Summary
Summary {data-width=650}
Manhattan plot
manhattan_plot
QQ plot
qq_plot
AF plot
af_plot
P-Z plot
pz_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: 23.17sQC 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 betweenAFandAF_reference.inflation_factor(lambda): Genomic inflation factor.mean_EFFECT: Mean ofEFFECTsize.n: Maximum value of reported sample size across all SNPs, \(n\).n_clumped_hits: Number of clumped hits.n_snps: Number of SNPsn_p_sig: Number of SNPs with pvalue below5e-8.n_mono: Number of monomorphic (MAF == 1orMAF == 0) SNPs.n_ns: Number of SNPs with nonsense values:- alleles other than
A, C, G or T. - P-values
< 0or> 1. - negative or infinite standard errors (
<= 0or= Infinity). - infinite beta estimates or allele frequencies
< 0or> 1.
- alleles other than
n_mac: Number of cases whereMAC(\(2 \times N \times MAF\)) is less than6.is_snpid_unique:trueif the combination ofIDREFALTis unique and therefore no duplication in snpid.n_miss_<*>: Number ofNAobservations 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 expectratio_se_nto 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 ofdiffand the mean ofdiff2(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<*>:r2statistics under various assumptions1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).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: NOTis_snpid_unique.mean_EFFECT_nonfinite:mean(EFFECT)isNA,NaN, orInf.mean_EFFECT_05:abs(mean(EFFECT))> 0.5.mean_EFFECT_01:abs(mean(EFFECT))> 0.1.mean_chisq:ldsc_mean_chisq> 1.3 orldsc_mean_chisq< 0.7.n_p_sig:n_p_sig> 1000.miss_<*>:n_miss_<*>/n_snps> 0.01.ldsc_ratio:ldsc_ratio> 0.5ldsc_intercept_beta:ldsc_intercept_beta> 1.5n_clumped_hits:n_clumped_hits> 1000r2_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