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-296/ieu-a-296.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-296/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 11:33:57 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-296/ieu-a-296.vcf.gz ...
Read summary statistics for 124470 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, 50539 SNPs remain.
After merging with regression SNP LD, 50539 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: 2.9489 (1.4824)
Lambda GC: 1.1647
Mean Chi^2: 1.1369
Intercept: 1.0798 (0.0199)
Ratio: 0.5825 (0.145)
Analysis finished at Wed Feb 5 11:34:13 2020
Total time elapsed: 15.66sQC metrics
Metrics
Metrics
{
"af_correlation": 0.7836,
"inflation_factor": 1.2439,
"mean_EFFECT": 0.014,
"n": 890,
"n_snps": 124470,
"n_clumped_hits": 0,
"n_p_sig": 0,
"n_mono": 0,
"n_ns": 0,
"n_mac": 3356,
"is_snpid_unique": true,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 1562,
"n_miss_AF_reference": 836,
"n_est": 887.4038,
"ratio_se_n": 0.9985,
"mean_diff": 0.0185,
"ratio_diff": 1.9071,
"sd_y_est1": 2.004,
"sd_y_est2": 2.0011,
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 50539,
"ldsc_nsnp_merge_regression_ld": 50539,
"ldsc_observed_scale_h2_beta": 2.9489,
"ldsc_observed_scale_h2_se": 1.4824,
"ldsc_intercept_beta": 1.0798,
"ldsc_intercept_se": 0.0199,
"ldsc_lambda_gc": 1.1647,
"ldsc_mean_chisq": 1.1369,
"ldsc_ratio": 0.5829
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | TRUE |
| n | TRUE |
| 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 | TRUE |
| 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 | 25 | 0 | 124470 | 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 | 8.089162e+00 | 5.770009e+00 | 1.00000e+00 | 3.000000e+00 | 6.000000e+00 | 1.200000e+01 | 2.200000e+01 | ▇▅▃▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.905289e+07 | 5.780982e+07 | 6.34110e+04 | 3.290885e+07 | 6.221905e+07 | 1.176620e+08 | 2.492107e+08 | ▇▅▃▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.397640e-02 | 8.381141e-01 | -7.25700e+01 | -1.071860e-01 | 1.202300e-03 | 1.125892e-01 | 8.823950e+01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.411805e-01 | 5.954927e-01 | 8.84652e-02 | 1.024980e-01 | 1.265900e-01 | 2.006810e-01 | 6.370640e+01 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.674632e-01 | 2.938981e-01 | 2.00000e-07 | 2.053037e-01 | 4.518929e-01 | 7.220940e-01 | 9.999700e-01 | ▇▇▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.676511e-01 | 2.937407e-01 | 2.00000e-07 | 2.056890e-01 | 4.520419e-01 | 7.221005e-01 | 9.999700e-01 | ▇▇▆▆▆ |
| numeric | AF | 1562 | 0.9874508 | NA | NA | NA | NA | NA | 3.171409e-01 | 2.834003e-01 | 1.46200e-03 | 7.602000e-02 | 2.287000e-01 | 5.088000e-01 | 9.985380e-01 | ▇▃▂▂▂ |
| numeric | AF_reference | 836 | 0.9932835 | NA | NA | NA | NA | NA | 2.868103e-01 | 2.577058e-01 | 1.99700e-04 | 7.408150e-02 | 2.062700e-01 | 4.464860e-01 | 1.000000e+00 | ▇▃▂▂▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.900000e+02 | 0.000000e+00 | 8.90000e+02 | 8.900000e+02 | 8.900000e+02 | 8.900000e+02 | 8.900000e+02 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 1118275 | rs61733845 | C | T | 0.1971380 | 0.1502180 | 0.1896710 | 0.1894034 | 0.09795 | 0.185703 | 890 |
| 1 | 1120431 | rs1320571 | G | A | 0.2289800 | 0.1507100 | 0.1289149 | 0.1286765 | 0.10820 | 0.185304 | 890 |
| 1 | 1135242 | rs9729550 | A | C | 0.0075952 | 0.0971193 | 0.9376639 | 0.9376649 | 0.34500 | 0.551917 | 890 |
| 1 | 1140435 | rs1815606 | G | T | 0.0458568 | 0.0925871 | 0.6204446 | 0.6204005 | 0.43860 | 0.712061 | 890 |
| 1 | 1163804 | rs7515488 | C | T | 0.1893450 | 0.1346840 | 0.1598961 | 0.1597698 | 0.14470 | 0.186901 | 890 |
| 1 | 1165310 | rs11260562 | G | A | -0.0825209 | 0.1861440 | 0.6575382 | 0.6575361 | 0.07310 | 0.101837 | 890 |
| 1 | 1173611 | rs6697886 | G | A | 0.1235940 | 0.1394840 | 0.3756272 | 0.3755744 | 0.13160 | 0.220647 | 890 |
| 1 | 1186502 | rs6603785 | A | T | 0.0870824 | 0.1499220 | 0.5612224 | 0.5613406 | 0.11400 | 0.246206 | 890 |
| 1 | 1194804 | rs11804831 | T | C | -0.0553558 | 0.0971645 | 0.5688804 | 0.5688729 | 0.35230 | 0.685903 | 890 |
| 1 | 1218086 | rs6603788 | C | T | -0.0886581 | 0.1297030 | 0.4942640 | 0.4942612 | 0.16520 | 0.469449 | 890 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 50966914 | rs470119 | T | C | 0.0458906 | 0.1035610 | 0.6577033 | 0.6576744 | 0.6857 | 0.5547120 | 890 |
| 22 | 50971752 | rs131794 | A | C | -0.0378076 | 0.1229260 | 0.7583942 | 0.7584142 | 0.8056 | 0.8326680 | 890 |
| 22 | 50988193 | rs131779 | A | G | -0.0378815 | 0.0990089 | 0.7020305 | 0.7020112 | 0.6477 | 0.5802720 | 890 |
| 22 | 50999182 | rs140518 | C | T | -0.0974002 | 0.1055840 | 0.3563732 | 0.3562730 | 0.7251 | 0.7655750 | 890 |
| 22 | 51078251 | rs4040041 | C | T | -0.0447923 | 0.0971731 | 0.6448727 | 0.6448318 | 0.4386 | 0.4666530 | 890 |
| 22 | 51094926 | rs9616810 | C | T | -0.0987573 | 0.1135030 | 0.3843519 | 0.3842538 | 0.2456 | 0.2224440 | 890 |
| 22 | 51105556 | rs9616812 | C | T | 0.0394561 | 0.0935837 | 0.6733394 | 0.6733076 | 0.4430 | 0.3628190 | 890 |
| 22 | 51109992 | rs9628185 | T | C | -0.0001375 | 0.0932462 | 0.9988240 | 0.9988239 | 0.4561 | 0.4053510 | 890 |
| 22 | 51134186 | rs8135777 | A | G | 1.5038300 | 2.6101100 | 0.5644806 | 0.5645099 | NA | 0.0273562 | 890 |
| 22 | 51156666 | rs9628187 | C | T | -0.0273881 | 0.1334530 | 0.8373980 | 0.8373951 | 0.1652 | 0.1299920 | 890 |
bcf preview
1 1118275 rs61733845 C T . PASS AF=0.09795 ES:SE:LP:AF:SS:ID 0.197138:0.150218:0.721999:0.09795:890:rs61733845
1 1120431 rs1320571 G A . PASS AF=0.1082 ES:SE:LP:AF:SS:ID 0.22898:0.15071:0.889697:0.1082:890:rs1320571
1 1135242 rs9729550 A C . PASS AF=0.345 ES:SE:LP:AF:SS:ID 0.00759523:0.0971193:0.0279528:0.345:890:rs9729550
1 1140435 rs1815606 G T . PASS AF=0.4386 ES:SE:LP:AF:SS:ID 0.0458568:0.0925871:0.207297:0.4386:890:rs1815606
1 1163804 rs7515488 C T . PASS AF=0.1447 ES:SE:LP:AF:SS:ID 0.189345:0.134684:0.796162:0.1447:890:rs7515488
1 1165310 rs11260562 G A . PASS AF=0.0731 ES:SE:LP:AF:SS:ID -0.0825209:0.186144:0.182079:0.0731:890:rs11260562
1 1173611 rs6697886 G A . PASS AF=0.1316 ES:SE:LP:AF:SS:ID 0.123594:0.139484:0.425243:0.1316:890:rs6697886
1 1186502 rs6603785 A T . PASS AF=0.114 ES:SE:LP:AF:SS:ID 0.0870824:0.149922:0.250865:0.114:890:rs6603785
1 1194804 rs11804831 T C . PASS AF=0.3523 ES:SE:LP:AF:SS:ID -0.0553558:0.0971645:0.244979:0.3523:890:rs11804831
1 1218086 rs6603788 C T . PASS AF=0.1652 ES:SE:LP:AF:SS:ID -0.0886581:0.129703:0.306041:0.1652:890:rs6603788
1 1227897 rs3737721 A G . PASS AF=0.06871 ES:SE:LP:AF:SS:ID -0.418591:0.201492:1.42128:0.06871:890:rs3737721
1 1231656 rs1749951 G A . PASS AF=0.05848 ES:SE:LP:AF:SS:ID 0.177098:0.18274:0.478117:0.05848:890:rs1749951
1 1233941 rs1739855 T C . PASS AF=0.1827 ES:SE:LP:AF:SS:ID -0.104524:0.123998:0.398654:0.1827:890:rs1739855
1 1241529 rs1536168 A G . PASS AF=0.91228 ES:SE:LP:AF:SS:ID -0.102936:0.156496:0.291803:0.91228:890:rs1536168
1 1242468 rs2274264 G A . PASS AF=0.06433 ES:SE:LP:AF:SS:ID -0.342134:0.203715:1.03051:0.06433:890:rs2274264
1 1247494 rs12103 T C . PASS AF=0.6857 ES:SE:LP:AF:SS:ID -0.00759635:0.101205:0.0267945:0.6857:890:rs12103
1 1249187 rs12142199 G A . PASS AF=0.6769 ES:SE:LP:AF:SS:ID 0.0176689:0.100934:0.0649782:0.6769:890:rs12142199
1 1254255 rs62623580 G A . PASS AF=0.04386 ES:SE:LP:AF:SS:ID 0.0118254:0.231982:0.0180252:0.04386:890:rs62623580
1 1335790 rs1240708 A G . PASS AF=0.3114 ES:SE:LP:AF:SS:ID 0.00301805:0.103663:0.0102059:0.3114:890:rs1240708
1 1493727 rs880051 G A . PASS AF=0.3816 ES:SE:LP:AF:SS:ID 0.0578318:0.0974109:0.257449:0.3816:890:rs880051
1 1497824 rs2296716 C T . PASS AF=0.1784 ES:SE:LP:AF:SS:ID 0.0588694:0.130727:0.185421:0.1784:890:rs2296716
1 1611995 rs4074196 A G . PASS AF=0.3713 ES:SE:LP:AF:SS:ID 0.0747611:0.0989581:0.347054:0.3713:890:rs4074196
1 1706160 rs7531583 A G . PASS AF=0.5673 ES:SE:LP:AF:SS:ID 0.0314803:0.094766:0.130909:0.5673:890:rs7531583
1 1721479 rs2272908 C T . PASS AF=0.348 ES:SE:LP:AF:SS:ID -0.0957355:0.098364:0.480939:0.348:890:rs2272908
1 1723031 rs9660180 G A . PASS AF=0.348 ES:SE:LP:AF:SS:ID -0.0957355:0.098364:0.480939:0.348:890:rs9660180
1 1781220 rs6681938 T C . PASS AF=0.2135 ES:SE:LP:AF:SS:ID -0.124267:0.117376:0.537767:0.2135:890:rs6681938
1 1838516 rs2377037 C A . PASS AF=0.2222 ES:SE:LP:AF:SS:ID 0.137624:0.111768:0.660976:0.2222:890:rs2377037
1 1840038 rs2474461 T C . PASS AF=0.8874 ES:SE:LP:AF:SS:ID 0.170283:0.154241:0.569998:0.8874:890:rs2474461
1 1853288 rs1884454 G T . PASS AF=0.2339 ES:SE:LP:AF:SS:ID 0.0942276:0.110757:0.403436:0.2339:890:rs1884454
1 1855319 rs2295362 C T . PASS AF=0.1155 ES:SE:LP:AF:SS:ID -0.0769893:0.149661:0.216827:0.1155:890:rs2295362
1 1871337 rs16824543 G A . PASS AF=0.117 ES:SE:LP:AF:SS:ID -0.0828468:0.148512:0.238841:0.117:890:rs16824543
1 1873625 rs12758705 G A . PASS AF=0.2266 ES:SE:LP:AF:SS:ID 0.100715:0.111847:0.434195:0.2266:890:rs12758705
1 1881070 rs4648596 G A . PASS AF=0.08626 ES:SE:LP:AF:SS:ID -0.042926:0.173019:0.0947115:0.08626:890:rs4648596
1 1888193 rs3820011 C A . PASS AF=0.2442 ES:SE:LP:AF:SS:ID 0.128456:0.110239:0.612446:0.2442:890:rs3820011
1 2024064 rs2459994 C T . PASS AF=0.2991 ES:SE:LP:AF:SS:ID 0.198481:0.10633:1.20607:0.2991:890:rs2459994
1 2146966 rs7512482 T C . PASS AF=0.2295 ES:SE:LP:AF:SS:ID 0.0430345:0.112618:0.153445:0.2295:890:rs7512482
1 2202774 rs6673129 C T . PASS AF=0.1681 ES:SE:LP:AF:SS:ID 0.224752:0.1272:1.1107:0.1681:890:rs6673129
1 2229478 rs12562937 C T . PASS AF=0.1711 ES:SE:LP:AF:SS:ID -0.00879712:0.12935:0.0242122:0.1711:890:rs12562937
1 2283896 rs2840528 A G . PASS AF=0.3421 ES:SE:LP:AF:SS:ID -0.06569:0.101466:0.28623:0.3421:890:rs2840528
1 2290143 rs34587196 G A . PASS AF=0.01023 ES:SE:LP:AF:SS:ID 0.691058:0.413551:1.02275:0.01023:890:rs34587196
1 2404256 rs2494626 C T . PASS AF=0.3202 ES:SE:LP:AF:SS:ID -0.038685:0.103617:0.149421:0.3202:890:rs2494626
1 2407781 rs78504402 C T . PASS AF=0.04386 ES:SE:LP:AF:SS:ID 0.0448665:0.230246:0.0728874:0.04386:890:rs78504402
1 2408471 rs115996655 G A . PASS AF=0.001462 ES:SE:LP:AF:SS:ID -3.23115:2.55819:0.684884:0.001462:890:rs115996655
1 2408834 rs11588930 G A . PASS AF=0.09064 ES:SE:LP:AF:SS:ID 0.167102:0.154025:0.555471:0.09064:890:rs11588930
1 2409892 rs12727342 A G . PASS AF=0.6477 ES:SE:LP:AF:SS:ID -0.112285:0.0969316:0.607738:0.6477:890:rs12727342
1 2410789 rs11799501 C T . PASS AF=0.636 ES:SE:LP:AF:SS:ID -0.10539:0.0970827:0.556407:0.636:890:rs11799501
1 2412279 rs4648638 A T . PASS AF=0.3567 ES:SE:LP:AF:SS:ID 0.145927:0.0963199:0.886511:0.3567:890:rs4648638
1 2412293 rs12731186 C T . PASS AF=0.08918 ES:SE:LP:AF:SS:ID -0.115429:0.169603:0.304356:0.08918:890:rs12731186
1 2413166 rs115810747 A G . PASS AF=0.004386 ES:SE:LP:AF:SS:ID 0.523005:0.575431:0.439537:0.004386:890:rs115810747
1 2413464 rs114424485 G C . PASS AF=0.001462 ES:SE:LP:AF:SS:ID -3.23115:2.55819:0.684884:0.001462:890:rs114424485