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-1058/ieu-a-1058.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-1058/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 11:34:15 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1058/ieu-a-1058.vcf.gz ...
Read summary statistics for 30341 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, 22620 SNPs remain.
After merging with regression SNP LD, 22620 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: 0.4375 (0.1141)
Lambda GC: 1.3112
Mean Chi^2: 1.4065
Intercept: 1.2176 (0.0377)
Ratio: 0.5353 (0.0928)
Analysis finished at Wed Feb 5 11:34:25 2020
Total time elapsed: 10.76sQC metrics
Metrics
Metrics
{
"af_correlation": 0.921,
"inflation_factor": 1.6133,
"mean_EFFECT": -0.0005,
"n": 24269,
"n_snps": 30341,
"n_clumped_hits": 15,
"n_p_sig": 2285,
"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": 93,
"n_est": 23995.997,
"ratio_se_n": 0.9944,
"mean_diff": 0.0014,
"ratio_diff": 1.261,
"sd_y_est1": 2.0537,
"sd_y_est2": 2.0421,
"r2_sum1": 0.8592,
"r2_sum2": 0.2037,
"r2_sum3": 0.206,
"r2_sum4": 0.1711,
"ldsc_nsnp_merge_refpanel_ld": 22620,
"ldsc_nsnp_merge_regression_ld": 22620,
"ldsc_observed_scale_h2_beta": 0.4375,
"ldsc_observed_scale_h2_se": 0.1141,
"ldsc_intercept_beta": 1.2176,
"ldsc_intercept_se": 0.0377,
"ldsc_lambda_gc": 1.3112,
"ldsc_mean_chisq": 1.4065,
"ldsc_ratio": 0.5353
}
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 | TRUE |
| ldsc_intercept_beta | FALSE |
| 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 | 22 | 0 | 30341 | 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 | 8.664711e+00 | 5.738202e+00 | 1.00000e+00 | 4.000000e+00 | 7.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▇▅▃▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.392248e+07 | 5.537350e+07 | 6.26140e+04 | 3.056204e+07 | 5.939664e+07 | 1.105376e+08 | 2.492107e+08 | ▇▅▃▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -5.480000e-04 | 2.295074e-01 | -1.90583e+00 | -2.176150e-02 | -9.995000e-04 | 1.980260e-02 | 2.100840e+01 | ▇▁▁▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.304391e-01 | 1.399497e+02 | 1.26792e-02 | 1.947250e-02 | 2.246300e-02 | 2.926580e-02 | 2.437740e+04 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.165367e-01 | 3.118337e-01 | 0.00000e+00 | 1.229000e-01 | 3.916003e-01 | 6.883004e-01 | 9.993000e-01 | ▇▅▅▅▃ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.165357e-01 | 3.118340e-01 | 0.00000e+00 | 1.228312e-01 | 3.916671e-01 | 6.883469e-01 | 9.993124e-01 | ▇▅▅▅▃ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.421246e-01 | 2.534484e-01 | 1.09600e-02 | 1.295000e-01 | 2.779000e-01 | 5.129000e-01 | 9.890400e-01 | ▇▅▃▂▂ |
| numeric | AF_reference | 93 | 0.9969348 | NA | NA | NA | NA | NA | 3.467371e-01 | 2.436786e-01 | 2.59580e-03 | 1.451680e-01 | 2.865420e-01 | 5.167730e-01 | 9.958070e-01 | ▇▆▃▂▂ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.426729e+04 | 2.567174e+00 | 2.42570e+04 | 2.426700e+04 | 2.426800e+04 | 2.426900e+04 | 2.426900e+04 | ▁▁▁▁▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 1135242 | rs9729550 | A | C | -0.1004840 | 0.0213296 | 0.0000025 | 0.0000025 | 0.25100 | 0.551917 | 24266 |
| 1 | 1140435 | rs1815606 | G | T | -0.0677437 | 0.0200188 | 0.0007151 | 0.0007144 | 0.30780 | 0.712061 | 24267 |
| 1 | 1163804 | rs7515488 | C | T | -0.1028080 | 0.0267243 | 0.0001195 | 0.0001196 | 0.14540 | 0.186901 | 24266 |
| 1 | 1165310 | rs11260562 | G | A | -0.0393647 | 0.0407840 | 0.3343998 | 0.3344449 | 0.05976 | 0.101837 | 24265 |
| 1 | 1173611 | rs6697886 | G | A | -0.1150740 | 0.0278495 | 0.0000360 | 0.0000360 | 0.12850 | 0.220647 | 24268 |
| 1 | 1186502 | rs6603785 | A | T | -0.0939811 | 0.0292685 | 0.0013210 | 0.0013227 | 0.11350 | 0.246206 | 24266 |
| 1 | 1194804 | rs11804831 | T | C | -0.0423857 | 0.0238793 | 0.0759294 | 0.0758983 | 0.19120 | 0.685903 | 24268 |
| 1 | 1218086 | rs6603788 | C | T | 0.0468836 | 0.0344479 | 0.1734998 | 0.1735136 | 0.08167 | 0.469449 | 24268 |
| 1 | 1233941 | rs1739855 | T | C | -0.0154183 | 0.0343314 | 0.6533005 | 0.6533581 | 0.08267 | 0.496805 | 24268 |
| 1 | 1241529 | rs1536168 | A | G | 0.0094445 | 0.0420501 | 0.8223000 | 0.8222903 | 0.95518 | 0.875200 | 24269 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 50351977 | rs28681372 | G | A | 0.0321101 | 0.0188218 | 0.0880704 | 0.0880070 | 0.59960 | 0.582268 | 24268 |
| 22 | 50470516 | rs11101958 | C | T | 0.0372958 | 0.0245367 | 0.1285000 | 0.1285108 | 0.20420 | 0.223642 | 24259 |
| 22 | 50474943 | rs1010282 | G | A | 0.0401818 | 0.0250823 | 0.1092001 | 0.1091560 | 0.20020 | 0.223842 | 24269 |
| 22 | 50704661 | rs2076139 | T | C | 0.0387408 | 0.0219744 | 0.0779202 | 0.0779010 | 0.74400 | 0.686901 | 24265 |
| 22 | 50947611 | rs6010121 | A | G | 0.0089597 | 0.0536833 | 0.8674000 | 0.8674488 | 0.03187 | 0.144569 | 24269 |
| 22 | 51078251 | rs4040041 | C | T | 0.0009995 | 0.0133748 | 0.9404000 | 0.9404295 | 0.39340 | 0.466653 | 24267 |
| 22 | 51094926 | rs9616810 | C | T | -0.0306654 | 0.0226815 | 0.1764002 | 0.1763751 | 0.22410 | 0.222444 | 24269 |
| 22 | 51105556 | rs9616812 | C | T | 0.0168571 | 0.0190864 | 0.3771004 | 0.3771285 | 0.49000 | 0.362819 | 24269 |
| 22 | 51109992 | rs9628185 | T | C | 0.0158733 | 0.0182683 | 0.3849001 | 0.3849026 | 0.49200 | 0.405351 | 24269 |
| 22 | 51156666 | rs9628187 | C | T | 0.0324672 | 0.0224066 | 0.1472001 | 0.1473371 | 0.20120 | 0.129992 | 24268 |
bcf preview
1 1135242 rs9729550 A C . PASS AF=0.251 ES:SE:LP:AF:SS:ID -0.100484:0.0213296:5.60818:0.251:24266:rs9729550
1 1140435 rs1815606 G T . PASS AF=0.3078 ES:SE:LP:AF:SS:ID -0.0677437:0.0200188:3.14563:0.3078:24267:rs1815606
1 1163804 rs7515488 C T . PASS AF=0.1454 ES:SE:LP:AF:SS:ID -0.102808:0.0267243:3.92263:0.1454:24266:rs7515488
1 1165310 rs11260562 G A . PASS AF=0.05976 ES:SE:LP:AF:SS:ID -0.0393647:0.040784:0.475734:0.05976:24265:rs11260562
1 1173611 rs6697886 G A . PASS AF=0.1285 ES:SE:LP:AF:SS:ID -0.115074:0.0278495:4.44406:0.1285:24268:rs6697886
1 1186502 rs6603785 A T . PASS AF=0.1135 ES:SE:LP:AF:SS:ID -0.0939811:0.0292685:2.8791:0.1135:24266:rs6603785
1 1194804 rs11804831 T C . PASS AF=0.1912 ES:SE:LP:AF:SS:ID -0.0423857:0.0238793:1.11959:0.1912:24268:rs11804831
1 1218086 rs6603788 C T . PASS AF=0.08167 ES:SE:LP:AF:SS:ID 0.0468836:0.0344479:0.760701:0.08167:24268:rs6603788
1 1233941 rs1739855 T C . PASS AF=0.08267 ES:SE:LP:AF:SS:ID -0.0154183:0.0343314:0.184887:0.08267:24268:rs1739855
1 1241529 rs1536168 A G . PASS AF=0.95518 ES:SE:LP:AF:SS:ID 0.00944446:0.0420501:0.0849697:0.95518:24269:rs1536168
1 1247494 rs12103 T C . PASS AF=0.8127 ES:SE:LP:AF:SS:ID 0.0228593:0.0236688:0.475994:0.8127:24261:rs12103
1 1249187 rs12142199 G A . PASS AF=0.8058 ES:SE:LP:AF:SS:ID 0.0196926:0.0231651:0.403073:0.8058:24265:rs12142199
1 1335790 rs1240708 A G . PASS AF=0.1813 ES:SE:LP:AF:SS:ID -0.0234734:0.0241495:0.480041:0.1813:24269:rs1240708
1 1611995 rs4074196 A G . PASS AF=0.4462 ES:SE:LP:AF:SS:ID -0.0136933:0.0184845:0.338377:0.4462:24259:rs4074196
1 1706160 rs7531583 A G . PASS AF=0.7361 ES:SE:LP:AF:SS:ID -0.0188218:0.0218553:0.409939:0.7361:24269:rs7531583
1 1721479 rs2272908 C T . PASS AF=0.505 ES:SE:LP:AF:SS:ID -0.0154183:0.0185182:0.392438:0.505:24269:rs2272908
1 1723031 rs9660180 G A . PASS AF=0.503 ES:SE:LP:AF:SS:ID -0.0138961:0.0184985:0.344381:0.503:24267:rs9660180
1 1781220 rs6681938 T C . PASS AF=0.3038 ES:SE:LP:AF:SS:ID -0.00601807:0.0201408:0.116282:0.3038:24268:rs6681938
1 1838516 rs2377037 C A . PASS AF=0.2281 ES:SE:LP:AF:SS:ID -0.0161294:0.0208336:0.357733:0.2281:24266:rs2377037
1 1871337 rs16824543 G A . PASS AF=0.04183 ES:SE:LP:AF:SS:ID -0.0368715:0.0454754:0.379344:0.04183:24269:rs16824543
1 1873625 rs12758705 G A . PASS AF=0.2331 ES:SE:LP:AF:SS:ID -0.00110061:0.020465:0.0190427:0.2331:24269:rs12758705
1 1881070 rs4648596 G A . PASS AF=0.0498 ES:SE:LP:AF:SS:ID -0.00581689:0.047215:0.0447935:0.0498:24269:rs4648596
1 2146966 rs7512482 T C . PASS AF=0.1663 ES:SE:LP:AF:SS:ID 0.0148886:0.0251242:0.256961:0.1663:24259:rs7512482
1 2229478 rs12562937 C T . PASS AF=0.2052 ES:SE:LP:AF:SS:ID 0.0168571:0.0231014:0.33208:0.2052:24269:rs12562937
1 2283896 rs2840528 A G . PASS AF=0.4253 ES:SE:LP:AF:SS:ID -0.0349021:0.0188151:1.19613:0.4253:24259:rs2840528
1 2444414 rs7535528 G A . PASS AF=0.3875 ES:SE:LP:AF:SS:ID 0.0487902:0.0193843:1.92628:0.3875:24266:rs7535528
1 2524915 rs10752747 G T . PASS AF=0.3088 ES:SE:LP:AF:SS:ID -0.116197:0.0198763:8.29688:0.3088:24265:rs10752747
1 2860931 rs2925499 C T . PASS AF=0.5458 ES:SE:LP:AF:SS:ID 0.0124775:0.0186343:0.298346:0.5458:24269:rs2925499
1 2883858 rs2485944 C T . PASS AF=0.1653 ES:SE:LP:AF:SS:ID -0.00823381:0.0238592:0.136677:0.1653:24269:rs2485944
1 2931327 rs6691208 C A . PASS AF=0.1076 ES:SE:LP:AF:SS:ID -0.020713:0.0285855:0.329105:0.1076:24269:rs6691208
1 3020246 rs2993493 C A . PASS AF=0.1524 ES:SE:LP:AF:SS:ID 0.0198026:0.0282129:0.316323:0.1524:24269:rs2993493
1 3080940 rs1736522 C G . PASS AF=0.4751 ES:SE:LP:AF:SS:ID 0.0160278:0.0184907:0.4133:0.4751:24264:rs1736522
1 3111669 rs12094678 G A . PASS AF=0.1843 ES:SE:LP:AF:SS:ID -0.0036065:0.0250799:0.0527134:0.1843:24268:rs12094678
1 3177480 rs3002685 A G . PASS AF=0.1823 ES:SE:LP:AF:SS:ID 0.0430595:0.0239886:1.139:0.1823:24269:rs3002685
1 3320064 rs6669407 A G . PASS AF=0.6564 ES:SE:LP:AF:SS:ID 0.0403013:0.0194317:1.41953:0.6564:24267:rs6669407
1 3342530 rs2244013 G A . PASS AF=0.2629 ES:SE:LP:AF:SS:ID -0.0337636:0.0208933:0.973875:0.2629:24269:rs2244013
1 3394250 rs10909948 C T . PASS AF=0.8645 ES:SE:LP:AF:SS:ID 0.0281937:0.027668:0.511308:0.8645:24269:rs10909948
1 3441382 rs1896 C T . PASS AF=0.3586 ES:SE:LP:AF:SS:ID 0.0344014:0.019392:1.11844:0.3586:24268:rs1896
1 3512341 rs2794327 C T . PASS AF=0.6524 ES:SE:LP:AF:SS:ID 0.00893984:0.0194641:0.189767:0.6524:24269:rs2794327
1 3801973 rs7551237 T C . PASS AF=0.1604 ES:SE:LP:AF:SS:ID 0.00796817:0.0255063:0.122168:0.1604:24269:rs7551237
1 3822703 rs10909830 C T . PASS AF=0.3078 ES:SE:LP:AF:SS:ID 0.00697561:0.0201899:0.136856:0.3078:24265:rs10909830
1 4089259 rs12062024 T A . PASS AF=0.1633 ES:SE:LP:AF:SS:ID -0.00662188:0.0262773:0.0963133:0.1633:24267:rs12062024
1 4089613 rs12080516 C T . PASS AF=0.1633 ES:SE:LP:AF:SS:ID -0.00652122:0.0261162:0.0953385:0.1633:24268:rs12080516
1 4120311 rs7514530 C T . PASS AF=0.2769 ES:SE:LP:AF:SS:ID -0.0139975:0.0205997:0.303818:0.2769:24269:rs7514530
1 4120987 rs10915372 C T . PASS AF=0.2769 ES:SE:LP:AF:SS:ID -0.0140989:0.0206336:0.305922:0.2769:24268:rs10915372
1 4121494 rs7556284 G A . PASS AF=0.2769 ES:SE:LP:AF:SS:ID -0.0139975:0.0206697:0.302509:0.2769:24269:rs7556284
1 4121584 rs7524800 A G . PASS AF=0.2769 ES:SE:LP:AF:SS:ID -0.0133892:0.0206369:0.28693:0.2769:24268:rs7524800
1 4121653 rs7556385 G A . PASS AF=0.2779 ES:SE:LP:AF:SS:ID -0.0139975:0.0206911:0.302161:0.2779:24269:rs7556385
1 4121812 rs7520448 C T . PASS AF=0.2769 ES:SE:LP:AF:SS:ID -0.0128826:0.0207116:0.27254:0.2769:24269:rs7520448
1 4133241 rs12021796 T G . PASS AF=0.242 ES:SE:LP:AF:SS:ID -0.0201007:0.0220984:0.439974:0.242:24267:rs12021796