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:11886,TotalVariants=9851866,VariantsNotRead=0,HarmonisedVariants=9851866,VariantsNotHarmonised=0,SwitchedAlleles=9851866,TotalControls=460102,TotalCases=2831,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_1140870788.vcf.gz --id UKB-b:11886 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20003_1140870788.txt.gz --cohort_cases 2831 --cohort_controls 460102 --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": "2019-09-13T12:41:00.288073",
    "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-11886/mac_discard.txt -Oz /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11886/UKB-b-11886_raw.vcf.gz; Date=Thu Oct 17 12:26:20 2019",
    "bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-11886/ukb-b-11886.vcf.gz; Date=Sat May  9 23:01:21 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-11886/UKB-b-11886_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11886/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:10 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11886/UKB-b-11886_data.vcf.gz ...
Read summary statistics for 3911890 SNPs.
Dropped 715 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, 935953 SNPs remain.
After merging with regression SNP LD, 935953 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0031 (0.001)
Lambda GC: 1.0117
Mean Chi^2: 1.0192
Intercept: 0.9872 (0.0074)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:42:01 2019
Total time elapsed: 50.82s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8718,
    "inflation_factor": 1,
    "mean_EFFECT": -4.1808e-07,
    "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": 31851,
    "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": 935953,
    "ldsc_nsnp_merge_regression_ld": 935953,
    "ldsc_observed_scale_h2_beta": 0.0031,
    "ldsc_observed_scale_h2_se": 0.001,
    "ldsc_intercept_beta": 0.9872,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.0117,
    "ldsc_mean_chisq": 1.0192,
    "ldsc_ratio": -0.6667
}
 

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 3 58 0 3911178 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 3911890 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 8.660592e+00 5.767776e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.856403e+07 5.675322e+07 828.0000000 3.161513e+07 6.890062e+07 1.147054e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -4.000000e-07 1.916000e-04 -0.0012536 -1.264000e-04 -3.000000e-07 1.259000e-04 1.215200e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.881000e-04 2.460000e-05 0.0001562 1.667000e-04 1.801000e-04 2.051000e-04 5.712000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.972345e-01 2.898986e-01 0.0000039 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 4.972344e-01 2.898726e-01 0.0000039 2.446874e-01 4.969012e-01 7.488857e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.979359e-01 2.099822e-01 0.1236320 2.147580e-01 3.517050e-01 5.542858e-01 8.763680e-01 ▇▅▃▃▂
numeric AF_reference 31851 0.9918579 NA NA NA NA NA NA NA 3.864483e-01 2.149495e-01 0.0000000 2.096650e-01 3.476440e-01 5.419330e-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 -0.0001537 0.0002874 0.5900000 0.5928281 0.623763 0.782149 NA
1 54676 rs2462492 C T 0.0002131 0.0002847 0.4500005 0.4541494 0.400401 NA NA
1 91536 rs6702460 G T 0.0003078 0.0002804 0.2700001 0.2722472 0.456851 0.420727 NA
1 534192 rs6680723 C T 0.0005251 0.0003202 0.1000000 0.1010469 0.240960 NA NA
1 706368 rs55727773 A G -0.0001678 0.0001988 0.4000000 0.3987537 0.515650 0.275160 NA
1 729679 rs4951859 C G -0.0000565 0.0002326 0.8100000 0.8080486 0.843212 0.639976 NA
1 736289 rs79010578 T A 0.0001717 0.0002510 0.4899999 0.4940294 0.132330 0.139577 NA
1 752566 rs3094315 G A -0.0002244 0.0002252 0.3200000 0.3190411 0.838951 0.718251 NA
1 752721 rs3131972 A G -0.0002171 0.0002250 0.3300000 0.3346746 0.838580 0.653355 NA
1 753405 rs3115860 C A -0.0002660 0.0002414 0.2700001 0.2705505 0.869781 0.751797 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51197266 rs61290853 A G 0.0002652 0.0001751 0.1299999 0.1299119 0.386333 0.4229230 NA
22 51198027 rs34939255 A G -0.0004001 0.0001983 0.0439997 0.0435627 0.254557 0.0984425 NA
22 51210289 rs112565862 C T -0.0000834 0.0002639 0.7499995 0.7521335 0.129955 0.1018370 NA
22 51211106 rs9628250 T C -0.0003709 0.0001966 0.0589997 0.0591394 0.271547 0.1671330 NA
22 51211392 rs3888396 T C -0.0001145 0.0002616 0.6600001 0.6614977 0.132635 0.1641370 NA
22 51212875 rs2238837 A C 0.0003985 0.0001868 0.0329997 0.0328618 0.331455 0.3724040 NA
22 51213613 rs34726907 C T -0.0001294 0.0002461 0.5999997 0.5989809 0.127816 0.1727240 NA
22 51216564 rs9616970 T C -0.0001090 0.0002450 0.6600001 0.6564813 0.128330 0.1563500 NA
22 51219006 rs28729663 G A -0.0000706 0.0002398 0.7700005 0.7685982 0.137953 0.2052720 NA
22 51237063 rs3896457 T C 0.0003942 0.0001912 0.0389996 0.0392011 0.297971 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  -0.000153686:0.000287402:0.229148:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  0.000213121:0.000284725:0.346787:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  0.000307798:0.000280351:0.568636:0.456851:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.24096  ES:SE:LP:AF:ID  0.000525113:0.00032023:1:0.24096:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  -0.000167753:0.000198795:0.39794:0.51565:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.843212 ES:SE:LP:AF:ID  -5.6503e-05:0.000232576:0.091515:0.843212:rs4951859
1   736289  rs79010578  T   A   .   PASS    AF=0.13233  ES:SE:LP:AF:ID  0.000171672:0.000251014:0.309804:0.13233:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838951 ES:SE:LP:AF:ID  -0.00022443:0.000225234:0.49485:0.838951:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.83858  ES:SE:LP:AF:ID  -0.000217058:0.000224991:0.481486:0.83858:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869781 ES:SE:LP:AF:ID  -0.000266001:0.000241425:0.568636:0.869781:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129871 ES:SE:LP:AF:ID  0.000289245:0.000241919:0.638272:0.129871:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869123 ES:SE:LP:AF:ID  -0.000271062:0.000240952:0.585027:0.869123:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869221 ES:SE:LP:AF:ID  -0.000273362:0.000241047:0.585027:0.869221:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869126 ES:SE:LP:AF:ID  -0.000272213:0.000240947:0.585027:0.869126:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838033 ES:SE:LP:AF:ID  -0.000233653:0.000224367:0.522879:0.838033:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838664 ES:SE:LP:AF:ID  -0.000241683:0.000224997:0.552842:0.838664:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839777 ES:SE:LP:AF:ID  -0.000242305:0.00022804:0.537602:0.839777:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869405 ES:SE:LP:AF:ID  -0.000293788:0.000240668:0.657577:0.869405:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868952 ES:SE:LP:AF:ID  -0.000284256:0.000240063:0.619789:0.868952:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867905 ES:SE:LP:AF:ID  -0.000262363:0.000239603:0.568636:0.867905:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869095 ES:SE:LP:AF:ID  -0.00029166:0.000240259:0.657577:0.869095:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  -0.000291902:0.000240278:0.657577:0.869104:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869112 ES:SE:LP:AF:ID  -0.000292117:0.000240283:0.657577:0.869112:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869589 ES:SE:LP:AF:ID  -0.000292457:0.000240943:0.657577:0.869589:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838313 ES:SE:LP:AF:ID  -0.000252265:0.000223941:0.585027:0.838313:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838434 ES:SE:LP:AF:ID  -0.000255707:0.000224099:0.60206:0.838434:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862261 ES:SE:LP:AF:ID  -0.000291789:0.000239414:0.657577:0.862261:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  -0.000260624:0.000233068:0.585027:0.706753:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761304 ES:SE:LP:AF:ID  -0.000315425:0.000190225:1.01323:0.761304:rs2977608
1   769223  rs60320384  C   G   .   PASS    AF=0.129576 ES:SE:LP:AF:ID  0.000328426:0.000241774:0.769551:0.129576:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868911 ES:SE:LP:AF:ID  -0.000311941:0.000240483:0.721246:0.868911:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129677 ES:SE:LP:AF:ID  0.00032417:0.000241618:0.744727:0.129677:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868921 ES:SE:LP:AF:ID  -0.000313588:0.000240488:0.721246:0.868921:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.26539  ES:SE:LP:AF:ID  -1.93249e-05:0.000212485:0.0315171:0.26539:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870044 ES:SE:LP:AF:ID  -0.000317324:0.000240978:0.721246:0.870044:rs2980319
1   778745  rs1055606   A   G   .   PASS    AF=0.128576 ES:SE:LP:AF:ID  0.000342992:0.00024193:0.79588:0.128576:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128873 ES:SE:LP:AF:ID  0.00033668:0.000241519:0.79588:0.128873:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868786 ES:SE:LP:AF:ID  -0.000331891:0.000240336:0.769551:0.868786:rs2977612
1   782981  rs6594026   C   T   .   PASS    AF=0.129513 ES:SE:LP:AF:ID  0.000327437:0.000241441:0.744727:0.129513:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.868539 ES:SE:LP:AF:ID  -0.000294799:0.00024028:0.657577:0.868539:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.86848  ES:SE:LP:AF:ID  -0.000291862:0.000240429:0.657577:0.86848:rs2980300
1   787399  rs2905055   G   T   .   PASS    AF=0.86078  ES:SE:LP:AF:ID  -0.000261822:0.000240264:0.552842:0.86078:rs2905055
1   787606  rs3863622   G   T   .   PASS    AF=0.128461 ES:SE:LP:AF:ID  0.000316877:0.000242743:0.721246:0.128461:rs3863622
1   787685  rs2905054   G   T   .   PASS    AF=0.861493 ES:SE:LP:AF:ID  -0.000274728:0.000240423:0.60206:0.861493:rs2905054
1   787844  rs2905053   C   T   .   PASS    AF=0.869229 ES:SE:LP:AF:ID  -0.000292171:0.000241308:0.638272:0.869229:rs2905053
1   791191  rs111818025 G   A   .   PASS    AF=0.127879 ES:SE:LP:AF:ID  0.000335521:0.000244298:0.769551:0.127879:rs111818025
1   795988  rs59380221  C   T   .   PASS    AF=0.143051 ES:SE:LP:AF:ID  0.000359669:0.000249207:0.823909:0.143051:rs59380221
1   796375  rs12083781  T   C   .   PASS    AF=0.123818 ES:SE:LP:AF:ID  0.000281599:0.000251065:0.585027:0.123818:rs12083781
1   798400  rs10900604  A   G   .   PASS    AF=0.20658  ES:SE:LP:AF:ID  0.000332331:0.000202935:1:0.20658:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.206409 ES:SE:LP:AF:ID  0.000335003:0.000203022:1.00436:0.206409:rs11240777