Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std plot

beta_std_plot

beta_std_plot

Metadata

{
    "fileformat": "VCFv4.2",
    "FILTER": "<ID=PASS,Description=\"All filters passed\">",
    "INFO": "<ID=AF,Number=A,Type=Float,Description=\"Allele Frequency\">",
    "FORMAT": "<ID=ES,Number=A,Type=Float,Description=\"Effect size estimate relative to the alternative allele\">",
    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
    "FORMAT.2": "<ID=LP,Number=A,Type=Float,Description=\"-log10 p-value for effect estimate\">",
    "FORMAT.3": "<ID=AF,Number=A,Type=Float,Description=\"Alternate allele frequency in the association study\">",
    "FORMAT.4": "<ID=SS,Number=A,Type=Float,Description=\"Sample size used to estimate genetic effect\">",
    "FORMAT.5": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
    "FORMAT.6": "<ID=SI,Number=A,Type=Float,Description=\"Accuracy score of summary data imputation\">",
    "FORMAT.7": "<ID=NC,Number=A,Type=Float,Description=\"Number of cases used to estimate genetic effect\">",
    "FORMAT.8": "<ID=ID,Number=1,Type=String,Description=\"Study variant identifier\">",
    "META": "<ID=TotalVariants,Number=1,Type=Integer,Description=\"Total number of variants in input\">",
    "META.1": "<ID=VariantsNotRead,Number=1,Type=Integer,Description=\"Number of variants that could not be read\">",
    "META.2": "<ID=HarmonisedVariants,Number=1,Type=Integer,Description=\"Total number of harmonised variants\">",
    "META.3": "<ID=VariantsNotHarmonised,Number=1,Type=Integer,Description=\"Total number of variants that could not be harmonised\">",
    "META.4": "<ID=SwitchedAlleles,Number=1,Type=Integer,Description=\"Total number of variants strand switched\">",
    "META.5": "<ID=TotalControls,Number=1,Type=Integer,Description=\"Total number of controls in the association study\">",
    "META.6": "<ID=TotalCases,Number=1,Type=Integer,Description=\"Total number of cases in the association study\">",
    "META.7": "<ID=StudyType,Number=1,Type=String,Description=\"Type of GWAS study [Continuous or CaseControl]\">",
    "SAMPLE": "<ID=UKB-b:837,TotalVariants=9851866,VariantsNotRead=0,HarmonisedVariants=9851866,VariantsNotHarmonised=0,SwitchedAlleles=9851866,TotalControls=461032,TotalCases=1188,StudyType=CaseControl>",
    "contig": "<ID=1,length=249250621,assembly=GRCh37>",
    "contig.1": "<ID=2,length=243199373,assembly=GRCh37>",
    "contig.2": "<ID=3,length=198022430,assembly=GRCh37>",
    "contig.3": "<ID=4,length=191154276,assembly=GRCh37>",
    "contig.4": "<ID=5,length=180915260,assembly=GRCh37>",
    "contig.5": "<ID=6,length=171115067,assembly=GRCh37>",
    "contig.6": "<ID=7,length=159138663,assembly=GRCh37>",
    "contig.7": "<ID=8,length=146364022,assembly=GRCh37>",
    "contig.8": "<ID=9,length=141213431,assembly=GRCh37>",
    "contig.9": "<ID=10,length=135534747,assembly=GRCh37>",
    "contig.10": "<ID=11,length=135006516,assembly=GRCh37>",
    "contig.11": "<ID=12,length=133851895,assembly=GRCh37>",
    "contig.12": "<ID=13,length=115169878,assembly=GRCh37>",
    "contig.13": "<ID=14,length=107349540,assembly=GRCh37>",
    "contig.14": "<ID=15,length=102531392,assembly=GRCh37>",
    "contig.15": "<ID=16,length=90354753,assembly=GRCh37>",
    "contig.16": "<ID=17,length=81195210,assembly=GRCh37>",
    "contig.17": "<ID=18,length=78077248,assembly=GRCh37>",
    "contig.18": "<ID=19,length=59128983,assembly=GRCh37>",
    "contig.19": "<ID=20,length=63025520,assembly=GRCh37>",
    "contig.20": "<ID=21,length=48129895,assembly=GRCh37>",
    "contig.21": "<ID=22,length=51304566,assembly=GRCh37>",
    "contig.22": "<ID=X,length=155270560,assembly=GRCh37>",
    "contig.23": "<ID=Y,length=59373566,assembly=GRCh37>",
    "contig.24": "<ID=MT,length=16569,assembly=GRCh37>",
    "contig.25": "<ID=GL000207.1,length=4262,assembly=GRCh37>",
    "contig.26": "<ID=GL000226.1,length=15008,assembly=GRCh37>",
    "contig.27": "<ID=GL000229.1,length=19913,assembly=GRCh37>",
    "contig.28": "<ID=GL000231.1,length=27386,assembly=GRCh37>",
    "contig.29": "<ID=GL000210.1,length=27682,assembly=GRCh37>",
    "contig.30": "<ID=GL000239.1,length=33824,assembly=GRCh37>",
    "contig.31": "<ID=GL000235.1,length=34474,assembly=GRCh37>",
    "contig.32": "<ID=GL000201.1,length=36148,assembly=GRCh37>",
    "contig.33": "<ID=GL000247.1,length=36422,assembly=GRCh37>",
    "contig.34": "<ID=GL000245.1,length=36651,assembly=GRCh37>",
    "contig.35": "<ID=GL000197.1,length=37175,assembly=GRCh37>",
    "contig.36": "<ID=GL000203.1,length=37498,assembly=GRCh37>",
    "contig.37": "<ID=GL000246.1,length=38154,assembly=GRCh37>",
    "contig.38": "<ID=GL000249.1,length=38502,assembly=GRCh37>",
    "contig.39": "<ID=GL000196.1,length=38914,assembly=GRCh37>",
    "contig.40": "<ID=GL000248.1,length=39786,assembly=GRCh37>",
    "contig.41": "<ID=GL000244.1,length=39929,assembly=GRCh37>",
    "contig.42": "<ID=GL000238.1,length=39939,assembly=GRCh37>",
    "contig.43": "<ID=GL000202.1,length=40103,assembly=GRCh37>",
    "contig.44": "<ID=GL000234.1,length=40531,assembly=GRCh37>",
    "contig.45": "<ID=GL000232.1,length=40652,assembly=GRCh37>",
    "contig.46": "<ID=GL000206.1,length=41001,assembly=GRCh37>",
    "contig.47": "<ID=GL000240.1,length=41933,assembly=GRCh37>",
    "contig.48": "<ID=GL000236.1,length=41934,assembly=GRCh37>",
    "contig.49": "<ID=GL000241.1,length=42152,assembly=GRCh37>",
    "contig.50": "<ID=GL000243.1,length=43341,assembly=GRCh37>",
    "contig.51": "<ID=GL000242.1,length=43523,assembly=GRCh37>",
    "contig.52": "<ID=GL000230.1,length=43691,assembly=GRCh37>",
    "contig.53": "<ID=GL000237.1,length=45867,assembly=GRCh37>",
    "contig.54": "<ID=GL000233.1,length=45941,assembly=GRCh37>",
    "contig.55": "<ID=GL000204.1,length=81310,assembly=GRCh37>",
    "contig.56": "<ID=GL000198.1,length=90085,assembly=GRCh37>",
    "contig.57": "<ID=GL000208.1,length=92689,assembly=GRCh37>",
    "contig.58": "<ID=GL000191.1,length=106433,assembly=GRCh37>",
    "contig.59": "<ID=GL000227.1,length=128374,assembly=GRCh37>",
    "contig.60": "<ID=GL000228.1,length=129120,assembly=GRCh37>",
    "contig.61": "<ID=GL000214.1,length=137718,assembly=GRCh37>",
    "contig.62": "<ID=GL000221.1,length=155397,assembly=GRCh37>",
    "contig.63": "<ID=GL000209.1,length=159169,assembly=GRCh37>",
    "contig.64": "<ID=GL000218.1,length=161147,assembly=GRCh37>",
    "contig.65": "<ID=GL000220.1,length=161802,assembly=GRCh37>",
    "contig.66": "<ID=GL000213.1,length=164239,assembly=GRCh37>",
    "contig.67": "<ID=GL000211.1,length=166566,assembly=GRCh37>",
    "contig.68": "<ID=GL000199.1,length=169874,assembly=GRCh37>",
    "contig.69": "<ID=GL000217.1,length=172149,assembly=GRCh37>",
    "contig.70": "<ID=GL000216.1,length=172294,assembly=GRCh37>",
    "contig.71": "<ID=GL000215.1,length=172545,assembly=GRCh37>",
    "contig.72": "<ID=GL000205.1,length=174588,assembly=GRCh37>",
    "contig.73": "<ID=GL000219.1,length=179198,assembly=GRCh37>",
    "contig.74": "<ID=GL000224.1,length=179693,assembly=GRCh37>",
    "contig.75": "<ID=GL000223.1,length=180455,assembly=GRCh37>",
    "contig.76": "<ID=GL000195.1,length=182896,assembly=GRCh37>",
    "contig.77": "<ID=GL000212.1,length=186858,assembly=GRCh37>",
    "contig.78": "<ID=GL000222.1,length=186861,assembly=GRCh37>",
    "contig.79": "<ID=GL000200.1,length=187035,assembly=GRCh37>",
    "contig.80": "<ID=GL000193.1,length=189789,assembly=GRCh37>",
    "contig.81": "<ID=GL000194.1,length=191469,assembly=GRCh37>",
    "contig.82": "<ID=GL000225.1,length=211173,assembly=GRCh37>",
    "contig.83": "<ID=GL000192.1,length=547496,assembly=GRCh37>",
    "gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_41250_1003.vcf.gz --id UKB-b:837 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_41250_1003.txt.gz --cohort_cases 1188 --cohort_controls 461032 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
    "file_date": "2019-09-13T13:26:34.052227",
    "bcftools_viewVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
    "bcftools_viewCommand": "view -T ^/mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-837/mac_discard.txt -Oz /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-837/UKB-b-837_raw.vcf.gz; Date=Thu Oct 17 12:20:31 2019",
    "bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-837/ukb-b-837.vcf.gz; Date=Sun May 10 01:45:59 2020"
}
 

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/public/UKB-b-837/UKB-b-837_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-837/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:31 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-837/UKB-b-837_data.vcf.gz ...
Read summary statistics for 1864963 SNPs.
Dropped 180 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 479444 SNPs remain.
After merging with regression SNP LD, 479444 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0019 (0.0015)
Lambda GC: 1.1048
Mean Chi^2: 1.1038
Intercept: 1.1245 (0.0117)
Ratio: 1.1997 (0.1129)
Analysis finished at Thu Oct 17 14:41:58 2019
Total time elapsed: 27.66s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.671,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 4.9925e-08,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 14750,
    "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": 479444,
    "ldsc_nsnp_merge_regression_ld": 479444,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.1245,
    "ldsc_intercept_se": 0.0117,
    "ldsc_lambda_gc": 1.1048,
    "ldsc_mean_chisq": 1.1038,
    "ldsc_ratio": 1.1994
}
 

Flags

name value
af_correlation TRUE
inflation_factor FALSE
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 between AF and AF_reference.
  • inflation_factor (lambda): Genomic inflation factor.
  • mean_EFFECT: Mean of EFFECT size.
  • n: Maximum value of reported sample size across all SNPs, \(n\).
  • n_clumped_hits: Number of clumped hits.
  • n_snps: Number of SNPs
  • n_p_sig: Number of SNPs with pvalue below 5e-8.
  • n_mono: Number of monomorphic (MAF == 1 or MAF == 0) SNPs.
  • n_ns: Number of SNPs with nonsense values:
    • alleles other than A, C, G or T.
    • P-values < 0 or > 1.
    • negative or infinite standard errors (<= 0 or = Infinity).
    • infinite beta estimates or allele frequencies < 0 or > 1.
  • n_mac: Number of cases where MAC (\(2 \times N \times MAF\)) is less than 6.
  • is_snpid_unique: true if the combination of ID REF ALT is unique and therefore no duplication in snpid.
  • n_miss_<*>: Number of NA observations 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 expect ratio_se_n to 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 of diff and the mean of diff2 (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<*>: r2 statistics under various assumptions
    • 1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).
    • 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: NOT is_snpid_unique.
  • mean_EFFECT_nonfinite: mean(EFFECT) is NA, NaN, or Inf.
  • mean_EFFECT_05: abs(mean(EFFECT)) > 0.5.
  • mean_EFFECT_01: abs(mean(EFFECT)) > 0.1.
  • mean_chisq: ldsc_mean_chisq > 1.3 or ldsc_mean_chisq < 0.7.
  • n_p_sig: n_p_sig > 1000.
  • miss_<*>: n_miss_<*> / n_snps > 0.01.
  • ldsc_ratio: ldsc_ratio > 0.5
  • ldsc_intercept_beta: ldsc_intercept_beta > 1.5
  • n_clumped_hits: n_clumped_hits > 1000
  • r2_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 0 1.000000 4 58 0 1864785 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 1864963 0.000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA NA NA 8.652263e+00 5.765308e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.871563e+07 5.663722e+07 1.23330e+04 3.185540e+07 6.931121e+07 1.148272e+08 2.491722e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA 0.000000e+00 1.143000e-04 -6.17900e-04 -7.720000e-05 -7.000000e-07 7.710000e-05 5.632000e-04 ▁▁▇▂▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 1.089000e-04 3.700000e-06 1.01400e-04 1.061000e-04 1.080000e-04 1.112000e-04 2.081000e-04 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.849097e-01 2.926415e-01 1.00000e-07 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▆
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.849124e-01 2.926164e-01 2.00000e-07 2.280464e-01 4.782583e-01 7.388273e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA NA NA 4.731421e-01 1.176771e-01 2.94613e-01 3.697720e-01 4.595950e-01 5.699370e-01 7.053870e-01 ▇▇▆▅▅
numeric AF_reference 14750 0.992091 NA NA NA NA NA NA NA 4.523655e-01 1.562520e-01 1.99700e-04 3.328670e-01 4.440890e-01 5.652960e-01 1.000000e+00 ▁▇▇▃▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C 0.0002634 0.0001866 0.1600000 0.1580490 0.623764 0.782149 NA
1 54676 rs2462492 C T -0.0001823 0.0001849 0.3200000 0.3241697 0.400392 NA NA
1 91536 rs6702460 G T 0.0000697 0.0001820 0.6999999 0.7017762 0.456850 0.420727 NA
1 706368 rs55727773 A G 0.0001651 0.0001291 0.2000000 0.2009845 0.515636 0.275160 NA
1 814495 rs74461805 C A 0.0001610 0.0001770 0.3599996 0.3631230 0.340367 NA NA
1 830181 rs28444699 A G 0.0000475 0.0001184 0.6899999 0.6881653 0.697228 0.691294 NA
1 831489 rs4970385 C T 0.0000548 0.0001163 0.6400000 0.6375168 0.705375 0.649161 NA
1 840753 rs4970382 T C -0.0000338 0.0001072 0.7499995 0.7525037 0.400170 0.468850 NA
1 843405 rs11516185 A G -0.0001455 0.0001331 0.2700001 0.2743108 0.362605 0.375399 NA
1 850218 rs6664536 T A 0.0000186 0.0001069 0.8600001 0.8619209 0.590320 0.345248 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51164115 rs5770996 C T 0.0001862 0.0001061 0.0790005 0.0793459 0.456927 0.514776 NA
22 51164287 rs6009957 T C 0.0001829 0.0001142 0.1100001 0.1090885 0.306559 0.415535 NA
22 51165664 rs8137951 G A 0.0001920 0.0001145 0.0929994 0.0934061 0.301564 0.406350 NA
22 51174048 rs9628245 G C 0.0000633 0.0001199 0.5999997 0.5973636 0.380107 0.433107 NA
22 51181919 rs9616825 G C 0.0001132 0.0001209 0.3500000 0.3489431 0.695477 0.619409 NA
22 51186143 rs2879914 T C 0.0002305 0.0001130 0.0409996 0.0414154 0.381813 0.273363 NA
22 51186228 rs3865766 C T 0.0002026 0.0001102 0.0659994 0.0659699 0.451044 0.453275 NA
22 51197266 rs61290853 A G 0.0001941 0.0001137 0.0879995 0.0879820 0.386335 0.422923 NA
22 51212875 rs2238837 A C 0.0002764 0.0001213 0.0230001 0.0226841 0.331445 0.372404 NA
22 51237063 rs3896457 T C 0.0001731 0.0001242 0.1600000 0.1634604 0.297974 0.205072 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623764 ES:SE:LP:AF:ID  0.000263432:0.000186611:0.79588:0.623764:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400392 ES:SE:LP:AF:ID  -0.00018227:0.000184872:0.49485:0.400392:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.45685  ES:SE:LP:AF:ID  6.97044e-05:0.000182032:0.154902:0.45685:rs6702460
1   706368  rs12029736  A   G   .   PASS    AF=0.515636 ES:SE:LP:AF:ID  0.00016506:0.000129079:0.69897:0.515636:rs12029736
1   814495  rs74461805  C   A   .   PASS    AF=0.340367 ES:SE:LP:AF:ID  0.000160961:0.000176991:0.443698:0.340367:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697228 ES:SE:LP:AF:ID  4.75226e-05:0.000118408:0.161151:0.697228:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705375 ES:SE:LP:AF:ID  5.4781e-05:0.000116265:0.19382:0.705375:rs4970385
1   840753  rs4970382   T   C   .   PASS    AF=0.40017  ES:SE:LP:AF:ID  -3.38183e-05:0.000107244:0.124939:0.40017:rs4970382
1   843405  rs11516185  A   G   .   PASS    AF=0.362605 ES:SE:LP:AF:ID  -0.000145545:0.000133138:0.568636:0.362605:rs11516185
1   850218  rs6664536   T   A   .   PASS    AF=0.59032  ES:SE:LP:AF:ID  1.85995e-05:0.000106937:0.0655015:0.59032:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603714 ES:SE:LP:AF:ID  2.12094e-05:0.000107536:0.0757207:0.603714:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.603933 ES:SE:LP:AF:ID  1.80145e-05:0.000107521:0.0604807:0.603933:rs6657440
1   852037  rs4970463   G   A   .   PASS    AF=0.589678 ES:SE:LP:AF:ID  1.05774e-05:0.00010711:0.0362122:0.589678:rs4970463
1   852063  rs28436996  G   A   .   PASS    AF=0.589658 ES:SE:LP:AF:ID  1.17014e-05:0.000107062:0.0409586:0.589658:rs28436996
1   852875  rs13303369  C   T   .   PASS    AF=0.607664 ES:SE:LP:AF:ID  1.83407e-05:0.000107762:0.0655015:0.607664:rs13303369
1   853954  rs1806509   C   A   .   PASS    AF=0.607823 ES:SE:LP:AF:ID  1.66564e-05:0.000107776:0.0555173:0.607823:rs1806509
1   854777  rs13303019  A   G   .   PASS    AF=0.61031  ES:SE:LP:AF:ID  1.16768e-05:0.000107881:0.0409586:0.61031:rs13303019
1   854978  rs13303057  A   C   .   PASS    AF=0.603275 ES:SE:LP:AF:ID  1.9415e-05:0.000107562:0.0655015:0.603275:rs13303057
1   855075  rs6673914   C   G   .   PASS    AF=0.61033  ES:SE:LP:AF:ID  9.90553e-06:0.000107883:0.0315171:0.61033:rs6673914
1   856099  rs28534711  T   G   .   PASS    AF=0.389941 ES:SE:LP:AF:ID  -1.41864e-05:0.000107904:0.0457575:0.389941:rs28534711
1   856108  rs28742275  A   G   .   PASS    AF=0.389924 ES:SE:LP:AF:ID  -1.41272e-05:0.00010791:0.0457575:0.389924:rs28742275
1   856476  rs4040605   A   G   .   PASS    AF=0.350379 ES:SE:LP:AF:ID  -4.75776e-05:0.000110853:0.173925:0.350379:rs4040605
1   866893  rs2880024   T   C   .   PASS    AF=0.61052  ES:SE:LP:AF:ID  3.70201e-05:0.000108489:0.136677:0.61052:rs2880024
1   868418  rs28546443  C   T   .   PASS    AF=0.297904 ES:SE:LP:AF:ID  -3.10294e-05:0.000119194:0.102373:0.297904:rs28546443
1   875770  rs4970379   A   G   .   PASS    AF=0.600034 ES:SE:LP:AF:ID  6.43907e-05:0.000109393:0.251812:0.600034:rs4970379
1   881627  rs2272757   G   A   .   PASS    AF=0.652356 ES:SE:LP:AF:ID  6.38565e-06:0.000110502:0.0222764:0.652356:rs2272757
1   891059  rs13303065  C   T   .   PASS    AF=0.652394 ES:SE:LP:AF:ID  1.18039e-07:0.000110485:-0:0.652394:rs13303065
1   891945  rs13303106  A   G   .   PASS    AF=0.652457 ES:SE:LP:AF:ID  4.31951e-06:0.000110614:0.0132283:0.652457:rs13303106
1   903245  rs28690976  A   G   .   PASS    AF=0.56691  ES:SE:LP:AF:ID  7.17145e-05:0.000109867:0.29243:0.56691:rs28690976
1   909073  rs3892467   C   T   .   PASS    AF=0.386664 ES:SE:LP:AF:ID  0.000130098:0.000109577:0.619789:0.386664:rs3892467
1   909238  rs3829740   G   C   .   PASS    AF=0.571404 ES:SE:LP:AF:ID  0.000116008:0.000106116:0.568636:0.571404:rs3829740
1   910394  rs28477686  C   T   .   PASS    AF=0.324473 ES:SE:LP:AF:ID  -4.83821e-05:0.000115014:0.173925:0.324473:rs28477686
1   912049  rs7367995   T   C   .   PASS    AF=0.58522  ES:SE:LP:AF:ID  5.74229e-06:0.000107188:0.0177288:0.58522:rs7367995
1   913889  rs2340596   G   A   .   PASS    AF=0.599175 ES:SE:LP:AF:ID  -1.10169e-05:0.000107363:0.0362122:0.599175:rs2340596
1   914333  rs13302979  C   G   .   PASS    AF=0.602482 ES:SE:LP:AF:ID  -5.97591e-06:0.000107689:0.0177288:0.602482:rs13302979
1   914852  rs13303368  G   C   .   PASS    AF=0.60004  ES:SE:LP:AF:ID  -1.1445e-05:0.000107481:0.0362122:0.60004:rs13303368
1   914940  rs13303033  T   C   .   PASS    AF=0.584251 ES:SE:LP:AF:ID  -2.21966e-06:0.000106881:0.00877392:0.584251:rs13303033
1   916834  rs6694632   G   A   .   PASS    AF=0.589064 ES:SE:LP:AF:ID  -5.22211e-06:0.000107046:0.0177288:0.589064:rs6694632
1   918384  rs13303118  G   T   .   PASS    AF=0.584161 ES:SE:LP:AF:ID  -6.70722e-06:0.000106831:0.0222764:0.584161:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.589287 ES:SE:LP:AF:ID  -9.67853e-06:0.000106964:0.0315171:0.589287:rs2341354
1   919501  rs4970414   G   T   .   PASS    AF=0.583885 ES:SE:LP:AF:ID  3.42175e-05:0.00011062:0.119186:0.583885:rs4970414
1   921716  rs13303278  C   A   .   PASS    AF=0.567875 ES:SE:LP:AF:ID  4.64355e-05:0.000106744:0.180456:0.567875:rs13303278
1   924528  rs34712273  C   A   .   PASS    AF=0.57847  ES:SE:LP:AF:ID  5.23099e-05:0.00010705:0.200659:0.57847:rs34712273
1   930533  rs3128110   C   G   .   PASS    AF=0.386094 ES:SE:LP:AF:ID  -8.34582e-05:0.000108419:0.356547:0.386094:rs3128110
1   930567  rs3121574   A   G   .   PASS    AF=0.386136 ES:SE:LP:AF:ID  -8.38962e-05:0.000108422:0.356547:0.386136:rs3121574
1   930751  rs3128111   C   G   .   PASS    AF=0.385091 ES:SE:LP:AF:ID  -8.32884e-05:0.000108488:0.356547:0.385091:rs3128111
1   931166  rs2710880   A   G   .   PASS    AF=0.386774 ES:SE:LP:AF:ID  -9.06635e-05:0.000108441:0.39794:0.386774:rs2710880
1   931362  rs2799060   G   A   .   PASS    AF=0.385582 ES:SE:LP:AF:ID  -8.42278e-05:0.000108493:0.356547:0.385582:rs2799060
1   933790  rs9442392   G   A   .   PASS    AF=0.578589 ES:SE:LP:AF:ID  6.22469e-05:0.000107014:0.251812:0.578589:rs9442392
1   936111  rs1936360   C   T   .   PASS    AF=0.573529 ES:SE:LP:AF:ID  5.50448e-05:0.000106988:0.21467:0.573529:rs1936360