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:8624,TotalVariants=9851866,VariantsNotRead=0,HarmonisedVariants=9851866,VariantsNotHarmonised=0,SwitchedAlleles=9851866,TotalControls=461668,TotalCases=1265,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_20003_1140868472.vcf.gz --id UKB-b:8624 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20003_1140868472.txt.gz --cohort_cases 1265 --cohort_controls 461668 --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": "2019-09-13T14:26:17.392420",
    "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-8624/mac_discard.txt -Oz /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8624/UKB-b-8624_raw.vcf.gz; Date=Thu Oct 17 12:21:11 2019",
    "bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-8624/ukb-b-8624.vcf.gz; Date=Sun May 10 09:42:06 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-8624/UKB-b-8624_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8624/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:05 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8624/UKB-b-8624_data.vcf.gz ...
Read summary statistics for 2042067 SNPs.
Dropped 202 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, 522806 SNPs remain.
After merging with regression SNP LD, 522806 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0021 (0.0014)
Lambda GC: 1.0156
Mean Chi^2: 1.0258
Intercept: 1.0029 (0.011)
Ratio: 0.1128 (0.4262)
Analysis finished at Thu Oct 17 14:42:54 2019
Total time elapsed: 49.2s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.7032,
    "inflation_factor": 1,
    "mean_EFFECT": 1.3388e-06,
    "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": 16213,
    "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": 522806,
    "ldsc_nsnp_merge_regression_ld": 522806,
    "ldsc_observed_scale_h2_beta": 0.0021,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.0029,
    "ldsc_intercept_se": 0.011,
    "ldsc_lambda_gc": 1.0156,
    "ldsc_mean_chisq": 1.0258,
    "ldsc_ratio": 0.1124
}
 

Flags

name value
af_correlation FALSE
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 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 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 1.0000000 4 58 0 2041867 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 N 2042067 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 8.648060e+00 5.764462e+00 1.0000e+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 7.872179e+07 5.664216e+07 5.6870e+03 3.182644e+07 6.927753e+07 1.148338e+08 2.491722e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.300000e-06 1.148000e-04 -5.9000e-04 -7.530000e-05 1.000000e-06 7.810000e-05 5.244000e-04 ▁▁▇▃▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.131000e-04 4.400000e-06 1.0460e-04 1.095000e-04 1.119000e-04 1.159000e-04 2.170000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.970267e-01 2.912191e-01 7.5000e-06 2.399999e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.970254e-01 2.911954e-01 7.5000e-06 2.434400e-01 4.972828e-01 7.500741e-01 9.999996e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.679361e-01 1.275333e-01 2.7668e-01 3.558715e-01 4.519800e-01 5.722135e-01 7.233200e-01 ▇▆▆▅▅
numeric AF_reference 16213 0.9920605 NA NA NA NA NA NA NA 4.477998e-01 1.618312e-01 1.9970e-04 3.226840e-01 4.378990e-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 0.0001073 0.0001925 0.5800000 0.5773303 0.623763 0.782149 NA
1 54676 rs2462492 C T 0.0002961 0.0001907 0.1199999 0.1204382 0.400401 NA NA
1 91536 rs6702460 G T 0.0002338 0.0001878 0.2099999 0.2131400 0.456851 0.420727 NA
1 706368 rs55727773 A G 0.0000103 0.0001331 0.9400001 0.9382125 0.515650 0.275160 NA
1 763394 rs369924889 G A -0.0000880 0.0001561 0.5700002 0.5729196 0.706753 0.617612 NA
1 814495 rs74461805 C A -0.0000400 0.0001826 0.8300000 0.8265235 0.340397 NA NA
1 830181 rs28444699 A G -0.0000670 0.0001221 0.5800000 0.5834290 0.697259 0.691294 NA
1 831489 rs4970385 C T -0.0000710 0.0001199 0.5500004 0.5540727 0.705403 0.649161 NA
1 831909 rs9697642 C T -0.0000643 0.0001199 0.5900000 0.5920108 0.705448 0.648562 NA
1 832066 rs9697380 G C -0.0000663 0.0001199 0.5800000 0.5801012 0.705634 0.664337 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51171693 rs756638 G A -0.0000484 0.0001241 0.6999999 0.6966926 0.282282 0.304912 NA
22 51174048 rs9628245 G C -0.0000471 0.0001237 0.6999999 0.7030367 0.380130 0.433107 NA
22 51180501 rs5770999 T C 0.0000985 0.0001253 0.4299995 0.4316509 0.713658 0.636981 NA
22 51181919 rs9616825 G C 0.0001169 0.0001247 0.3500000 0.3485409 0.695471 0.619409 NA
22 51182485 rs6009961 A G 0.0000990 0.0001257 0.4299995 0.4311312 0.715505 0.638379 NA
22 51186143 rs2879914 T C -0.0000656 0.0001166 0.5700002 0.5737696 0.381826 0.273363 NA
22 51186228 rs3865766 C T -0.0000243 0.0001136 0.8300000 0.8303524 0.451063 0.453275 NA
22 51197266 rs61290853 A G -0.0000066 0.0001173 0.9599999 0.9553408 0.386333 0.422923 NA
22 51212875 rs2238837 A C -0.0000468 0.0001251 0.7099994 0.7080641 0.331455 0.372404 NA
22 51237063 rs3896457 T C -0.0000458 0.0001280 0.7199992 0.7207224 0.297971 0.205072 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  0.000107268:0.000192482:0.236572:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  0.000296128:0.000190689:0.920819:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  0.000233757:0.00018776:0.677781:0.456851:rs6702460
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  1.03205e-05:0.000133139:0.0268721:0.51565:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  -8.79985e-05:0.000156093:0.244125:0.706753:rs3115847
1   814495  rs74461805  C   A   .   PASS    AF=0.340397 ES:SE:LP:AF:ID  -4.00103e-05:0.00018256:0.0809219:0.340397:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697259 ES:SE:LP:AF:ID  -6.69784e-05:0.000122138:0.236572:0.697259:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705403 ES:SE:LP:AF:ID  -7.09576e-05:0.000119928:0.259637:0.705403:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705448 ES:SE:LP:AF:ID  -6.42702e-05:0.000119924:0.229148:0.705448:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705634 ES:SE:LP:AF:ID  -6.63497e-05:0.00011993:0.236572:0.705634:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705662 ES:SE:LP:AF:ID  -6.68173e-05:0.000119942:0.236572:0.705662:rs4500250
1   832918  rs28765502  T   C   .   PASS    AF=0.294371 ES:SE:LP:AF:ID  6.61883e-05:0.000119937:0.236572:0.294371:rs28765502
1   840753  rs4970382   T   C   .   PASS    AF=0.400106 ES:SE:LP:AF:ID  3.65705e-05:0.000110624:0.130768:0.400106:rs4970382
1   843405  rs11516185  A   G   .   PASS    AF=0.362599 ES:SE:LP:AF:ID  -4.02704e-05:0.000137327:0.113509:0.362599:rs11516185
1   850218  rs6664536   T   A   .   PASS    AF=0.590333 ES:SE:LP:AF:ID  -0.00010466:0.0001103:0.468521:0.590333:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603726 ES:SE:LP:AF:ID  -9.48881e-05:0.000110919:0.408935:0.603726:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.603944 ES:SE:LP:AF:ID  -9.62017e-05:0.000110903:0.408935:0.603944:rs6657440
1   852037  rs4970463   G   A   .   PASS    AF=0.589688 ES:SE:LP:AF:ID  -0.00011023:0.000110479:0.49485:0.589688:rs4970463
1   852063  rs28436996  G   A   .   PASS    AF=0.589667 ES:SE:LP:AF:ID  -0.000110118:0.000110429:0.49485:0.589667:rs28436996
1   852875  rs13303369  C   T   .   PASS    AF=0.607674 ES:SE:LP:AF:ID  -9.56011e-05:0.000111151:0.408935:0.607674:rs13303369
1   853954  rs1806509   C   A   .   PASS    AF=0.607833 ES:SE:LP:AF:ID  -9.88989e-05:0.000111166:0.431798:0.607833:rs1806509
1   854777  rs13303019  A   G   .   PASS    AF=0.610318 ES:SE:LP:AF:ID  -8.65668e-05:0.000111275:0.356547:0.610318:rs13303019
1   854978  rs13303057  A   C   .   PASS    AF=0.603286 ES:SE:LP:AF:ID  -0.000107434:0.000110946:0.481486:0.603286:rs13303057
1   855075  rs6673914   C   G   .   PASS    AF=0.610338 ES:SE:LP:AF:ID  -8.62404e-05:0.000111278:0.356547:0.610338:rs6673914
1   856099  rs28534711  T   G   .   PASS    AF=0.389935 ES:SE:LP:AF:ID  9.15571e-05:0.000111299:0.387216:0.389935:rs28534711
1   856108  rs28742275  A   G   .   PASS    AF=0.389918 ES:SE:LP:AF:ID  9.17883e-05:0.000111304:0.387216:0.389918:rs28742275
1   856476  rs4040605   A   G   .   PASS    AF=0.350351 ES:SE:LP:AF:ID  9.95925e-05:0.000114341:0.420216:0.350351:rs4040605
1   866893  rs2880024   T   C   .   PASS    AF=0.610554 ES:SE:LP:AF:ID  -0.000105696:0.000111903:0.468521:0.610554:rs2880024
1   868418  rs28546443  C   T   .   PASS    AF=0.297865 ES:SE:LP:AF:ID  0.000186357:0.00012295:0.886057:0.297865:rs28546443
1   870645  rs28576697  T   C   .   PASS    AF=0.291287 ES:SE:LP:AF:ID  0.000117028:0.00012197:0.468521:0.291287:rs28576697
1   871334  rs4072383   G   T   .   PASS    AF=0.720619 ES:SE:LP:AF:ID  -3.84132e-05:0.000121215:0.124939:0.720619:rs4072383
1   873558  rs1110052   G   T   .   PASS    AF=0.715253 ES:SE:LP:AF:ID  -6.47831e-05:0.000120251:0.229148:0.715253:rs1110052
1   875770  rs4970379   A   G   .   PASS    AF=0.600084 ES:SE:LP:AF:ID  -7.94308e-05:0.000112833:0.318759:0.600084:rs4970379
1   881627  rs2272757   G   A   .   PASS    AF=0.65239  ES:SE:LP:AF:ID  -6.2984e-05:0.000113981:0.236572:0.65239:rs2272757
1   891059  rs13303065  C   T   .   PASS    AF=0.652428 ES:SE:LP:AF:ID  -7.22433e-05:0.000113963:0.275724:0.652428:rs13303065
1   891945  rs13303106  A   G   .   PASS    AF=0.65249  ES:SE:LP:AF:ID  -6.24025e-05:0.000114095:0.236572:0.65249:rs13303106
1   903245  rs28690976  A   G   .   PASS    AF=0.566937 ES:SE:LP:AF:ID  -5.51247e-05:0.000113322:0.200659:0.566937:rs28690976
1   909073  rs3892467   C   T   .   PASS    AF=0.386683 ES:SE:LP:AF:ID  2.54704e-05:0.000113014:0.0861861:0.386683:rs3892467
1   909238  rs3829740   G   C   .   PASS    AF=0.571412 ES:SE:LP:AF:ID  1.48286e-05:0.00010945:0.05061:0.571412:rs3829740
1   910394  rs28477686  C   T   .   PASS    AF=0.324456 ES:SE:LP:AF:ID  -5.87486e-05:0.000118632:0.207608:0.324456:rs28477686
1   912049  rs7367995   T   C   .   PASS    AF=0.58525  ES:SE:LP:AF:ID  -2.80017e-05:0.00011056:0.09691:0.58525:rs7367995
1   913889  rs2340596   G   A   .   PASS    AF=0.599213 ES:SE:LP:AF:ID  -2.56062e-05:0.00011074:0.0861861:0.599213:rs2340596
1   914333  rs13302979  C   G   .   PASS    AF=0.602521 ES:SE:LP:AF:ID  -1.34295e-05:0.000111076:0.0457575:0.602521:rs13302979
1   914852  rs13303368  G   C   .   PASS    AF=0.600078 ES:SE:LP:AF:ID  -1.75358e-05:0.000110862:0.0604807:0.600078:rs13303368
1   914940  rs13303033  T   C   .   PASS    AF=0.584292 ES:SE:LP:AF:ID  -2.24329e-05:0.00011024:0.0757207:0.584292:rs13303033
1   916834  rs6694632   G   A   .   PASS    AF=0.589106 ES:SE:LP:AF:ID  -2.54626e-05:0.000110409:0.0861861:0.589106:rs6694632
1   918384  rs13303118  G   T   .   PASS    AF=0.584205 ES:SE:LP:AF:ID  -2.58857e-05:0.000110188:0.091515:0.584205:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.589331 ES:SE:LP:AF:ID  -2.67455e-05:0.000110324:0.091515:0.589331:rs2341354
1   919501  rs4970414   G   T   .   PASS    AF=0.583932 ES:SE:LP:AF:ID  -9.98281e-05:0.000114094:0.420216:0.583932:rs4970414
1   921716  rs13303278  C   A   .   PASS    AF=0.567888 ES:SE:LP:AF:ID  1.73463e-05:0.000110097:0.0604807:0.567888:rs13303278