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/0751d5d2-73a8-4032-8b22-a60b9569a3c0/call-vcf/inputs/-261022249/upload.txt.gz --id ieu-b-5075 --json /data/cromwell-executions/qc/0751d5d2-73a8-4032-8b22-a60b9569a3c0/call-vcf/inputs/-261022249/ieu-b-5075_data.json --ref /data/cromwell-executions/qc/0751d5d2-73a8-4032-8b22-a60b9569a3c0/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/0751d5d2-73a8-4032-8b22-a60b9569a3c0/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-5075/ieu-b-5075.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/0751d5d2-73a8-4032-8b22-a60b9569a3c0/call-ldsc/inputs/-261022249/ieu-b-5075.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-5075/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Thu Jun 30 20:10:06 2022
Reading summary statistics from /data/cromwell-executions/qc/0751d5d2-73a8-4032-8b22-a60b9569a3c0/call-ldsc/inputs/-261022249/ieu-b-5075.vcf.gz ...
Read summary statistics for 0 SNPs.
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.
Traceback (most recent call last):
File "./ldsc/ldsc.py", line 647, in <module>
sumstats.estimate_h2(args, log)
File "/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
args, log, args.h2)
File "/ldsc/ldscore/sumstats.py", line 252, in _read_ld_sumstats
sumstats = _merge_and_log(ref_ld, sumstats, 'reference panel LD', log)
File "/ldsc/ldscore/sumstats.py", line 238, in _merge_and_log
raise ValueError(msg.format(N=len(sumstats), F=noun))
ValueError: After merging with reference panel LD, 0 SNPs remain.
Analysis finished at Thu Jun 30 20:11:17 2022
Total time elapsed: 1.0m:10.84sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9284,
"inflation_factor": 1.0966,
"mean_EFFECT": "NaN",
"n": "-Inf",
"n_snps": 13230376,
"n_clumped_hits": 38,
"n_p_sig": 2691,
"n_mono": 40913,
"n_ns": 894881,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 2665305,
"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": 0,
"ldsc_nsnp_merge_regression_ld": "NA",
"ldsc_observed_scale_h2_beta": "NA",
"ldsc_observed_scale_h2_se": "NA",
"ldsc_intercept_beta": "NA",
"ldsc_intercept_se": "NA",
"ldsc_lambda_gc": "NA",
"ldsc_mean_chisq": "NA",
"ldsc_ratio": "NA"
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | TRUE |
| is_snpid_non_unique | TRUE |
| mean_EFFECT_nonfinite | TRUE |
| mean_EFFECT_05 | NA |
| mean_EFFECT_01 | NA |
| mean_chisq | NA |
| n_p_sig | TRUE |
| miss_EFFECT | FALSE |
| miss_SE | FALSE |
| miss_PVAL | FALSE |
| ldsc_ratio | NA |
| ldsc_intercept_beta | NA |
| 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 | 560299 | 0.9576506 | 3 | 12 | 0 | 12658040 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 101 | 0 | 16389 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 72474 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 13230376 | 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 | 8.433292e+00 | 5.628473e+00 | 1.0000e+00 | 4.000000e+00 | 7.000000e+00 | 1.200000e+01 | 22 | ▇▅▃▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.981471e+07 | 5.518843e+07 | 3.0200e+02 | 3.495929e+07 | 7.113922e+07 | 1.142961e+08 | 249220724 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | NaN | NaN | -Inf | -7.803400e-03 | 4.700000e-06 | 7.935200e-03 | Inf | ▁▁▁▁▇ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | Inf | NaN | 3.3088e-03 | 4.369100e-03 | 1.259540e-02 | 4.298200e-02 | Inf | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.835682e-01 | 2.954233e-01 | 0.0000e+00 | 2.200002e-01 | 4.799997e-01 | 7.400005e-01 | 1 | ▇▇▇▆▇ |
| numeric | PVAL_ztest | 7894 | 0.9994033 | NA | NA | NA | NA | NA | NA | NA | 4.832596e-01 | 2.952154e-01 | 0.0000e+00 | 2.229661e-01 | 4.774446e-01 | 7.391359e-01 | 1 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.027235e-01 | 2.963692e-01 | 0.0000e+00 | 2.022000e-03 | 2.945300e-02 | 3.139020e-01 | 1 | ▇▁▁▁▁ |
| numeric | AF_reference | 2665305 | 0.7985465 | NA | NA | NA | NA | NA | NA | NA | 1.830341e-01 | 2.405877e-01 | 0.0000e+00 | 9.984000e-04 | 6.789140e-02 | 2.921330e-01 | 1 | ▇▂▁▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 751343 | rs28544273 | T | A | 0.0031688 | 0.0049099 | 0.5199996 | 0.5186729 | 0.148354 | 0.242612 | NA |
| 1 | 751756 | rs143225517 | T | C | 0.0031629 | 0.0048984 | 0.5199996 | 0.5184738 | 0.147893 | 0.242212 | NA |
| 1 | 752566 | rs3094315 | G | A | -0.0031615 | 0.0045368 | 0.4899999 | 0.4858850 | 0.842014 | 0.718251 | NA |
| 1 | 752894 | rs3131971 | T | C | -0.0034300 | 0.0047762 | 0.4700002 | 0.4726631 | 0.848967 | 0.753195 | NA |
| 1 | 753405 | rs3115860 | C | A | -0.0033657 | 0.0048640 | 0.4899999 | 0.4889655 | 0.850825 | 0.751797 | NA |
| 1 | 753425 | rs3131970 | T | C | -0.0033532 | 0.0048438 | 0.4899999 | 0.4887652 | 0.850164 | 0.749002 | NA |
| 1 | 756285 | rs1557551112 | A | ATCCACCCTGTCTACACTACCTGCTTGTCCAGCAGG | -0.0023096 | 0.0051727 | 0.6600001 | 0.6552401 | 0.858298 | NA | NA |
| 1 | 759293 | rs10157329 | T | A | 0.0042499 | 0.0057653 | 0.4600002 | 0.4610280 | 0.123358 | 0.154153 | NA |
| 1 | 759700 | rs989694037 | T | C | -0.0031147 | 0.0047609 | 0.5099998 | 0.5129673 | 0.845138 | NA | NA |
| 1 | 759837 | rs114111569 | T | A | -0.0030570 | 0.0049146 | 0.5300002 | 0.5339297 | 0.850181 | 0.752596 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51185302 | rs540965397 | C | T | 0.0035066 | 0.0119313 | 0.7700005 | 0.7688362 | 0.026177 | 0.0017971 | NA |
| 22 | 51186143 | rs2879914 | T | C | 0.0072344 | 0.0041162 | 0.0790005 | 0.0788259 | 0.330104 | 0.2733630 | NA |
| 22 | 51186228 | rs3865766 | C | T | 0.0069020 | 0.0040942 | 0.0920005 | 0.0918295 | 0.349963 | 0.4532750 | NA |
| 22 | 51188607 | rs184876585 | G | C | 0.0157066 | 0.0281506 | 0.5800000 | 0.5768792 | 0.004566 | 0.0013978 | NA |
| 22 | 51188757 | NA | T | G | 0.0383132 | 0.0600256 | 0.5199996 | 0.5232908 | 0.000953 | NA | NA |
| 22 | 51190830 | rs149425561 | T | G | 0.0101593 | 0.0045126 | 0.0239999 | 0.0243651 | 0.238521 | 0.1429710 | NA |
| 22 | 51192518 | rs5771005 | C | G | 0.0102549 | 0.0043128 | 0.0170000 | 0.0174171 | 0.304950 | 0.2398160 | NA |
| 22 | 51194097 | rs1313596790 | G | A | -0.0005863 | 0.0224627 | 0.9800000 | 0.9791756 | 0.006720 | NA | NA |
| 22 | 51194988 | rs565867875 | G | C | 0.0188266 | 0.0150534 | 0.2099999 | 0.2110606 | 0.017670 | 0.0005990 | NA |
| 22 | 51196592 | NA | T | C | 0.0882257 | 0.0741956 | 0.2300001 | 0.2344018 | 0.000624 | NA | NA |
bcf preview
1 751343 rs28544273 T A . PASS AF=0.148354 ES:SE:LP:AF:ID 0.00316878:0.00490985:0.283997:0.148354:rs28544273
1 751756 rs28527770 T C . PASS AF=0.147893 ES:SE:LP:AF:ID 0.00316287:0.00489836:0.283997:0.147893:rs28527770
1 752566 rs3094315 G A . PASS AF=0.842014 ES:SE:LP:AF:ID -0.00316154:0.00453678:0.309804:0.842014:rs3094315
1 752894 rs3131971 T C . PASS AF=0.848967 ES:SE:LP:AF:ID -0.00343002:0.00477617:0.327902:0.848967:rs3131971
1 753405 rs3115860 C A . PASS AF=0.850825 ES:SE:LP:AF:ID -0.00336567:0.004864:0.309804:0.850825:rs3115860
1 753425 rs1431026348 T C . PASS AF=0.850164 ES:SE:LP:AF:ID -0.00335321:0.00484376:0.309804:0.850164:rs1431026348
1 756285 rs1557551112 A ATCCACCCTGTCTACACTACCTGCTTGTCCAGCAGG . PASS AF=0.858298 ES:SE:LP:AF:ID -0.0023096:0.00517274:0.180456:0.858298:rs1557551112
1 759293 rs10157329 T A . PASS AF=0.123358 ES:SE:LP:AF:ID 0.00424995:0.00576534:0.337242:0.123358:rs10157329
1 759700 rs989694037 T C . PASS AF=0.845138 ES:SE:LP:AF:ID -0.00311469:0.00476089:0.29243:0.845138:rs989694037
1 759837 rs3115851 T A . PASS AF=0.850181 ES:SE:LP:AF:ID -0.00305696:0.00491458:0.275724:0.850181:rs3115851
1 760912 rs1048488 C T . PASS AF=0.843753 ES:SE:LP:AF:ID -0.00311896:0.00477072:0.29243:0.843753:rs1048488
1 761147 rs3115850 T C . PASS AF=0.843462 ES:SE:LP:AF:ID -0.00311727:0.00477238:0.29243:0.843462:rs3115850
1 761752 rs1057213 C T . PASS AF=0.848593 ES:SE:LP:AF:ID -0.00310384:0.0049293:0.275724:0.848593:rs1057213
1 762273 rs3115849 G A . PASS AF=0.847476 ES:SE:LP:AF:ID -0.00300414:0.00509052:0.251812:0.847476:rs3115849
1 762589 rs772021405 G C . PASS AF=0.854038 ES:SE:LP:AF:ID -0.00305573:0.00514589:0.259637:0.854038:rs772021405
1 762592 rs1209077270 C G . PASS AF=0.854032 ES:SE:LP:AF:ID -0.00305854:0.00514668:0.259637:0.854032:rs1209077270
1 762601 rs3131949 T C . PASS AF=0.85412 ES:SE:LP:AF:ID -0.00308901:0.00514698:0.259637:0.85412:rs3131949
1 762632 rs3131948 T A . PASS AF=0.854337 ES:SE:LP:AF:ID -0.00307813:0.00514716:0.259637:0.854337:rs3131948
1 764191 rs7515915 T G . PASS AF=0.139424 ES:SE:LP:AF:ID 0.00301351:0.0053112:0.244125:0.139424:rs7515915
1 769138 rs1483790918 C CAT . PASS AF=0.856446 ES:SE:LP:AF:ID -0.00316943:0.00541123:0.251812:0.856446:rs1483790918
1 769223 rs60320384 C G . PASS AF=0.134708 ES:SE:LP:AF:ID 0.00310752:0.00561676:0.236572:0.134708:rs60320384
1 771823 rs2977605 T C . PASS AF=0.858389 ES:SE:LP:AF:ID -0.00249912:0.00545402:0.187087:0.858389:rs2977605
1 771967 rs59066358 G A . PASS AF=0.13196 ES:SE:LP:AF:ID 0.00254566:0.00572603:0.180456:0.13196:rs59066358
1 772755 rs2905039 A C . PASS AF=0.859553 ES:SE:LP:AF:ID -0.00257064:0.00551583:0.19382:0.859553:rs2905039
1 775181 rs61768182 A G . PASS AF=0.142837 ES:SE:LP:AF:ID 0.00304442:0.00548831:0.236572:0.142837:rs61768182
1 775659 rs2905035 A G . PASS AF=0.850861 ES:SE:LP:AF:ID -0.0030323:0.00535349:0.244125:0.850861:rs2905035
1 777122 rs2980319 A T . PASS AF=0.851949 ES:SE:LP:AF:ID -0.00281382:0.00540882:0.221849:0.851949:rs2980319
1 799276 rs1361372105 G A . PASS AF=0.012452 ES:SE:LP:AF:ID -0.0354733:0.0176064:1.35655:0.012452:rs1361372105
1 842685 rs145037928 T C . PASS AF=0.018247 ES:SE:LP:AF:ID 0.00750215:0.0147138:0.21467:0.018247:rs145037928
1 843309 rs535993749 C T . PASS AF=0.006923 ES:SE:LP:AF:ID -0.016806:0.0237238:0.318759:0.006923:rs535993749
1 845635 rs117086422 C T . PASS AF=0.142323 ES:SE:LP:AF:ID 0.00232962:0.00503104:0.19382:0.142323:rs117086422
1 846078 rs778265812 C T . PASS AF=0.142464 ES:SE:LP:AF:ID 0.00251135:0.00499089:0.21467:0.142464:rs778265812
1 846808 rs4475691 C T . PASS AF=0.141282 ES:SE:LP:AF:ID 0.00156465:0.00476349:0.130768:0.141282:rs4475691
1 846864 rs1269142199 G C . PASS AF=0.140458 ES:SE:LP:AF:ID 0.00165801:0.0048048:0.136677:0.140458:rs1269142199
1 847228 rs3905286 C T . PASS AF=0.141816 ES:SE:LP:AF:ID 0.00200261:0.00488055:0.167491:0.141816:rs3905286
1 847491 rs1158719307 G A . PASS AF=0.1426 ES:SE:LP:AF:ID 0.00200077:0.00488243:0.167491:0.1426:rs1158719307
1 848090 rs4246505 G A . PASS AF=0.137204 ES:SE:LP:AF:ID 0.00274791:0.00497506:0.236572:0.137204:rs4246505
1 848445 rs1156895099 G A . PASS AF=0.143191 ES:SE:LP:AF:ID 0.00200116:0.00489754:0.167491:0.143191:rs1156895099
1 848456 rs11507767 A G . PASS AF=0.143198 ES:SE:LP:AF:ID 0.00195082:0.00490316:0.161151:0.143198:rs11507767
1 848654 rs5772026 T TG . PASS AF=0.862642 ES:SE:LP:AF:ID -0.00222122:0.00496415:0.187087:0.862642:rs5772026
1 848738 rs3829741 C T . PASS AF=0.138224 ES:SE:LP:AF:ID 0.00215077:0.00494706:0.180456:0.138224:rs3829741
1 848828 rs3841265 G GA . PASS AF=0.847235 ES:SE:LP:AF:ID 0.00735286:0.00536038:0.769551:0.847235:rs3841265
1 849440 rs79376265 C T . PASS AF=0.147175 ES:SE:LP:AF:ID -0.00706756:0.00533093:0.744727:0.147175:rs79376265
1 850062 rs28723578 A T . PASS AF=0.143459 ES:SE:LP:AF:ID 0.00205096:0.00491584:0.167491:0.143459:rs28723578
1 850123 rs28622257 C T . PASS AF=0.138997 ES:SE:LP:AF:ID 0.00221507:0.00496583:0.180456:0.138997:rs28622257
1 850528 rs114889920 A G . PASS AF=0.147475 ES:SE:LP:AF:ID -0.00697616:0.00528836:0.721246:0.147475:rs114889920
1 851190 rs28609852 G A . PASS AF=0.142841 ES:SE:LP:AF:ID 0.00213126:0.00494113:0.173925:0.142841:rs28609852
1 851198 rs146517096 G A . PASS AF=0.007215 ES:SE:LP:AF:ID 0.00410939:0.023162:0.0655015:0.007215:rs146517096
1 851204 rs28552953 G C . PASS AF=0.146125 ES:SE:LP:AF:ID 0.00212956:0.00495401:0.173925:0.146125:rs28552953
1 852664 rs28605311 C T . PASS AF=0.140178 ES:SE:LP:AF:ID 0.00228631:0.00498338:0.187087:0.140178:rs28605311