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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"Gwas2VCF_command": "--data /data/cromwell-executions/qc/0e008373-d7ee-4076-8058-9ba83a48dcd8/call-vcf/inputs/-261044538/upload.txt.gz --id ieu-b-4815 --json /data/cromwell-executions/qc/0e008373-d7ee-4076-8058-9ba83a48dcd8/call-vcf/inputs/-261044538/ieu-b-4815_data.json --ref /data/cromwell-executions/qc/0e008373-d7ee-4076-8058-9ba83a48dcd8/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/0e008373-d7ee-4076-8058-9ba83a48dcd8/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-4815/ieu-b-4815.vcf.gz --alias alias.txt; 1.3.0",
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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 /data/cromwell-executions/qc/0e008373-d7ee-4076-8058-9ba83a48dcd8/call-ldsc/inputs/-261044538/ieu-b-4815.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4815/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Wed Jan 5 04:59:44 2022
Reading summary statistics from /data/cromwell-executions/qc/0e008373-d7ee-4076-8058-9ba83a48dcd8/call-ldsc/inputs/-261044538/ieu-b-4815.vcf.gz ...
Read summary statistics for 7191573 SNPs.
Dropped 19717 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1199274 SNPs remain.
After merging with regression SNP LD, 1199274 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1957 (0.0145)
Lambda GC: 1.1754
Mean Chi^2: 1.2098
Intercept: 1.0173 (0.0079)
Ratio: 0.0826 (0.0375)
Analysis finished at Wed Jan 5 05:01:23 2022
Total time elapsed: 1.0m:39.17sQC metrics
Metrics
Metrics
{
"af_correlation": "NA",
"inflation_factor": 1.1494,
"mean_EFFECT": -0.0002,
"n": 51852,
"n_snps": 7191598,
"n_clumped_hits": 11,
"n_p_sig": 771,
"n_mono": 0,
"n_ns": 0,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 7191598,
"n_miss_AF_reference": 46780,
"n_est": "NA",
"ratio_se_n": "NA",
"mean_diff": "NaN",
"ratio_diff": "NaN",
"sd_y_est1": "NaN",
"sd_y_est2": "NA",
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 1199274,
"ldsc_nsnp_merge_regression_ld": 1199274,
"ldsc_observed_scale_h2_beta": 0.1957,
"ldsc_observed_scale_h2_se": 0.0145,
"ldsc_intercept_beta": 1.0173,
"ldsc_intercept_se": 0.0079,
"ldsc_lambda_gc": 1.1754,
"ldsc_mean_chisq": 1.2098,
"ldsc_ratio": 0.0825
}
Flags
| name | value |
|---|---|
| af_correlation | NA |
| inflation_factor | FALSE |
| n | FALSE |
| is_snpid_non_unique | TRUE |
| 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 | 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 | logical.mean | logical.count | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| character | ID | 8 | 0.9999989 | 3 | 58 | 0 | 7191573 | 0 | NA | NA | 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 | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | AF | 7191598 | 0.0000000 | NA | NA | NA | NA | NA | NaN | : | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.631819e+00 | 5.745131e+00 | 1.000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.892427e+07 | 5.636321e+07 | 8.280e+02 | 3.248775e+07 | 6.955367e+07 | 1.147668e+08 | 2.492223e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.781000e-04 | 6.506610e-02 | -8.122e-01 | -3.230000e-02 | 0.000000e+00 | 3.190000e-02 | 7.185000e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 5.379030e-02 | 3.118810e-02 | 2.370e-02 | 3.060000e-02 | 3.990000e-02 | 6.680000e-02 | 1.969000e-01 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.770810e-01 | 2.950111e-01 | 0.000e+00 | 2.156001e-01 | 4.695999e-01 | 7.322999e-01 | 1.000000e+00 | ▇▇▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.770808e-01 | 2.950118e-01 | 0.000e+00 | 2.155551e-01 | 4.696326e-01 | 7.323234e-01 | 1.000000e+00 | ▇▇▆▆▆ |
| numeric | AF_reference | 46780 | 0.9934952 | NA | NA | NA | NA | NA | NA | NA | 2.661372e-01 | 2.522957e-01 | 1.997e-04 | 5.930510e-02 | 1.805110e-01 | 4.143370e-01 | 1.000000e+00 | ▇▃▂▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.765798e+04 | 4.791777e+03 | 2.845e+04 | 4.576400e+04 | 4.915100e+04 | 5.162600e+04 | 5.185200e+04 | ▁▁▂▂▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 768448 | rs12562034 | G | A | -0.0909 | 0.0627 | 0.1471001 | 0.1471252 | NA | 0.1918930 | 30540 |
| 1 | 777232 | rs112618790 | C | T | -0.1027 | 0.0652 | 0.1150000 | 0.1152210 | NA | 0.0668930 | 30540 |
| 1 | 791853 | rs6684487 | G | A | -0.1148 | 0.0653 | 0.0790806 | 0.0787407 | NA | 0.0762780 | 30540 |
| 1 | 794332 | rs12127425 | G | A | -0.1408 | 0.0718 | 0.0500899 | 0.0498787 | NA | 0.1162140 | 29926 |
| 1 | 796100 | rs12132398 | C | T | -0.1344 | 0.0713 | 0.0594306 | 0.0594308 | NA | 0.0856629 | 29926 |
| 1 | 797281 | rs76631953 | G | C | -0.1305 | 0.0712 | 0.0669607 | 0.0668226 | NA | 0.0656949 | 29926 |
| 1 | 797325 | rs111739932 | T | C | -0.1291 | 0.0712 | 0.0696803 | 0.0698006 | NA | 0.0680911 | 29926 |
| 1 | 797440 | rs58013264 | T | C | 0.0812 | 0.0457 | 0.0752593 | 0.0756003 | NA | 0.1894970 | 38123 |
| 1 | 798026 | rs4951864 | C | T | 0.1327 | 0.0697 | 0.0568801 | 0.0569266 | NA | 0.8941690 | 29921 |
| 1 | 798400 | rs10900604 | A | G | -0.0061 | 0.0375 | 0.8708000 | 0.8707809 | NA | 0.4105430 | 39179 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51196164 | rs8136603 | A | T | -0.0646 | 0.0773 | 0.4037997 | 0.4033209 | NA | 0.1427720 | 34282 |
| 22 | 51196296 | rs9616961 | G | C | 0.0152 | 0.0698 | 0.8279999 | 0.8276122 | NA | 0.0395367 | 31822 |
| 22 | 51197576 | rs147713773 | G | C | 0.0206 | 0.0702 | 0.7693997 | 0.7691803 | NA | 0.0471246 | 31822 |
| 22 | 51197602 | rs187225588 | T | A | -0.0681 | 0.0768 | 0.3753998 | 0.3752303 | NA | 0.0175719 | 35296 |
| 22 | 51198569 | rs142671391 | G | C | -0.0360 | 0.0815 | 0.6587005 | 0.6586934 | NA | 0.1110220 | 34282 |
| 22 | 51198906 | rs6010079 | G | A | 0.0100 | 0.0703 | 0.8864999 | 0.8868845 | NA | 0.0421326 | 31822 |
| 22 | 51202748 | rs9616963 | A | G | 0.0175 | 0.0700 | 0.8024999 | 0.8025873 | NA | 0.0391374 | 31822 |
| 22 | 51208568 | rs148425445 | G | T | -0.0590 | 0.0761 | 0.4380997 | 0.4381650 | NA | 0.1160140 | 35296 |
| 22 | 51216564 | rs9616970 | T | C | 0.0059 | 0.0532 | 0.9124000 | 0.9116939 | NA | 0.1563500 | 29573 |
| 22 | 51222100 | rs114553188 | G | T | -0.0474 | 0.0785 | 0.5462997 | 0.5459622 | NA | 0.0880591 | 35296 |
bcf preview
1 768448 rs12562034 G A . PASS . ES:SE:LP:SS:ID -0.0909:0.0627:0.832387:30540:rs12562034
1 777232 rs112618790 C T . PASS . ES:SE:LP:SS:ID -0.1027:0.0652:0.939302:30540:rs112618790
1 791853 rs6684487 G A . PASS . ES:SE:LP:SS:ID -0.1148:0.0653:1.10193:30540:rs6684487
1 794332 rs12127425 G A . PASS . ES:SE:LP:SS:ID -0.1408:0.0718:1.30025:29926:rs12127425
1 796100 rs12132398 C T . PASS . ES:SE:LP:SS:ID -0.1344:0.0713:1.22599:29926:rs12132398
1 797281 rs1347695410 G C . PASS . ES:SE:LP:SS:ID -0.1305:0.0712:1.17418:29926:rs1347695410
1 797325 rs1338750774 T C . PASS . ES:SE:LP:SS:ID -0.1291:0.0712:1.15689:29926:rs1338750774
1 797440 rs58013264 T C . PASS . ES:SE:LP:SS:ID 0.0812:0.0457:1.12344:38123:rs58013264
1 798026 rs4951864 C T . PASS . ES:SE:LP:SS:ID 0.1327:0.0697:1.24504:29921:rs4951864
1 798400 rs10900604 A G . PASS . ES:SE:LP:SS:ID -0.0061:0.0375:0.0600816:39179:rs10900604
1 798801 rs12132517 G A . PASS . ES:SE:LP:SS:ID -0.122:0.0712:1.06278:29926:rs12132517
1 798959 rs11240777 G A . PASS . ES:SE:LP:SS:ID -0.0014:0.0364:0.0135418:40774:rs11240777
1 799499 rs147634896 T C . PASS . ES:SE:LP:SS:ID -0.1257:0.0717:1.09871:29926:rs147634896
1 800383 rs4951931 C T . PASS . ES:SE:LP:SS:ID 0.1352:0.07:1.27295:30227:rs4951931
1 801467 rs61768212 G C . PASS . ES:SE:LP:SS:ID 0.0784:0.0458:1.06093:37810:rs61768212
1 801661 rs12132974 C T . PASS . ES:SE:LP:SS:ID -0.1344:0.0723:1.20018:29926:rs12132974
1 801680 rs12134490 A C . PASS . ES:SE:LP:SS:ID -0.1299:0.0723:1.13924:29926:rs12134490
1 801858 rs17276806 C T . PASS . ES:SE:LP:SS:ID -0.1298:0.0724:1.1368:29926:rs17276806
1 802856 rs139867617 C T . PASS . ES:SE:LP:SS:ID -0.126:0.0725:1.08635:29926:rs139867617
1 804759 rs7526310 C T . PASS . ES:SE:LP:SS:ID 0.0767:0.0458:1.02724:37810:rs7526310
1 808631 rs11240779 G A . PASS . ES:SE:LP:SS:ID -0.0398:0.0365:0.561458:38424:rs11240779
1 808928 rs1247187939 C T . PASS . ES:SE:LP:SS:ID -0.0445:0.0365:0.652865:38424:rs1247187939
1 833223 rs13303211 C T . PASS . ES:SE:LP:SS:ID 0.0092:0.0453:0.0759793:30540:rs13303211
1 833302 rs28752186 C T . PASS . ES:SE:LP:SS:ID 0.0088:0.0453:0.0726296:30540:rs28752186
1 833824 rs28484835 T C . PASS . ES:SE:LP:SS:ID 0.0091:0.0453:0.075204:30540:rs28484835
1 833927 rs28593608 T C . PASS . ES:SE:LP:SS:ID 0.0225:0.047:0.199146:30766:rs28593608
1 834198 rs28385272 T C . PASS . ES:SE:LP:SS:ID 0.0219:0.047:0.192803:30766:rs28385272
1 834832 rs796468152 G C . PASS . ES:SE:LP:SS:ID 0.0077:0.0453:0.0631345:30540:rs796468152
1 834928 rs4422949 A G . PASS . ES:SE:LP:SS:ID 0.0193:0.047:0.16647:30766:rs4422949
1 834999 rs28570054 G A . PASS . ES:SE:LP:SS:ID 0.0206:0.047:0.179864:30766:rs28570054
1 835499 rs4422948 A G . PASS . ES:SE:LP:SS:ID 0.0034:0.0452:0.0266874:30540:rs4422948
1 836529 rs1192410597 C G . PASS . ES:SE:LP:SS:ID 0.0174:0.0472:0.14685:30540:rs1192410597
1 836896 rs28705752 T C . PASS . ES:SE:LP:SS:ID 0.0165:0.0433:0.153354:30766:rs28705752
1 836924 rs72890788 G A . PASS . ES:SE:LP:SS:ID 0.0105:0.047:0.0848641:30766:rs72890788
1 838387 rs4970384 T C . PASS . ES:SE:LP:SS:ID 0.002:0.0471:0.0153377:30766:rs4970384
1 838555 rs4970383 C A . PASS . ES:SE:LP:SS:ID 0.0189:0.0446:0.172308:30766:rs4970383
1 839103 rs28562941 A G . PASS . ES:SE:LP:SS:ID 0.0244:0.0432:0.242604:30766:rs28562941
1 841085 rs1264290483 C G . PASS . ES:SE:LP:SS:ID 0.0319:0.0455:0.315783:30540:rs1264290483
1 842013 rs1191510089 T G . PASS . ES:SE:LP:SS:ID 0.0028:0.0471:0.0207249:30766:rs1191510089
1 845635 rs117086422 C T . PASS . ES:SE:LP:SS:ID 0.0429:0.0367:0.61493:45093:rs117086422
1 845938 rs57760052 G A . PASS . ES:SE:LP:SS:ID 0.0338:0.0365:0.451365:45093:rs57760052
1 846078 rs778265812 C T . PASS . ES:SE:LP:SS:ID 0.008:0.0377:0.0802422:45093:rs778265812
1 846398 rs58781670 G A . PASS . ES:SE:LP:SS:ID 0.0364:0.037:0.486916:45093:rs58781670
1 846465 rs60454217 C T . PASS . ES:SE:LP:SS:ID 0.2291:0.115:1.33273:41025:rs60454217
1 846543 rs79396034 G T . PASS . ES:SE:LP:SS:ID 0.3015:0.1225:1.85981:36561:rs79396034
1 846808 rs4475691 C T . PASS . ES:SE:LP:SS:ID 0.0041:0.0376:0.0394817:45093:rs4475691
1 846864 rs1269142199 G C . PASS . ES:SE:LP:SS:ID 0.0039:0.0377:0.037536:44867:rs1269142199
1 847228 rs3905286 C T . PASS . ES:SE:LP:SS:ID 0.0125:0.0372:0.133122:45093:rs3905286
1 847491 rs1158719307 G A . PASS . ES:SE:LP:SS:ID 0.0063:0.0368:0.0630341:45093:rs1158719307
1 848090 rs4246505 G A . PASS . ES:SE:LP:SS:ID 0.009:0.0368:0.093665:45093:rs4246505