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-301/ieu-a-301.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-301/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 11:30:48 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-301/ieu-a-301.vcf.gz ...
Read summary statistics for 2423570 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, 1132773 SNPs remain.
After merging with regression SNP LD, 1132773 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2216 (0.0278)
Lambda GC: 1.113
Mean Chi^2: 1.3334
Intercept: 0.9554 (0.009)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Wed Feb  5 11:31:11 2020
Total time elapsed: 23.17s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9292,
    "inflation_factor": 1.0136,
    "mean_EFFECT": 0.0001,
    "n": 187365,
    "n_snps": 2423570,
    "n_clumped_hits": 88,
    "n_p_sig": 4093,
    "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": 367197,
    "n_miss_AF_reference": 19261,
    "n_est": 185012.8371,
    "ratio_se_n": 0.9937,
    "mean_diff": -0,
    "ratio_diff": 30.6345,
    "sd_y_est1": 1.5881,
    "sd_y_est2": 1.5781,
    "r2_sum1": 0.0895,
    "r2_sum2": 0.0355,
    "r2_sum3": 0.036,
    "r2_sum4": 0.0633,
    "ldsc_nsnp_merge_refpanel_ld": 1132773,
    "ldsc_nsnp_merge_regression_ld": 1132773,
    "ldsc_observed_scale_h2_beta": 0.2216,
    "ldsc_observed_scale_h2_se": 0.0278,
    "ldsc_intercept_beta": 0.9554,
    "ldsc_intercept_se": 0.009,
    "ldsc_lambda_gc": 1.113,
    "ldsc_mean_chisq": 1.3334,
    "ldsc_ratio": -0.1338
}
 

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 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 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 34 0 2423570 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 8.583781e+00 5.647818e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.200000e+01 2.20000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.873574e+07 5.563751e+07 1.1523e+04 3.252951e+07 7.008373e+07 1.141082e+08 2.49219e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 7.820000e-05 1.001240e-02 -3.7360e-01 -5.000000e-03 0.000000e+00 5.000000e-03 1.97200e-01 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.080800e-03 4.602800e-03 3.5000e-03 5.400000e-03 6.300000e-03 8.700000e-03 9.00000e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.958849e-01 2.918758e-01 0.0000e+00 2.427001e-01 4.971003e-01 7.485003e-01 1.00000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.815531e-01 2.954443e-01 0.0000e+00 2.209002e-01 4.767506e-01 7.388827e-01 1.00000e+00 ▇▇▇▆▆
numeric AF 367197 0.8484892 NA NA NA NA NA 3.564396e-01 2.699176e-01 1.3190e-03 1.240000e-01 2.902000e-01 5.515000e-01 9.98681e-01 ▇▅▃▂▂
numeric AF_reference 19261 0.9920526 NA NA NA NA NA 3.594982e-01 2.553555e-01 0.0000e+00 1.451680e-01 2.969250e-01 5.427320e-01 1.00000e+00 ▇▆▃▃▂
numeric N 0 1.0000000 NA NA NA NA NA 9.537662e+04 1.777510e+04 5.0001e+04 9.263600e+04 9.457800e+04 9.459500e+04 1.87365e+05 ▁▇▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 721290 rs12565286 G C -0.0108 0.0185 0.3204004 0.5593658 0.04354 0.0371406 61221.1
1 752566 rs3094315 G A 0.0092 0.0095 0.6160004 0.3328341 0.83640 0.7182510 57396.0
1 775659 rs2905035 A G 0.0180 0.0110 0.4657995 0.1017635 NA 0.7450080 56773.0
1 777122 rs2980319 A T 0.0190 0.0111 0.4484004 0.0869498 NA 0.7472040 56773.0
1 779322 rs4040617 A G -0.0168 0.0113 0.5549004 0.1370873 0.12930 0.2264380 55028.0
1 785050 rs2905062 G A 0.0157 0.0073 0.0712804 0.0315011 0.86680 0.6269970 99429.2
1 785989 rs2980300 T C 0.0198 0.0110 0.3636997 0.0718606 0.84960 0.6269970 56589.0
1 990380 rs3121561 C T 0.0151 0.0104 0.1753000 0.1465230 0.29550 0.3434500 64828.0
1 998501 rs3813193 G C 0.0222 0.0111 0.0387802 0.0455003 NA 0.2066690 56268.0
1 1003629 rs4075116 C T -0.0052 0.0075 0.5336998 0.4881004 0.73610 0.7206470 80989.0
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51151724 rs6010061 C T 0.0092 0.0062 0.1319001 0.1378432 0.42080 0.6098240 93064
22 51156933 rs6010063 A G 0.0016 0.0053 0.9780000 0.7627384 0.40770 0.4960060 90645
22 51158017 rs6010065 G C 0.0028 0.0053 0.8384001 0.5972898 NA 0.5475240 92343
22 51163138 rs715586 C T -0.0135 0.0053 0.0065440 0.0108601 0.12140 0.0902556 181785
22 51165664 rs8137951 G A 0.0103 0.0039 0.0153699 0.0082655 0.28100 0.4063500 184307
22 51171693 rs756638 G A 0.0041 0.0067 0.3037001 0.5405773 0.25990 0.3049120 83810
22 51175626 rs3810648 A G -0.0040 0.0108 0.7878998 0.7111065 0.05277 0.1084270 90620
22 51178090 rs2285395 G A 0.0035 0.0078 0.5856997 0.6536351 0.05145 0.0666933 177491
22 51196164 rs8136603 A T -0.0099 0.0132 0.5024004 0.4532547 NA 0.1427720 92343
22 51212875 rs2238837 A C 0.0139 0.0082 0.0928795 0.0900523 0.22690 0.3724040 74708

bcf preview

1   721290  rs12565286  G   C   .   PASS    AF=0.04354  ES:SE:LP:AF:SS:ID   -0.0108:0.0185:0.494307:0.04354:61221.1:rs12565286
1   752566  rs3094315   G   A   .   PASS    AF=0.8364   ES:SE:LP:AF:SS:ID   0.0092:0.0095:0.210419:0.8364:57396:rs3094315
1   775659  rs2905035   A   G   .   PASS    .   ES:SE:LP:SS:ID  0.018:0.011:0.331801:56773:rs2905035
1   777122  rs2980319   A   T   .   PASS    .   ES:SE:LP:SS:ID  0.019:0.0111:0.348334:56773:rs2980319
1   779322  rs4040617   A   G   .   PASS    AF=0.1293   ES:SE:LP:AF:SS:ID   -0.0168:0.0113:0.255785:0.1293:55028:rs4040617
1   785050  rs2905062   G   A   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   0.0157:0.0073:1.14703:0.8668:99429.2:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.8496   ES:SE:LP:AF:SS:ID   0.0198:0.011:0.439257:0.8496:56589:rs2980300
1   990380  rs3121561   C   T   .   PASS    AF=0.2955   ES:SE:LP:AF:SS:ID   0.0151:0.0104:0.756218:0.2955:64828:rs3121561
1   998501  rs3813193   G   C   .   PASS    .   ES:SE:LP:SS:ID  0.0222:0.0111:1.41139:56268:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.7361   ES:SE:LP:AF:SS:ID   -0.0052:0.0075:0.272703:0.7361:80989:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.1596   ES:SE:LP:AF:SS:ID   0.0168:0.0099:1.15945:0.1596:56268:rs3934834
1   1017170 rs3766193   C   G   .   PASS    .   ES:SE:LP:SS:ID  -0.0041:0.0068:0.296881:90450:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.5488   ES:SE:LP:AF:SS:ID   -0.0075:0.0065:0.598599:0.5488:90450:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.1504   ES:SE:LP:AF:SS:ID   0.024:0.0111:1.59125:0.1504:56268:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.562    ES:SE:LP:AF:SS:ID   -0.0038:0.0064:0.307594:0.562:90450:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.562    ES:SE:LP:AF:SS:ID   -0.0054:0.0063:0.459671:0.562:90422:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.1636   ES:SE:LP:AF:SS:ID   0.0218:0.0117:1.26177:0.1636:56268:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.7203   ES:SE:LP:AF:SS:ID   -0.0013:0.0065:0.040148:0.7203:89347:rs3737728
1   1021583 rs10907178  A   C   .   PASS    AF=0.157    ES:SE:LP:AF:SS:ID   0.0186:0.0113:1.11436:0.157:56268:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.7203   ES:SE:LP:AF:SS:ID   -0.0002:0.007:0.00418937:0.7203:90450:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.5633   ES:SE:LP:AF:SS:ID   -0.0089:0.0068:0.436519:0.5633:89572:rs6701114
1   1026707 rs4074137   C   A   .   PASS    AF=0.5976   ES:SE:LP:AF:SS:ID   0.0003:0.0072:0.0694075:0.5976:59389:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.1478   ES:SE:LP:AF:SS:ID   0.012:0.0088:0.782779:0.1478:59389:rs6687776
1   1031540 rs9651273   A   G   .   PASS    AF=0.719    ES:SE:LP:AF:SS:ID   0:0.0071:0.012915:0.719:59389:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.08971  ES:SE:LP:AF:SS:ID   -0.0013:0.0105:0.124013:0.08971:74360:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.1174   ES:SE:LP:AF:SS:ID   0.003:0.0099:0.109859:0.1174:66521:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.1174   ES:SE:LP:AF:SS:ID   0.0055:0.0095:0.341512:0.1174:74360:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.08443  ES:SE:LP:AF:SS:ID   -0.0004:0.0103:0.117646:0.08443:76753:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.1174   ES:SE:LP:AF:SS:ID   0.005:0.009:0.37789:0.1174:74360:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.08839  ES:SE:LP:AF:SS:ID   -0.0023:0.0106:0.088576:0.08839:74360:rs4970409
1   1060235 rs7540009   G   A   .   PASS    AF=0.0277   ES:SE:LP:AF:SS:ID   0.0212:0.0222:0.257511:0.0277:53118:rs7540009
1   1060608 rs17160824  G   A   .   PASS    AF=0.08707  ES:SE:LP:AF:SS:ID   -0.0014:0.0105:0.124765:0.08707:74360:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.08575  ES:SE:LP:AF:SS:ID   -0.0001:0.0106:0.154282:0.08575:74360:rs17160826
1   1061152 rs12748370  T   C   .   PASS    AF=0.08575  ES:SE:LP:AF:SS:ID   -0.0006:0.0105:0.11702:0.08575:74360:rs12748370
1   1061166 rs11807848  T   C   .   PASS    AF=0.3918   ES:SE:LP:AF:SS:ID   -0.0004:0.0076:0.109523:0.3918:59389:rs11807848
1   1062015 rs9659914   C   T   .   PASS    AF=0.0277   ES:SE:LP:AF:SS:ID   0.0236:0.0242:0.28929:0.0277:53118:rs9659914
1   1062638 rs9442373   C   A   .   PASS    AF=0.5607   ES:SE:LP:AF:SS:ID   0.0004:0.0076:0.08019:0.5607:59389:rs9442373
1   1064535 rs6682475   G   C   .   PASS    .   ES:SE:LP:SS:ID  -0.0058:0.0101:0.32892:59389:rs6682475
1   1064979 rs2298217   C   T   .   PASS    AF=0.1161   ES:SE:LP:AF:SS:ID   0.0006:0.0097:0.0800333:0.1161:59389:rs2298217
1   1066029 rs12145826  G   A   .   PASS    AF=0.06596  ES:SE:LP:AF:SS:ID   0.0252:0.0188:0.727694:0.06596:50216:rs12145826
1   1066403 rs10907182  T   C   .   PASS    AF=0.5897   ES:SE:LP:AF:SS:ID   0.0015:0.0086:0.00651968:0.5897:59389:rs10907182
1   1071118 rs10907183  G   C   .   PASS    .   ES:SE:LP:SS:ID  0.007:0.009:0.23463:59389:rs10907183
1   1077064 rs4970357   C   A   .   PASS    AF=0.91161  ES:SE:LP:AF:SS:ID   0.0111:0.0115:0.473273:0.91161:78335:rs4970357
1   1087683 rs9442380   T   C   .   PASS    AF=0.93404  ES:SE:LP:AF:SS:ID   0.0168:0.0108:0.924453:0.93404:88001:rs9442380
1   1089262 rs4970358   A   G   .   PASS    AF=0.96702  ES:SE:LP:AF:SS:ID   0.0131:0.0151:0.403623:0.96702:85253:rs4970358
1   1094738 rs4970362   A   G   .   PASS    AF=0.6293   ES:SE:LP:AF:SS:ID   0.0072:0.0097:0.427826:0.6293:55176:rs4970362
1   1097335 rs9442385   T   G   .   PASS    AF=0.93668  ES:SE:LP:AF:SS:ID   0.0145:0.0106:0.719194:0.93668:86320:rs9442385
1   1099342 rs9660710   A   C   .   PASS    AF=0.93668  ES:SE:LP:AF:SS:ID   0.0142:0.0103:0.775985:0.93668:88711:rs9660710
1   1100217 rs1891905   C   T   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   0.0192:0.0165:0.636388:0.94987:85253:rs1891905
1   1106473 rs4970420   G   A   .   PASS    AF=0.19 ES:SE:LP:AF:SS:ID   0.0005:0.0102:0.107349:0.19:59389:rs4970420