805:0.031906:0.439237:0.04028:51874:rs1749951
1   1233941 rs1739855   T   C   .   PASS    AF=0.07333  ES:SE:LP:AF:SS:ID   0.046083:0.0229599:1.34932:0.07333:51874:rs1739855
1   1241529 rs1536168   A   G   .   PASS    AF=0.95394  ES:SE:LP:AF:SS:ID   -0.0388531:0.0294021:0.729658:0.95394:51874:rs1536168
1   1242468 rs2274264   G   A   .   PASS    AF=0.002467 ES:SE:LP:AF:SS:ID   0.106205:0.09604:0.570579:0.002467:51874:rs2274264
1   1247494 rs12103 T   C   .   PASS    AF=0.8166   ES:SE:LP:AF:SS:ID   -0.0788611:0.0157611:6.24954:0.8166:51874:rs12103
1   1249187 rs12142199  G   A   .   PASS    AF=0.8026   ES:SE:LP:AF:SS:ID   -0.0646391:0.0154665:4.53399:0.8026:51874:rs12142199
1   1254255 rs62623580  G   A   .   PASS    AF=0.007606 ES:SE:LP:AF:SS:ID   0.0960413:0.067431:0.811459:0.007606:51874:rs62623580
1   1335790 rs1240708   A   G   .   PASS    AF=0.1737   ES:SE:LP:AF:SS:ID   0.0745538:0.0160139:5.49069:0.1737:51874:rs1240708
1   1493727 rs880051    G   A   .   PASS    AF=0.232    ES:SE:LP:AF:SS:ID   0.0593995:0.0141283:4.58189:0.232:51874:rs880051
1   1497824 rs2296716   C   T   .   PASS    AF=0.1208   ES:SE:LP:AF:SS:ID   0.0381788:0.0184257:1.41723:0.1208:51874:rs2296716
1   1611995 rs4074196   A   G   .   PASS    AF=0.4414   ES:SE:LP:AF:SS:ID   -0.000456669:0.0138093:0.0116109:0.4414:51874:rs4074196
1   1706160 rs7531583   A   G   .   PASS    AF=0.77 ES:SE:LP:AF:SS:ID   -0.0339188:0.0140192:1.80843:0.77:51874:rs7531583
1   1721479 rs2272908   C   T   .   PASS    AF=0.4974   ES:SE:LP:AF:SS:ID   -0.0401344:0.0120482:3.06306:0.4974:51874:rs2272908
1   1723031 rs9660180   G   A   .   PASS    AF=0.4974   ES:SE:LP:AF:SS:ID   -0.0418833:0.0120656:3.28571:0.4974:51874:rs9660180
1   1781220 rs6681938   T   C   .   PASS    AF=0.2996   ES:SE:LP:AF:SS:ID   -0.00356077:0.0132235:0.103629:0.2996:51874:rs6681938
1   1838516 rs2377037   C   A   .   PASS    AF=0.2747   ES:SE:LP:AF:SS:ID   0.0245855:0.0137239:1.13535:0.2747:51874:rs2377037
1   1840038 rs2474461   T   C   .   PASS    AF=0.95331  ES:SE:LP:AF:SS:ID   -0.0367077:0.0287288:0.696061:0.95331:51874:rs2474461
1   1853288 rs1884454   G   T   .   PASS    AF=0.2694   ES:SE:LP:AF:SS:ID   0.0229567:0.0137751:1.01951:0.2694:51874:rs1884454
1   1855319 rs2295362   C   T   .   PASS    AF=0.0452   ES:SE:LP:AF:SS:ID   0.0228883:0.0295255:0.358309:0.0452:51874:rs2295362
1   1871337 rs16824543  G   A   .   PASS    AF=0.04241  ES:SE:LP:AF:SS:ID   0.0115429:0.0306901:0.150683:0.04241:51874:rs16824543
1   1873625 rs12758705  G   A   .   PASS    AF=0.2651   ES:SE:LP:AF:SS:ID   0.022732:0.0139577:0.985514:0.2651:51874:rs12758705
1   1881070 rs4648596   G   A   .   PASS    AF=0.04073  ES:SE:LP:AF:SS:ID   0.0162246:0.0319478:0.21356:0.04073:51874:rs4648596
1   1888193 rs3820011   C   A   .   PASS    AF=0.2698   ES:SE:LP:AF:SS:ID   0.0285245:0.0141515:1.35816:0.2698:51874:rs3820011
1   2024064 rs2459994   C   T   .   PASS    AF=0.1824   ES:SE:LP:AF:SS:ID   0.0400149:0.0163225:1.84694:0.1824:51874:rs2459994
1   2146966 rs7512482   T   C   .   PASS    AF=0.1674   ES:SE:LP:AF:SS:ID   -0.0281917:0.0173789:0.979782:0.1674:51874:rs7512482
1   2202774 rs6673129   C   T   .   PASS    AF=0.1651   ES:SE:LP:AF:SS:ID   0.0053222:0.0174129:0.119259:0.1651:51874:rs6673129
1   2229478 rs12562937  C   T   .   PASS    AF=0.1998   ES:SE:LP:AF:SS:ID   0.00655724:0.0161572:0.164398:0.1998:51874:rs12562937
1   2283896 rs2840528   A   G   .   PASS    AF=0.4158   ES:SE:LP:AF:SS:ID   -0.00913153:0.0126387:0.327918:0.4158:51874:rs2840528
1   2290143 rs34587196  G   A   .   PASS    AF=0.01202  ES:SE:LP:AF:SS:ID   0.0411307:0.0561654:0.333504:0.01202:51874:rs34587196
1   2404256 rs2494626   C   T   .   PASS    AF=0.2884   ES:SE:LP:AF:SS:ID   -0.00666996:0.0146293:0.18813:0.2884:51874:rs2494626
1   2407781 rs78504402  C   T   .   PASS    AF=0.06862  ES:SE:LP:AF:SS:ID   0.0518998:0.0252018:1.40385:0.06862:51874:rs78504402
1   2408471 rs115996655 G   A   .   PASS    AF=0.007814 ES:SE:LP:AF:SS:ID   -0.0967139:0.0693296:0.78776:0.007814:51874:rs115996655
1   2408834 rs11588930  G   A   .   PASS    AF=0.101    ES:SE:LP:AF:SS:ID   -0.00162999:0.021933:0.0265218:0.101:51874:rs11588930
1   2409892 rs12727342  A   G   .   PASS    AF=0.6229   ES:SE:LP:AF:SS:ID   0.0123899:0.0132409:0.456662:0.6229:51874:rs12727342
1   2410789 rs11799501  C   T   .   PASS    AF=0.5834   ES:SE:LP:AF:SS:ID   0.0293994:0.0131663:1.59254:0.5834:51874:rs11799501
1   2412279 rs4648638   A   T   .   PASS    AF=0.388    ES:SE:LP:AF:SS:ID   -0.0181095:0.0132003:0.769308:0.388:51874:rs4648638
1   2412293 rs12731186  C   T   .   PASS    AF=0.1211   ES:SE:LP:AF:SS:ID   -0.0110222:0.0190713:0.249261:0.1211:51874:rs12731186
1   2413166 rs115810747 A   G   .   PASS    AF=0.04094  ES:SE:LP:AF:SS:ID   0.0419527:0.0335342:0.675884:0.04094:51874:rs115810747
1   2413464 rs114424485 G   C   .   PASS    AF=0.008958 ES:SE:LP:AF:SS:ID   -0.0653354:0.067433:0.47808:0.008958:51874:rs114424485