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-783/ieu-a-783.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-783/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 11:36:44 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-783/ieu-a-783.vcf.gz ...
Read summary statistics for 119461 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, 53309 SNPs remain.
After merging with regression SNP LD, 53309 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: 1.0317 (0.2744)
Lambda GC: 1.3684
Mean Chi^2: 3.0595
Intercept: 1.1205 (0.0487)
Ratio: 0.0585 (0.0237)
Analysis finished at Wed Feb 5 11:36:54 2020
Total time elapsed: 9.8sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9365,
"inflation_factor": 1.2395,
"mean_EFFECT": -0.0001,
"n": 86851.5,
"n_snps": 119461,
"n_clumped_hits": 28,
"n_p_sig": 1784,
"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": 27,
"n_miss_AF_reference": 759,
"n_est": 84518.0092,
"ratio_se_n": 0.9865,
"mean_diff": 0,
"ratio_diff": 0.949,
"sd_y_est1": 0.9989,
"sd_y_est2": 0.9854,
"r2_sum1": 0.048,
"r2_sum2": 0.0481,
"r2_sum3": 0.0494,
"r2_sum4": 0.0486,
"ldsc_nsnp_merge_refpanel_ld": 53309,
"ldsc_nsnp_merge_regression_ld": 53309,
"ldsc_observed_scale_h2_beta": 1.0317,
"ldsc_observed_scale_h2_se": 0.2744,
"ldsc_intercept_beta": 1.1205,
"ldsc_intercept_se": 0.0487,
"ldsc_lambda_gc": 1.3684,
"ldsc_mean_chisq": 3.0595,
"ldsc_ratio": 0.0585
}
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 | 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 | 5 | 23 | 0 | 119461 | 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 | 8.655670e+00 | 5.544837e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.200000e+01 | 2.200000e+01 | ▇▆▆▃▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.375294e+07 | 5.531762e+07 | 4.04830e+04 | 2.795870e+07 | 6.161817e+07 | 1.108161e+08 | 2.491546e+08 | ▇▅▃▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -1.451000e-04 | 1.932410e-02 | -4.08600e-01 | -6.100000e-03 | 0.000000e+00 | 6.000000e-03 | 2.795000e-01 | ▁▁▇▃▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.012360e-02 | 1.062500e-02 | 4.60000e-03 | 5.200000e-03 | 6.500000e-03 | 1.050000e-02 | 2.382000e-01 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.602390e-01 | 3.047533e-01 | 0.00000e+00 | 1.870002e-01 | 4.527005e-01 | 7.260006e-01 | 1.000000e+00 | ▇▆▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.401525e-01 | 3.072384e-01 | 0.00000e+00 | 1.589977e-01 | 4.207073e-01 | 7.059072e-01 | 1.000000e+00 | ▇▅▅▅▅ |
| numeric | AF | 27 | 0.9997740 | NA | NA | NA | NA | NA | 2.828638e-01 | 2.628896e-01 | 1.31900e-03 | 6.332000e-02 | 1.953000e-01 | 4.446000e-01 | 9.986810e-01 | ▇▃▂▂▁ |
| numeric | AF_reference | 759 | 0.9936465 | NA | NA | NA | NA | NA | 2.863228e-01 | 2.549292e-01 | 1.99700e-04 | 7.947280e-02 | 2.042730e-01 | 4.392970e-01 | 1.000000e+00 | ▇▃▂▂▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.090881e+04 | 1.186047e+04 | 2.00068e+04 | 8.079040e+04 | 8.661300e+04 | 8.675580e+04 | 8.685150e+04 | ▁▁▁▁▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 721290 | rs12565286 | G | C | -0.0041 | 0.0209 | 0.7919997 | 0.8444753 | 0.04354 | 0.0371406 | 32893.4 |
| 1 | 1140435 | rs1815606 | G | T | 0.0007 | 0.0052 | 0.8549000 | 0.8929160 | 0.31270 | 0.7120610 | 78713.1 |
| 1 | 1706136 | rs6603811 | T | C | -0.0256 | 0.0100 | 0.0139101 | 0.0104672 | 0.93668 | 0.7466050 | 86134.5 |
| 1 | 1706160 | rs7531583 | A | G | -0.0038 | 0.0057 | 0.6021005 | 0.5049851 | 0.75730 | 0.5832670 | 80804.9 |
| 1 | 1708801 | rs12044597 | A | G | 0.0051 | 0.0048 | 0.3257999 | 0.2880088 | 0.51060 | 0.3602240 | 80787.0 |
| 1 | 1723031 | rs9660180 | G | A | 0.0057 | 0.0049 | 0.2895003 | 0.2447219 | 0.51320 | 0.3580270 | 77979.0 |
| 1 | 1812688 | rs6603803 | A | G | 0.0052 | 0.0048 | 0.3167000 | 0.2786605 | 0.50790 | 0.3606230 | 80441.0 |
| 1 | 1823922 | rs6688000 | A | G | -0.0303 | 0.0105 | 0.0067750 | 0.0039053 | 0.94195 | 0.7651760 | 86140.3 |
| 1 | 1874326 | rs2803328 | C | G | 0.0086 | 0.0050 | 0.0830004 | 0.0854324 | 0.50000 | 0.3835860 | 74018.0 |
| 1 | 2035379 | rs10910029 | A | G | -0.0073 | 0.0048 | 0.2655003 | 0.1283017 | 0.62270 | 0.5315500 | 86126.9 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 50661869 | rs5771242 | T | C | -0.0111 | 0.0054 | 0.0710395 | 0.0398254 | 0.76780 | 0.8512380 | 86113.1 |
| 22 | 50672097 | rs17248301 | T | C | 0.0092 | 0.0183 | 0.7157000 | 0.6151525 | 0.01583 | 0.0517173 | 75104.6 |
| 22 | 50858813 | rs7410608 | G | C | 0.0067 | 0.0049 | 0.2709000 | 0.1715166 | 0.34960 | 0.4916130 | 85992.1 |
| 22 | 50873497 | rs1134848 | C | T | -0.0119 | 0.0089 | 0.3069997 | 0.1811970 | 0.13980 | 0.0529153 | 54571.8 |
| 22 | 50873694 | rs2273259 | T | C | 0.0048 | 0.0052 | 0.5242000 | 0.3559671 | 0.33910 | 0.4802320 | 75541.0 |
| 22 | 50878927 | rs12171249 | G | A | 0.0020 | 0.0060 | 0.7732003 | 0.7388827 | 0.28760 | 0.2062700 | 77281.0 |
| 22 | 51062832 | rs8142033 | G | A | 0.0198 | 0.0092 | 0.0431003 | 0.0313837 | 0.08575 | 0.1773160 | 86110.1 |
| 22 | 51163138 | rs715586 | C | T | -0.0036 | 0.0069 | 0.5803995 | 0.6018520 | 0.12140 | 0.0902556 | 84081.0 |
| 22 | 51165664 | rs8137951 | G | A | -0.0029 | 0.0051 | 0.5316000 | 0.5696090 | 0.28100 | 0.4063500 | 86127.0 |
| 22 | 51178090 | rs2285395 | G | A | 0.0144 | 0.0106 | 0.1900002 | 0.1743081 | 0.05145 | 0.0666933 | 80534.1 |
bcf preview
1 721290 rs12565286 G C . PASS AF=0.04354 ES:SE:LP:AF:SS:ID -0.0041:0.0209:0.101275:0.04354:32893.4:rs12565286
1 1140435 rs1815606 G T . PASS AF=0.3127 ES:SE:LP:AF:SS:ID 0.0007:0.0052:0.0680847:0.3127:78713.1:rs1815606
1 1706136 rs6603811 T C . PASS AF=0.93668 ES:SE:LP:AF:SS:ID -0.0256:0.01:1.85667:0.93668:86134.5:rs6603811
1 1706160 rs7531583 A G . PASS AF=0.7573 ES:SE:LP:AF:SS:ID -0.0038:0.0057:0.220331:0.7573:80804.9:rs7531583
1 1708801 rs12044597 A G . PASS AF=0.5106 ES:SE:LP:AF:SS:ID 0.0051:0.0048:0.487049:0.5106:80787:rs12044597
1 1723031 rs9660180 G A . PASS AF=0.5132 ES:SE:LP:AF:SS:ID 0.0057:0.0049:0.538351:0.5132:77979:rs9660180
1 1812688 rs6603803 A G . PASS AF=0.5079 ES:SE:LP:AF:SS:ID 0.0052:0.0048:0.499352:0.5079:80441:rs6603803
1 1823922 rs6688000 A G . PASS AF=0.94195 ES:SE:LP:AF:SS:ID -0.0303:0.0105:2.16909:0.94195:86140.3:rs6688000
1 1874326 rs2803328 C G . PASS AF=0.5 ES:SE:LP:AF:SS:ID 0.0086:0.005:1.08092:0.5:74018:rs2803328
1 2035379 rs10910029 A G . PASS AF=0.6227 ES:SE:LP:AF:SS:ID -0.0073:0.0048:0.575935:0.6227:86126.9:rs10910029
1 2069172 rs425277 C T . PASS AF=0.2836 ES:SE:LP:AF:SS:ID 0.0004:0.0052:0.138824:0.2836:86205:rs425277
1 2119833 rs2460002 A G . PASS AF=0.6755 ES:SE:LP:AF:SS:ID 0.0084:0.005:0.826231:0.6755:86183.9:rs2460002
1 2142518 rs380190 A C . PASS AF=0.2863 ES:SE:LP:AF:SS:ID -0.0022:0.0055:0.341893:0.2863:74271:rs380190
1 2182342 rs10797416 T C . PASS AF=0.3654 ES:SE:LP:AF:SS:ID -0.0001:0.0048:0.0432075:0.3654:86196:rs10797416
1 2184855 rs12385717 G C . PASS AF=0.06464 ES:SE:LP:AF:SS:ID -0.0073:0.0099:0.4011:0.06464:86092.1:rs12385717
1 2204755 rs7553178 G A . PASS AF=0.6596 ES:SE:LP:AF:SS:ID 0.0054:0.005:0.448306:0.6596:86144:rs7553178
1 2251357 rs12080256 C A . PASS AF=0.2177 ES:SE:LP:AF:SS:ID 0.0193:0.0071:1.93293:0.2177:67726:rs12080256
1 2280661 rs2055204 G A . PASS AF=0.5158 ES:SE:LP:AF:SS:ID -0.0025:0.0047:0.231658:0.5158:86121:rs2055204
1 2390331 rs10910077 G A . PASS AF=0.2916 ES:SE:LP:AF:SS:ID -0.002:0.0052:0.226799:0.2916:83362.9:rs10910077
1 2409383 rs12742193 G A . PASS AF=0.1253 ES:SE:LP:AF:SS:ID -0.0003:0.0107:0.0117087:0.1253:41839:rs12742193
1 2420913 rs6668720 A G . PASS AF=0.6359 ES:SE:LP:AF:SS:ID 0.0054:0.0049:0.868702:0.6359:86031:rs6668720
1 2541727 rs11589185 C T . PASS AF=0.07916 ES:SE:LP:AF:SS:ID -0.0038:0.0084:0.058588:0.07916:75028.7:rs11589185
1 2723345 rs4648360 C T . PASS AF=0.4288 ES:SE:LP:AF:SS:ID -0.0033:0.0047:0.28042:0.4288:86157:rs4648360
1 2725952 rs7538063 C T . PASS AF=0.1715 ES:SE:LP:AF:SS:ID 0.016:0.0068:1.57873:0.1715:81438.1:rs7538063
1 2727804 rs10909880 C T . PASS AF=0.4274 ES:SE:LP:AF:SS:ID -0.0039:0.0061:0.254925:0.4274:57561:rs10909880
1 2829551 rs1869970 A G . PASS AF=0.2322 ES:SE:LP:AF:SS:ID 0.0047:0.0056:0.347464:0.2322:86133:rs1869970
1 2839757 rs4648432 A C . PASS AF=0.2691 ES:SE:LP:AF:SS:ID -0.0053:0.0053:0.441291:0.2691:86056:rs4648432
1 2842270 rs2045331 G A . PASS AF=0.2691 ES:SE:LP:AF:SS:ID -0.0049:0.0053:0.450629:0.2691:86115:rs2045331
1 2890345 rs4648445 G A . PASS AF=0.7111 ES:SE:LP:AF:SS:ID -0.0055:0.005:0.300683:0.7111:84925:rs4648445
1 2904056 rs10797373 G A . PASS AF=0.7058 ES:SE:LP:AF:SS:ID -0.0003:0.0061:0.163993:0.7058:57383.1:rs10797373
1 2996196 rs7525173 C G . PASS AF=0.4974 ES:SE:LP:AF:SS:ID 0.0054:0.005:0.542724:0.4974:72489:rs7525173
1 3089849 rs17390062 T C . PASS AF=0.1135 ES:SE:LP:AF:SS:ID 0.0006:0.0081:0.0484197:0.1135:86363.2:rs17390062
1 3103826 rs4233024 C T . PASS AF=0.8522 ES:SE:LP:AF:SS:ID 0.0098:0.0082:0.67305:0.8522:57510.4:rs4233024
1 3105276 rs2817138 T G . PASS AF=0.8588 ES:SE:LP:AF:SS:ID 0.0067:0.0071:0.41805:0.8588:86259.8:rs2817138
1 3117678 rs12095716 G C . PASS AF=0.2256 ES:SE:LP:AF:SS:ID -0.0014:0.0059:0.139243:0.2256:86131.9:rs12095716
1 3138136 rs2817148 A G . PASS AF=0.02375 ES:SE:LP:AF:SS:ID 0.014:0.0172:0.393619:0.02375:72152.2:rs2817148
1 3144068 rs10158583 G A . PASS AF=0.08971 ES:SE:LP:AF:SS:ID 0.0008:0.0094:0.0801377:0.08971:74613:rs10158583
1 3209631 rs4648376 G A . PASS AF=0.562 ES:SE:LP:AF:SS:ID 0.0019:0.0047:0.148742:0.562:86333:rs4648376
1 3214170 rs7553849 T C . PASS AF=0.7625 ES:SE:LP:AF:SS:ID 0.0024:0.0057:0.0105502:0.7625:86345:rs7553849
1 3229185 rs12743017 G A . PASS AF=0.07652 ES:SE:LP:AF:SS:ID -0.0088:0.0086:0.818728:0.07652:86335.2:rs12743017
1 3264190 rs2483289 A C . PASS AF=0.7098 ES:SE:LP:AF:SS:ID -0.0014:0.0051:0.0263642:0.7098:86327:rs2483289
1 3491107 rs4431782 T C . PASS AF=0.0752 ES:SE:LP:AF:SS:ID -0.006:0.0083:0.348141:0.0752:80835:rs4431782
1 3564818 rs3765690 A T . PASS AF=0.04222 ES:SE:LP:AF:SS:ID -0.0005:0.0109:0.164056:0.04222:84855.6:rs3765690
1 3654747 rs7515164 C A . PASS AF=0.06464 ES:SE:LP:AF:SS:ID -0.0127:0.0101:0.671824:0.06464:86302.3:rs7515164
1 3793324 rs6668103 A G . PASS AF=0.2876 ES:SE:LP:AF:SS:ID -0.0029:0.0061:0.14533:0.2876:64632:rs6668103
1 3812610 rs12757243 G A . PASS AF=0.009235 ES:SE:LP:AF:SS:ID -0.014:0.0221:0.05061:0.009235:79676.8:rs12757243
1 4010342 rs12046333 A G . PASS AF=0.06992 ES:SE:LP:AF:SS:ID -0.0095:0.0109:0.397614:0.06992:74514.9:rs12046333
1 4039896 rs11587331 C T . PASS AF=0.5897 ES:SE:LP:AF:SS:ID 0.0073:0.0047:0.718967:0.5897:86329.1:rs11587331
1 4080885 rs4378174 C T . PASS AF=0.1583 ES:SE:LP:AF:SS:ID 0.0023:0.0068:0.188492:0.1583:86287:rs4378174
1 4085543 rs12026862 T C . PASS AF=0.01451 ES:SE:LP:AF:SS:ID 0.0164:0.018:0.906578:0.01451:66706:rs12026862