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-52/ieu-a-52.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-52/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 11:08:42 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-52/ieu-a-52.vcf.gz ...
Read summary statistics for 2214251 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, 1058281 SNPs remain.
After merging with regression SNP LD, 1058281 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1747 (0.0125)
Lambda GC: 1.0368
Mean Chi^2: 1.0825
Intercept: 0.8834 (0.0083)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Wed Feb  5 11:09:10 2020
Total time elapsed: 28.24s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9083,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 0,
    "n": 100384,
    "n_snps": 2214251,
    "n_clumped_hits": 20,
    "n_p_sig": 405,
    "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": 8685,
    "n_miss_AF_reference": 17436,
    "n_est": 98674.3461,
    "ratio_se_n": 0.9914,
    "mean_diff": -0,
    "ratio_diff": 1.864,
    "sd_y_est1": 1.4592,
    "sd_y_est2": 1.4467,
    "r2_sum1": 0.0118,
    "r2_sum2": 0.0056,
    "r2_sum3": 0.0057,
    "r2_sum4": 0.0103,
    "ldsc_nsnp_merge_refpanel_ld": 1058281,
    "ldsc_nsnp_merge_regression_ld": 1058281,
    "ldsc_observed_scale_h2_beta": 0.1747,
    "ldsc_observed_scale_h2_se": 0.0125,
    "ldsc_intercept_beta": 0.8834,
    "ldsc_intercept_se": 0.0083,
    "ldsc_lambda_gc": 1.0368,
    "ldsc_mean_chisq": 1.0825,
    "ldsc_ratio": -1.4133
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 42 0 2214251 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 8.518331e+00 5.627839e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.200000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.895998e+07 5.548620e+07 1.3034e+04 3.295025e+07 7.041318e+07 1.142107e+08 2.491747e+08 ▇▇▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.750000e-05 9.814800e-03 -9.6000e-02 -5.700000e-03 0.000000e+00 5.800000e-03 1.000000e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.073900e-03 3.560200e-03 4.7000e-03 6.800000e-03 7.700000e-03 1.000000e-02 4.900000e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.935585e-01 2.915440e-01 0.0000e+00 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.935787e-01 2.912827e-01 0.0000e+00 2.394069e-01 4.917677e-01 7.459807e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 8685 0.9960777 NA NA NA NA NA 3.710231e-01 2.655606e-01 8.3000e-03 1.417000e-01 3.083000e-01 5.667000e-01 9.917000e-01 ▇▆▃▃▂
numeric AF_reference 17436 0.9921256 NA NA NA NA NA 3.724409e-01 2.486544e-01 1.9970e-04 1.631390e-01 3.160940e-01 5.539140e-01 1.000000e+00 ▇▇▅▃▂
numeric N 0 1.0000000 NA NA NA NA NA 5.806952e+04 8.187220e+03 5.0000e+04 5.696200e+04 5.758500e+04 5.762100e+04 1.003840e+05 ▇▁▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 785050 rs2905062 G A -0.0150 0.0090 0.0929994 0.0955807 NA 0.626997 60461
1 1003629 rs4075116 C T 0.0018 0.0082 0.8300000 0.8262511 0.73730 0.720647 54170
1 1017170 rs3766193 C G -0.0020 0.0075 0.7899998 0.7897258 0.56670 0.575479 54766
1 1017197 rs3766192 C T -0.0007 0.0072 0.9199999 0.9225499 0.57630 0.511182 55052
1 1018562 rs9442371 C T -0.0016 0.0071 0.8200001 0.8217054 0.59170 0.530152 55081
1 1018704 rs9442372 A G -0.0014 0.0071 0.8400000 0.8436843 0.60170 0.611022 55076
1 1021415 rs3737728 A G 0.0015 0.0078 0.8499999 0.8475012 0.71670 0.812700 55353
1 1021695 rs9442398 A G -0.0002 0.0081 0.9800000 0.9803011 0.72500 0.727236 55211
1 1022037 rs6701114 C T -0.0052 0.0080 0.5199996 0.5156922 0.56670 0.586661 50155
1 1097335 rs9442385 T G -0.0019 0.0130 0.8900000 0.8837999 0.94167 0.834665 53942
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51151350 rs6009951 C T 0.0063 0.0071 0.3700002 0.3749045 0.4000 0.5559110 57629
22 51151724 rs6010061 C T 0.0084 0.0072 0.2399999 0.2433450 0.3833 0.6098240 57453
22 51158017 rs6010065 G C 0.0022 0.0068 0.7499995 0.7462943 0.4417 0.5475240 55101
22 51163138 rs715586 C T -0.0007 0.0074 0.9199999 0.9246368 0.1500 0.0902556 92526
22 51165664 rs8137951 G A 0.0060 0.0053 0.2599998 0.2576027 0.2750 0.4063500 98101
22 51178090 rs2285395 G A -0.0021 0.0100 0.8400000 0.8336677 0.0667 0.0666933 92634
23 35921591 rs2204667 C G -0.0140 0.0088 0.1100001 0.1116300 0.1667 NA 57597
23 51666786 rs14115 A G 0.0032 0.0140 0.8200001 0.8192020 0.0250 NA 52169
23 70163799 rs1626496 A C -0.0009 0.0130 0.9400001 0.9448059 0.0750 NA 57601
23 118495837 rs12882977 G A -0.0062 0.0064 0.3300000 0.3326699 0.5167 0.2307280 57618

bcf preview

1   785050  rs2905062   G   A   .   PASS    .   ES:SE:LP:SS:ID  -0.015:0.009:1.03152:60461:rs2905062
1   1003629 rs4075116   C   T   .   PASS    AF=0.7373   ES:SE:LP:AF:SS:ID   0.0018:0.0082:0.0809219:0.7373:54170:rs4075116
1   1017170 rs3766193   C   G   .   PASS    AF=0.5667   ES:SE:LP:AF:SS:ID   -0.002:0.0075:0.102373:0.5667:54766:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.5763   ES:SE:LP:AF:SS:ID   -0.0007:0.0072:0.0362122:0.5763:55052:rs3766192
1   1018562 rs9442371   C   T   .   PASS    AF=0.5917   ES:SE:LP:AF:SS:ID   -0.0016:0.0071:0.0861861:0.5917:55081:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.6017   ES:SE:LP:AF:SS:ID   -0.0014:0.0071:0.0757207:0.6017:55076:rs9442372
1   1021415 rs3737728   A   G   .   PASS    AF=0.7167   ES:SE:LP:AF:SS:ID   0.0015:0.0078:0.0705811:0.7167:55353:rs3737728
1   1021695 rs9442398   A   G   .   PASS    AF=0.725    ES:SE:LP:AF:SS:ID   -0.0002:0.0081:0.00877392:0.725:55211:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.5667   ES:SE:LP:AF:SS:ID   -0.0052:0.008:0.283997:0.5667:50155:rs6701114
1   1097335 rs9442385   T   G   .   PASS    AF=0.94167  ES:SE:LP:AF:SS:ID   -0.0019:0.013:0.05061:0.94167:53942:rs9442385
1   1099342 rs9660710   A   C   .   PASS    AF=0.94068  ES:SE:LP:AF:SS:ID   -0.0005:0.013:0.0132283:0.94068:54765:rs9660710
1   1100217 rs1891905   C   T   .   PASS    AF=0.95833  ES:SE:LP:AF:SS:ID   -0.0037:0.018:0.0809219:0.95833:54003:rs1891905
1   1124663 rs6684820   G   A   .   PASS    AF=0.2667   ES:SE:LP:AF:SS:ID   -0.011:0.0083:0.744727:0.2667:54518:rs6684820
1   1125553 rs10907174  A   T   .   PASS    AF=0.225    ES:SE:LP:AF:SS:ID   -0.0079:0.0087:0.443698:0.225:55855:rs10907174
1   1130727 rs10907175  A   C   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   -0.0074:0.012:0.267606:0.1:56099:rs10907175
1   1135242 rs9729550   A   C   .   PASS    AF=0.275    ES:SE:LP:AF:SS:ID   -0.01:0.0081:0.69897:0.275:54478:rs9729550
1   1138913 rs3819001   T   C   .   PASS    AF=0.0431   ES:SE:LP:AF:SS:ID   -0.02:0.018:0.568636:0.0431:52579:rs3819001
1   1140435 rs1815606   G   T   .   PASS    AF=0.3103   ES:SE:LP:AF:SS:ID   -0.0082:0.0062:0.744727:0.3103:76828:rs1815606
1   1143657 rs3753348   C   G   .   PASS    AF=0.03333  ES:SE:LP:AF:SS:ID   -0.023:0.02:0.619789:0.03333:53189:rs3753348
1   1152631 rs11721 C   A   .   PASS    AF=0.08333  ES:SE:LP:AF:SS:ID   -0.023:0.013:1.16749:0.08333:53180:rs11721
1   1158277 rs3813199   G   A   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   -0.0076:0.011:0.29243:0.1:56975:rs3813199
1   1162435 rs3766186   C   A   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   -0.0078:0.012:0.30103:0.1:56964:rs3766186
1   1163804 rs7515488   C   T   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.021:0.01:1.42022:0.15:56927:rs7515488
1   1165310 rs11260562  G   A   .   PASS    AF=0.05172  ES:SE:LP:AF:SS:ID   -0.033:0.016:1.36653:0.05172:51893:rs11260562
1   1176597 rs6675798   T   C   .   PASS    AF=0.1083   ES:SE:LP:AF:SS:ID   -0.028:0.013:1.56864:0.1083:52589:rs6675798
1   1181751 rs6603783   T   C   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   -0.026:0.013:1.39794:0.1:52569:rs6603783
1   1192515 rs7524470   A   G   .   PASS    AF=0.05833  ES:SE:LP:AF:SS:ID   -0.0072:0.019:0.154902:0.05833:52134:rs7524470
1   1194804 rs11804831  T   C   .   PASS    AF=0.2083   ES:SE:LP:AF:SS:ID   -0.028:0.0093:2.63827:0.2083:55264:rs11804831
1   1198618 rs12563338  T   A   .   PASS    AF=0.04167  ES:SE:LP:AF:SS:ID   -0.03:0.019:0.958607:0.04167:56308:rs12563338
1   1206343 rs6667923   C   A   .   PASS    AF=0.05833  ES:SE:LP:AF:SS:ID   -0.012:0.018:0.29243:0.05833:56683:rs6667923
1   1206619 rs6668223   C   A   .   PASS    AF=0.0339   ES:SE:LP:AF:SS:ID   -0.018:0.021:0.39794:0.0339:54836:rs6668223
1   1211292 rs6685064   C   T   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   -0.014:0.013:0.568636:0.1:55074:rs6685064
1   1474304 rs1571150   C   A   .   PASS    AF=0.3  ES:SE:LP:AF:SS:ID   0.0011:0.007:0.0555173:0.3:57604:rs1571150
1   1478153 rs3766180   T   C   .   PASS    AF=0.2417   ES:SE:LP:AF:SS:ID   0.0021:0.0072:0.113509:0.2417:57503:rs3766180
1   1478180 rs3766178   T   C   .   PASS    AF=0.2667   ES:SE:LP:AF:SS:ID   0.0018:0.0072:0.09691:0.2667:57580:rs3766178
1   1481348 rs3766177   T   C   .   PASS    .   ES:SE:LP:SS:ID  0.0043:0.0078:0.236572:57408:rs3766177
1   1483010 rs7517401   G   A   .   PASS    AF=0.2833   ES:SE:LP:AF:SS:ID   0.0004:0.0072:0.0177288:0.2833:57205:rs7517401
1   1486834 rs3128342   C   A   .   PASS    AF=0.3333   ES:SE:LP:AF:SS:ID   0.0001:0.0074:0.00436481:0.3333:52786:rs3128342
1   1489670 rs7531530   C   T   .   PASS    AF=0.25 ES:SE:LP:AF:SS:ID   0.005:0.0075:0.29243:0.25:57616:rs7531530
1   1489928 rs7366884   T   C   .   PASS    AF=0.25 ES:SE:LP:AF:SS:ID   0.005:0.0077:0.283997:0.25:57612:rs7366884
1   1497201 rs3766169   A   C   .   PASS    AF=0.2458   ES:SE:LP:AF:SS:ID   0.0017:0.0072:0.091515:0.2458:57613:rs3766169
1   1499298 rs9439468   A   G   .   PASS    AF=0.3103   ES:SE:LP:AF:SS:ID   0.0009:0.0068:0.05061:0.3103:57629:rs9439468
1   1500941 rs6603791   A   G   .   PASS    AF=0.3  ES:SE:LP:AF:SS:ID   0.001:0.0068:0.0555173:0.3:57616:rs6603791
1   1501064 rs6656541   T   G   .   PASS    AF=0.3  ES:SE:LP:AF:SS:ID   0.0005:0.0069:0.0268721:0.3:57622:rs6656541
1   1505255 rs6603793   C   T   .   PASS    AF=0.3  ES:SE:LP:AF:SS:ID   0.0007:0.0069:0.0362122:0.3:57611:rs6603793
1   1509034 rs7520996   T   C   .   PASS    AF=0.2797   ES:SE:LP:AF:SS:ID   -0.0033:0.0071:0.19382:0.2797:57292:rs7520996
1   1510801 rs7519837   C   T   .   PASS    AF=0.2917   ES:SE:LP:AF:SS:ID   -0.0042:0.0071:0.259637:0.2917:57211:rs7519837
1   1706136 rs6603811   T   C   .   PASS    AF=0.97458  ES:SE:LP:AF:SS:ID   -0.01:0.01:0.481486:0.97458:85551:rs6603811
1   1706160 rs7531583   A   G   .   PASS    AF=0.7833   ES:SE:LP:AF:SS:ID   -0.0042:0.0057:0.337242:0.7833:97676:rs7531583
1   1708801 rs12044597  A   G   .   PASS    AF=0.5169   ES:SE:LP:AF:SS:ID   0.0089:0.0049:1.17393:0.5169:98150:rs12044597