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-302/ieu-a-302.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-302/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 10:58:17 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-302/ieu-a-302.vcf.gz ...
Read summary statistics for 2415963 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, 1130660 SNPs remain.
After merging with regression SNP LD, 1130660 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2219 (0.0382)
Lambda GC: 1.1216
Mean Chi^2: 1.3411
Intercept: 0.9609 (0.0075)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Wed Feb 5 10:58:48 2020
Total time elapsed: 30.84sQC metrics
Metrics
Metrics
{
"af_correlation": 0.929,
"inflation_factor": 1.0075,
"mean_EFFECT": -0,
"n": 177861,
"n_snps": 2415963,
"n_clumped_hits": 55,
"n_p_sig": 3198,
"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": 365698,
"n_miss_AF_reference": 19092,
"n_est": 174323.6947,
"ratio_se_n": 0.99,
"mean_diff": 1.378e-06,
"ratio_diff": 0.328,
"sd_y_est1": 1.4245,
"sd_y_est2": 1.4103,
"r2_sum1": 0.0554,
"r2_sum2": 0.0273,
"r2_sum3": 0.0279,
"r2_sum4": 0.0523,
"ldsc_nsnp_merge_refpanel_ld": 1130660,
"ldsc_nsnp_merge_regression_ld": 1130660,
"ldsc_observed_scale_h2_beta": 0.2219,
"ldsc_observed_scale_h2_se": 0.0382,
"ldsc_intercept_beta": 0.9609,
"ldsc_intercept_se": 0.0075,
"ldsc_lambda_gc": 1.1216,
"ldsc_mean_chisq": 1.3411,
"ldsc_ratio": -0.1146
}
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 | 2415963 | 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 | 8.581066e+00 | 5.646134e+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 | 7.874427e+07 | 5.563148e+07 | 1.1523e+04 | 3.254224e+07 | 7.009782e+07 | 1.141179e+08 | 2.49219e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -1.800000e-05 | 9.259800e-03 | -2.4740e-01 | -4.600000e-03 | 0.000000e+00 | 4.600000e-03 | 2.22900e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.387700e-03 | 4.147300e-03 | 3.3000e-03 | 4.900000e-03 | 5.800000e-03 | 8.000000e-03 | 7.52000e-02 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.975589e-01 | 2.906437e-01 | 0.0000e+00 | 2.464002e-01 | 4.984000e-01 | 7.491004e-01 | 1.00000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.799232e-01 | 2.948543e-01 | 0.0000e+00 | 2.197201e-01 | 4.750505e-01 | 7.346225e-01 | 1.00000e+00 | ▇▇▇▆▆ |
| numeric | AF | 365698 | 0.8486326 | NA | NA | NA | NA | NA | 3.569399e-01 | 2.696041e-01 | 1.3190e-03 | 1.240000e-01 | 2.916000e-01 | 5.528000e-01 | 9.98681e-01 | ▇▅▃▂▂ |
| numeric | AF_reference | 19092 | 0.9920976 | NA | NA | NA | NA | NA | 3.599584e-01 | 2.550943e-01 | 0.0000e+00 | 1.459660e-01 | 2.975240e-01 | 5.431310e-01 | 1.00000e+00 | ▇▆▃▃▂ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.162125e+04 | 1.666812e+04 | 5.0002e+04 | 8.876400e+04 | 9.099600e+04 | 9.101300e+04 | 1.77861e+05 | ▁▇▁▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 721290 | rs12565286 | G | C | -0.0106 | 0.0169 | 0.2788001 | 0.5305157 | 0.04354 | 0.0371406 | 57442.4 |
| 1 | 752566 | rs3094315 | G | A | 0.0193 | 0.0094 | 0.0343202 | 0.0400540 | 0.83640 | 0.7182510 | 53814.0 |
| 1 | 785050 | rs2905062 | G | A | 0.0148 | 0.0068 | 0.0094291 | 0.0295201 | 0.86680 | 0.6269970 | 93089.0 |
| 1 | 998501 | rs3813193 | G | C | -0.0007 | 0.0098 | 0.9817000 | 0.9430567 | NA | 0.2066690 | 52680.0 |
| 1 | 1003629 | rs4075116 | C | T | 0.0003 | 0.0068 | 0.8990000 | 0.9648106 | 0.73610 | 0.7206470 | 77405.0 |
| 1 | 1005806 | rs3934834 | C | T | 0.0036 | 0.0090 | 0.7043994 | 0.6891565 | 0.15960 | 0.2234420 | 52680.0 |
| 1 | 1017170 | rs3766193 | C | G | 0.0053 | 0.0063 | 0.3514002 | 0.4001968 | NA | 0.5754790 | 86868.0 |
| 1 | 1017197 | rs3766192 | C | T | 0.0011 | 0.0060 | 0.7292996 | 0.8545365 | 0.54880 | 0.5111820 | 86868.0 |
| 1 | 1017587 | rs3766191 | C | T | 0.0030 | 0.0100 | 0.7822003 | 0.7641772 | 0.15040 | 0.1711260 | 52680.0 |
| 1 | 1018562 | rs9442371 | C | T | 0.0017 | 0.0059 | 0.6669004 | 0.7732429 | 0.56200 | 0.5301520 | 86868.0 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51151724 | rs6010061 | C | T | 0.0068 | 0.0056 | 0.4724001 | 0.2246386 | 0.42080 | 0.6098240 | 89482 |
| 22 | 51156933 | rs6010063 | A | G | -0.0052 | 0.0049 | 0.5855999 | 0.2885879 | 0.40770 | 0.4960060 | 87063 |
| 22 | 51158017 | rs6010065 | G | C | -0.0061 | 0.0049 | 0.4618001 | 0.2131693 | NA | 0.5475240 | 88761 |
| 22 | 51163138 | rs715586 | C | T | -0.0125 | 0.0050 | 0.0196300 | 0.0124193 | 0.12140 | 0.0902556 | 172784 |
| 22 | 51165664 | rs8137951 | G | A | 0.0009 | 0.0037 | 0.7589008 | 0.8078170 | 0.28100 | 0.4063500 | 174882 |
| 22 | 51171693 | rs756638 | G | A | -0.0011 | 0.0061 | 0.9860000 | 0.8568952 | 0.25990 | 0.3049120 | 80228 |
| 22 | 51175626 | rs3810648 | A | G | 0.0041 | 0.0100 | 0.5669999 | 0.6818059 | 0.05277 | 0.1084270 | 87038 |
| 22 | 51178090 | rs2285395 | G | A | 0.0056 | 0.0074 | 0.3663996 | 0.4491956 | 0.05145 | 0.0666933 | 169295 |
| 22 | 51196164 | rs8136603 | A | T | 0.0087 | 0.0126 | 0.3365999 | 0.4898948 | NA | 0.1427720 | 88761 |
| 22 | 51212875 | rs2238837 | A | C | 0.0047 | 0.0075 | 0.7949999 | 0.5308778 | 0.22690 | 0.3724040 | 71127 |
bcf preview
1 721290 rs12565286 G C . PASS AF=0.04354 ES:SE:LP:AF:SS:ID -0.0106:0.0169:0.554707:0.04354:57442.4:rs12565286
1 752566 rs3094315 G A . PASS AF=0.8364 ES:SE:LP:AF:SS:ID 0.0193:0.0094:1.46445:0.8364:53814:rs3094315
1 785050 rs2905062 G A . PASS AF=0.8668 ES:SE:LP:AF:SS:ID 0.0148:0.0068:2.02553:0.8668:93089:rs2905062
1 998501 rs3813193 G C . PASS . ES:SE:LP:SS:ID -0.0007:0.0098:0.00802121:52680:rs3813193
1 1003629 rs4075116 C T . PASS AF=0.7361 ES:SE:LP:AF:SS:ID 0.0003:0.0068:0.0462403:0.7361:77405:rs4075116
1 1005806 rs3934834 C T . PASS AF=0.1596 ES:SE:LP:AF:SS:ID 0.0036:0.009:0.152181:0.1596:52680:rs3934834
1 1017170 rs3766193 C G . PASS . ES:SE:LP:SS:ID 0.0053:0.0063:0.454198:86868:rs3766193
1 1017197 rs3766192 C T . PASS AF=0.5488 ES:SE:LP:AF:SS:ID 0.0011:0.006:0.137094:0.5488:86868:rs3766192
1 1017587 rs3766191 C T . PASS AF=0.1504 ES:SE:LP:AF:SS:ID 0.003:0.01:0.106682:0.1504:52680:rs3766191
1 1018562 rs9442371 C T . PASS AF=0.562 ES:SE:LP:AF:SS:ID 0.0017:0.0059:0.175939:0.562:86868:rs9442371
1 1018704 rs9442372 A G . PASS AF=0.562 ES:SE:LP:AF:SS:ID 0.0037:0.0058:0.372532:0.562:86841:rs9442372
1 1021346 rs10907177 A G . PASS AF=0.1636 ES:SE:LP:AF:SS:ID 0.0027:0.0105:0.107516:0.1636:52680:rs10907177
1 1021415 rs3737728 A G . PASS AF=0.7203 ES:SE:LP:AF:SS:ID 0.0027:0.0059:0.409604:0.7203:85760:rs3737728
1 1021583 rs10907178 A C . PASS AF=0.157 ES:SE:LP:AF:SS:ID 0.0032:0.0102:0.117874:0.157:52680:rs10907178
1 1021695 rs9442398 A G . PASS AF=0.7203 ES:SE:LP:AF:SS:ID 0.004:0.0063:0.435689:0.7203:86868:rs9442398
1 1022037 rs6701114 C T . PASS AF=0.5633 ES:SE:LP:AF:SS:ID 0.0036:0.0062:0.419988:0.5633:85990:rs6701114
1 1026707 rs4074137 C A . PASS AF=0.5976 ES:SE:LP:AF:SS:ID -0.0054:0.0064:0.351933:0.5976:55801:rs4074137
1 1030565 rs6687776 C T . PASS AF=0.1478 ES:SE:LP:AF:SS:ID 0.0027:0.0079:0.134363:0.1478:55801:rs6687776
1 1031540 rs9651273 A G . PASS AF=0.719 ES:SE:LP:AF:SS:ID -0.0017:0.0065:0.150519:0.719:55801:rs9651273
1 1036959 rs11579015 T C . PASS AF=0.08971 ES:SE:LP:AF:SS:ID 0.0052:0.0096:0.303818:0.08971:70774:rs11579015
1 1040026 rs6671356 T C . PASS AF=0.1174 ES:SE:LP:AF:SS:ID -0.0034:0.0088:0.0780016:0.1174:62933:rs6671356
1 1046164 rs6666280 C T . PASS AF=0.1174 ES:SE:LP:AF:SS:ID 0.0039:0.0085:0.34979:0.1174:70774:rs6666280
1 1048955 rs4970405 A G . PASS AF=0.08443 ES:SE:LP:AF:SS:ID 0.0046:0.0094:0.294821:0.08443:73172:rs4970405
1 1049950 rs12726255 A G . PASS AF=0.1174 ES:SE:LP:AF:SS:ID 0.0002:0.0081:0.14868:0.1174:70774:rs12726255
1 1053452 rs4970409 G A . PASS AF=0.08839 ES:SE:LP:AF:SS:ID 0.0079:0.0096:0.432033:0.08839:70774:rs4970409
1 1060608 rs17160824 G A . PASS AF=0.08707 ES:SE:LP:AF:SS:ID 0.0085:0.0096:0.492414:0.08707:70774:rs17160824
1 1061115 rs17160826 T C . PASS AF=0.08575 ES:SE:LP:AF:SS:ID 0.0052:0.0096:0.324222:0.08575:70774:rs17160826
1 1061152 rs12748370 T C . PASS AF=0.08575 ES:SE:LP:AF:SS:ID 0.0042:0.0096:0.261695:0.08575:70774:rs12748370
1 1061166 rs11807848 T C . PASS AF=0.3918 ES:SE:LP:AF:SS:ID 0.0055:0.007:0.320936:0.3918:55801:rs11807848
1 1062638 rs9442373 C A . PASS AF=0.5607 ES:SE:LP:AF:SS:ID -0.0005:0.007:0.0827571:0.5607:55801:rs9442373
1 1064535 rs6682475 G C . PASS . ES:SE:LP:SS:ID 0.0097:0.0091:0.375821:55801:rs6682475
1 1064979 rs2298217 C T . PASS AF=0.1161 ES:SE:LP:AF:SS:ID -0.0034:0.0086:0.0958798:0.1161:55801:rs2298217
1 1066403 rs10907182 T C . PASS AF=0.5897 ES:SE:LP:AF:SS:ID 0.0065:0.0077:0.192397:0.5897:55801:rs10907182
1 1071118 rs10907183 G C . PASS . ES:SE:LP:SS:ID 0.0098:0.0081:0.39599:55801:rs10907183
1 1077064 rs4970357 C A . PASS AF=0.91161 ES:SE:LP:AF:SS:ID 0.0108:0.011:0.306889:0.91161:74760:rs4970357
1 1087683 rs9442380 T C . PASS AF=0.93404 ES:SE:LP:AF:SS:ID 0.0072:0.0101:0.239427:0.93404:84414:rs9442380
1 1089262 rs4970358 A G . PASS AF=0.96702 ES:SE:LP:AF:SS:ID 0.0096:0.0141:0.227092:0.96702:78545:rs4970358
1 1094738 rs4970362 A G . PASS AF=0.6293 ES:SE:LP:AF:SS:ID 0.008:0.0078:0.268895:0.6293:51588:rs4970362
1 1097335 rs9442385 T G . PASS AF=0.93668 ES:SE:LP:AF:SS:ID 0.0084:0.01:0.297225:0.93668:79617:rs9442385
1 1099342 rs9660710 A C . PASS AF=0.93668 ES:SE:LP:AF:SS:ID 0.0041:0.0095:0.0950141:0.93668:85130:rs9660710
1 1100217 rs1891905 C T . PASS AF=0.94987 ES:SE:LP:AF:SS:ID 0.0122:0.0149:0.336393:0.94987:78545:rs1891905
1 1106473 rs4970420 G A . PASS AF=0.19 ES:SE:LP:AF:SS:ID 0.0087:0.0095:0.402195:0.19:55801:rs4970420
1 1119858 rs1320565 C T . PASS AF=0.08047 ES:SE:LP:AF:SS:ID -0.0131:0.0104:0.485187:0.08047:60295:rs1320565
1 1120431 rs1320571 G A . PASS AF=0.04749 ES:SE:LP:AF:SS:ID -0.015:0.0166:0.550985:0.04749:72029:rs1320571
1 1121794 rs11260549 G A . PASS AF=0.1346 ES:SE:LP:AF:SS:ID 0.0185:0.0084:0.763463:0.1346:66096:rs11260549
1 1124663 rs6684820 G A . PASS AF=0.2691 ES:SE:LP:AF:SS:ID 0.0096:0.0059:0.384892:0.2691:90292:rs6684820
1 1125553 rs10907174 A T . PASS . ES:SE:LP:SS:ID 0.0121:0.0064:0.349304:90292:rs10907174
1 1129672 rs11260554 G T . PASS AF=0.124 ES:SE:LP:AF:SS:ID 0.0195:0.0085:0.801343:0.124:66059:rs11260554
1 1130727 rs10907175 A C . PASS AF=0.08971 ES:SE:LP:AF:SS:ID 0.0028:0.0085:0.167044:0.08971:88408:rs10907175
1 1135242 rs9729550 A C . PASS AF=0.2665 ES:SE:LP:AF:SS:ID 0.0049:0.0058:0.0531549:0.2665:90292:rs9729550