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-292/ieu-a-292.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-292/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 11:46:48 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-292/ieu-a-292.vcf.gz ...
Read summary statistics for 14352 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, 14107 SNPs remain.
After merging with regression SNP LD, 14107 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: 15.5612 (1.7143)
Lambda GC: 27.6897
Mean Chi^2: 22.684
Intercept: 8.2358 (0.3569)
Ratio: 0.3337 (0.0165)
Analysis finished at Wed Feb 5 11:46:55 2020
Total time elapsed: 7.46sQC metrics
Metrics
Metrics
{
"af_correlation": 0.8863,
"inflation_factor": 27.2402,
"mean_EFFECT": 0.0043,
"n": 33000,
"n_snps": 14352,
"n_clumped_hits": 114,
"n_p_sig": 3061,
"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": 0,
"n_miss_AF_reference": 94,
"n_est": 32851.0508,
"ratio_se_n": 0.9977,
"mean_diff": -0.0011,
"ratio_diff": 6.003,
"sd_y_est1": 1.4178,
"sd_y_est2": 1.4146,
"r2_sum1": 0.6063,
"r2_sum2": 0.3016,
"r2_sum3": 0.3029,
"r2_sum4": 0.2887,
"ldsc_nsnp_merge_refpanel_ld": 14107,
"ldsc_nsnp_merge_regression_ld": 14107,
"ldsc_observed_scale_h2_beta": 15.5612,
"ldsc_observed_scale_h2_se": 1.7143,
"ldsc_intercept_beta": 8.2358,
"ldsc_intercept_se": 0.3569,
"ldsc_lambda_gc": 27.6897,
"ldsc_mean_chisq": 22.684,
"ldsc_ratio": 0.3337
}
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 | TRUE |
| n_clumped_hits | FALSE |
| r2_sum1 | TRUE |
| 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 | 21 | 0 | 14352 | 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 | 8.829501e+00 | 6.212953e+00 | 1.00000e+00 | 3.000000e+00 | 8.000000e+00 | 1.30000e+01 | 2.20000e+01 | ▇▃▃▃▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.846165e+07 | 5.664125e+07 | 6.53510e+04 | 3.748686e+07 | 6.228988e+07 | 1.13037e+08 | 2.47655e+08 | ▇▆▃▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.348100e-03 | 6.507820e-02 | -7.09480e-01 | -4.489280e-02 | 1.488860e-02 | 5.05567e-02 | 5.61899e-01 | ▁▁▇▂▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.394590e-02 | 6.135900e-03 | 1.07999e-02 | 1.130020e-02 | 1.220020e-02 | 1.42999e-02 | 2.19300e-01 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.543910e-02 | 1.034758e-01 | 0.00000e+00 | 4.000000e-07 | 4.311000e-04 | 1.69725e-02 | 9.97600e-01 | ▇▁▁▁▁ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.545130e-02 | 1.034479e-01 | 0.00000e+00 | 4.000000e-07 | 4.235000e-04 | 1.68700e-02 | 1.00000e+00 | ▇▁▁▁▁ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.985416e-01 | 2.307958e-01 | 2.62000e-04 | 2.140000e-01 | 3.670000e-01 | 5.77000e-01 | 9.92000e-01 | ▆▇▆▅▂ |
| numeric | AF_reference | 94 | 0.9934504 | NA | NA | NA | NA | NA | 3.933883e-01 | 2.293012e-01 | 3.99400e-04 | 2.040730e-01 | 3.619210e-01 | 5.63898e-01 | 9.94010e-01 | ▆▇▆▅▂ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.300000e+04 | 0.000000e+00 | 3.30000e+04 | 3.300000e+04 | 3.300000e+04 | 3.30000e+04 | 3.30000e+04 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 1120431 | rs1320571 | G | A | 0.0487902 | 0.0302005 | 0.1049999 | 0.1061932 | 0.0442 | 0.185304 | 33000 |
| 1 | 1140435 | rs1815606 | G | T | 0.0497421 | 0.0125014 | 0.0000633 | 0.0000692 | 0.3100 | 0.712061 | 33000 |
| 1 | 1152631 | rs11721 | C | A | 0.0971267 | 0.0174996 | 0.0000000 | 0.0000000 | 0.0781 | 0.158546 | 33000 |
| 1 | 1163804 | rs7515488 | C | T | 0.0953102 | 0.0155009 | 0.0000000 | 0.0000000 | 0.1470 | 0.186901 | 33000 |
| 1 | 1165310 | rs11260562 | G | A | 0.1079570 | 0.0239007 | 0.0000066 | 0.0000063 | 0.0546 | 0.101837 | 33000 |
| 1 | 1173611 | rs6697886 | G | A | 0.0962189 | 0.0162001 | 0.0000000 | 0.0000000 | 0.1310 | 0.220647 | 33000 |
| 1 | 1174282 | rs4970364 | T | C | 0.0901435 | 0.0141999 | 0.0000000 | 0.0000000 | 0.2400 | 0.658147 | 33000 |
| 1 | 1176597 | rs6675798 | T | C | 0.0977231 | 0.0172002 | 0.0000000 | 0.0000000 | 0.1000 | 0.182109 | 33000 |
| 1 | 1177630 | rs2297864 | A | G | 0.0980539 | 0.0172000 | 0.0000000 | 0.0000000 | 0.0990 | 0.170128 | 33000 |
| 1 | 1178245 | rs11260566 | C | T | 0.0980337 | 0.0171993 | 0.0000000 | 0.0000000 | 0.0931 | 0.178714 | 33000 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 50333415 | rs4073387 | G | A | 0.0582689 | 0.0174999 | 0.0008108 | 0.0008695 | 0.141 | 0.0898562 | 33000 |
| 22 | 50351977 | rs28681372 | G | A | -0.0294288 | 0.0124000 | 0.0179399 | 0.0176304 | 0.620 | 0.5822680 | 33000 |
| 22 | 50435480 | rs5771069 | A | G | 0.0313875 | 0.0113001 | 0.0055280 | 0.0054757 | 0.509 | 0.6070290 | 33000 |
| 22 | 50439430 | rs137845 | A | G | 0.0310780 | 0.0113000 | 0.0060660 | 0.0059547 | 0.507 | 0.6080270 | 33000 |
| 22 | 50446550 | rs137862 | C | A | 0.0305292 | 0.0114007 | 0.0064880 | 0.0074100 | 0.514 | 0.5938500 | 33000 |
| 22 | 50446988 | rs137864 | C | T | 0.0305292 | 0.0112993 | 0.0071280 | 0.0068951 | 0.508 | 0.5818690 | 33000 |
| 22 | 50961854 | rs2782 | T | C | -0.0525924 | 0.0114012 | 0.0000039 | 0.0000040 | 0.609 | 0.6525560 | 33000 |
| 22 | 50962208 | rs12148 | T | G | -0.0525924 | 0.0114012 | 0.0000039 | 0.0000040 | 0.609 | 0.6555510 | 33000 |
| 22 | 50966914 | rs470119 | T | C | -0.0525924 | 0.0114012 | 0.0000044 | 0.0000040 | 0.608 | 0.5547120 | 33000 |
| 22 | 50971266 | rs140522 | T | C | -0.0563803 | 0.0115991 | 0.0000011 | 0.0000012 | 0.669 | 0.6190100 | 33000 |
bcf preview
1 1120431 rs1320571 G A . PASS AF=0.0442 ES:SE:LP:AF:SS:ID 0.0487902:0.0302005:0.978811:0.0442:33000:rs1320571
1 1140435 rs1815606 G T . PASS AF=0.31 ES:SE:LP:AF:SS:ID 0.0497421:0.0125014:4.1988:0.31:33000:rs1815606
1 1152631 rs11721 C A . PASS AF=0.0781 ES:SE:LP:AF:SS:ID 0.0971267:0.0174996:7.52959:0.0781:33000:rs11721
1 1163804 rs7515488 C T . PASS AF=0.147 ES:SE:LP:AF:SS:ID 0.0953102:0.0155009:9.1152:0.147:33000:rs7515488
1 1165310 rs11260562 G A . PASS AF=0.0546 ES:SE:LP:AF:SS:ID 0.107957:0.0239007:5.18013:0.0546:33000:rs11260562
1 1173611 rs6697886 G A . PASS AF=0.131 ES:SE:LP:AF:SS:ID 0.0962189:0.0162001:8.61243:0.131:33000:rs6697886
1 1174282 rs4970364 T C . PASS AF=0.24 ES:SE:LP:AF:SS:ID 0.0901435:0.0141999:9.63339:0.24:33000:rs4970364
1 1176597 rs6675798 T C . PASS AF=0.1 ES:SE:LP:AF:SS:ID 0.0977231:0.0172002:7.89722:0.1:33000:rs6675798
1 1177630 rs2297864 A G . PASS AF=0.099 ES:SE:LP:AF:SS:ID 0.0980539:0.0172:7.88739:0.099:33000:rs2297864
1 1178245 rs11260566 C T . PASS AF=0.0931 ES:SE:LP:AF:SS:ID 0.0980337:0.0171993:7.87647:0.0931:33000:rs11260566
1 1178925 rs12093154 G A . PASS AF=0.0953 ES:SE:LP:AF:SS:ID 0.0980337:0.0171993:7.94539:0.0953:33000:rs12093154
1 1192515 rs7524470 A G . PASS AF=0.039 ES:SE:LP:AF:SS:ID 0.0653922:0.0234999:2.26769:0.039:33000:rs7524470
1 1193723 rs12072310 A C . PASS AF=0.051 ES:SE:LP:AF:SS:ID 0.0778534:0.0228999:3.17705:0.051:33000:rs12072310
1 1194804 rs11804831 T C . PASS AF=0.183 ES:SE:LP:AF:SS:ID 0.0990472:0.0147999:10.7077:0.183:33000:rs11804831
1 1201640 rs11260570 T C . PASS AF=0.039 ES:SE:LP:AF:SS:ID 0.0662466:0.0235001:2.3165:0.039:33000:rs11260570
1 1206343 rs6667923 C A . PASS AF=0.0354 ES:SE:LP:AF:SS:ID 0.0667236:0.0234997:2.34065:0.0354:33000:rs6667923
1 1209636 rs3737722 A G . PASS AF=0.064 ES:SE:LP:AF:SS:ID 0.0705298:0.0218001:2.92046:0.064:33000:rs3737722
1 1210471 rs11260577 T C . PASS AF=0.078 ES:SE:LP:AF:SS:ID 0.0803428:0.0210999:3.86012:0.078:33000:rs11260577
1 1211292 rs6685064 C T . PASS AF=0.0625 ES:SE:LP:AF:SS:ID 0.0695261:0.0213989:2.923:0.0625:33000:rs6685064
1 1218086 rs6603788 C T . PASS AF=0.0732 ES:SE:LP:AF:SS:ID 0.0825012:0.0212007:4.01117:0.0732:33000:rs6603788
1 1232319 rs604618 G A . PASS AF=0.0711 ES:SE:LP:AF:SS:ID 0.0861777:0.0235991:3.6038:0.0711:33000:rs604618
1 1233941 rs1739855 T C . PASS AF=0.072 ES:SE:LP:AF:SS:ID 0.0864297:0.0233001:3.69186:0.072:33000:rs1739855
1 1237036 rs2477782 T C . PASS AF=0.074 ES:SE:LP:AF:SS:ID 0.0868659:0.0231999:3.73707:0.074:33000:rs2477782
1 1239339 rs11260584 T G . PASS AF=0.9342 ES:SE:LP:AF:SS:ID -0.0870947:0.0232994:3.71422:0.9342:33000:rs11260584
1 1239935 rs12410087 A C . PASS AF=0.108 ES:SE:LP:AF:SS:ID 0.100705:0.0163001:9.15503:0.108:33000:rs12410087
1 1247494 rs12103 T C . PASS AF=0.818 ES:SE:LP:AF:SS:ID -0.109751:0.0152993:12.1157:0.818:33000:rs12103
1 1249187 rs12142199 G A . PASS AF=0.811 ES:SE:LP:AF:SS:ID -0.0977231:0.0150002:10.12:0.811:33000:rs12142199
1 1250957 rs34054191 G A . PASS AF=0.0335 ES:SE:LP:AF:SS:ID 0.0916672:0.0271012:3.17627:0.0335:33000:rs34054191
1 1254136 rs4970432 G A . PASS AF=0.931 ES:SE:LP:AF:SS:ID -0.0842516:0.0225001:3.75056:0.931:33000:rs4970432
1 1258246 rs3845293 A C . PASS AF=0.9345 ES:SE:LP:AF:SS:ID -0.0834216:0.0225013:3.7018:0.9345:33000:rs3845293
1 1287127 rs307380 G A . PASS AF=0.933 ES:SE:LP:AF:SS:ID -0.0811016:0.0223:3.56976:0.933:33000:rs307380
1 1295323 rs34389364 G A . PASS AF=0.929 ES:SE:LP:AF:SS:ID -0.0808847:0.0223002:3.5516:0.929:33000:rs34389364
1 1295403 rs34876581 T C . PASS AF=0.9326 ES:SE:LP:AF:SS:ID -0.0806579:0.0223002:3.55783:0.9326:33000:rs34876581
1 1297065 rs2765023 C T . PASS AF=0.106 ES:SE:LP:AF:SS:ID 0.0998453:0.0161991:9.13859:0.106:33000:rs2765023
1 1297422 rs2765021 C T . PASS AF=0.932 ES:SE:LP:AF:SS:ID -0.0806679:0.0222:3.56607:0.932:33000:rs2765021
1 1305561 rs17160669 C T . PASS AF=0.105 ES:SE:LP:AF:SS:ID 0.0971267:0.0161993:8.73377:0.105:33000:rs17160669
1 1314015 rs2649588 C T . PASS AF=0.927 ES:SE:LP:AF:SS:ID -0.0772051:0.0217998:3.41061:0.927:33000:rs2649588
1 1333598 rs35242196 C A . PASS AF=0.0964 ES:SE:LP:AF:SS:ID 0.0925792:0.0166008:7.55098:0.0964:33000:rs35242196
1 1335790 rs1240708 A G . PASS AF=0.168 ES:SE:LP:AF:SS:ID 0.100815:0.0155001:10.0802:0.168:33000:rs1240708
1 1365570 rs1695824 A C . PASS AF=0.218 ES:SE:LP:AF:SS:ID 0.08534:0.015:7.85699:0.218:33000:rs1695824
1 1366830 rs873927 A G . PASS AF=0.218 ES:SE:LP:AF:SS:ID 0.085449:0.0151:7.84224:0.218:33000:rs873927
1 1665613 rs4648764 A G . PASS AF=0.457 ES:SE:LP:AF:SS:ID 0.0537173:0.0120999:5.0355:0.457:33000:rs4648764
1 1684472 rs7407 C T . PASS AF=0.507 ES:SE:LP:AF:SS:ID -0.0525573:0.0116998:5.16564:0.507:33000:rs7407
1 1687625 rs34306661 T C . PASS AF=0.436 ES:SE:LP:AF:SS:ID 0.0534008:0.0116002:5.38059:0.436:33000:rs34306661
1 1689164 rs2235536 C T . PASS AF=0.424 ES:SE:LP:AF:SS:ID 0.0535408:0.0116007:5.35184:0.424:33000:rs2235536
1 1689762 rs2235537 T C . PASS AF=0.439 ES:SE:LP:AF:SS:ID 0.0528735:0.0116:5.31876:0.439:33000:rs2235537
1 1691050 rs35672141 C T . PASS AF=0.487 ES:SE:LP:AF:SS:ID -0.0544562:0.0115002:5.70908:0.487:33000:rs35672141
1 1692321 rs1107910 T C . PASS AF=0.448 ES:SE:LP:AF:SS:ID 0.0515038:0.0113001:5.27893:0.448:33000:rs1107910
1 1707740 rs12041925 T G . PASS AF=0.262 ES:SE:LP:AF:SS:ID 0.0442654:0.0125:3.42864:0.262:33000:rs12041925
1 1708801 rs12044597 A G . PASS AF=0.497 ES:SE:LP:AF:SS:ID -0.0573251:0.0110993:6.63676:0.497:33000:rs12044597