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:1733,TotalVariants=9851866,VariantsNotRead=0,HarmonisedVariants=9851866,VariantsNotHarmonised=0,SwitchedAlleles=9851866,TotalControls=52728,StudyType=Continuous>",
    "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_5161.vcf.gz --id UKB-b:1733 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_5161.txt.gz --cohort_controls 52728 --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": "2019-09-12T23:15:51.252460",
    "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-1733/mac_discard.txt -Oz /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1733/UKB-b-1733_raw.vcf.gz; Date=Thu Oct 17 12:34:46 2019",
    "bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-1733/ukb-b-1733.vcf.gz; Date=Sat May  9 22:58:57 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-1733/UKB-b-1733_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1733/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1733/UKB-b-1733_data.vcf.gz ...
Read summary statistics for 8321893 SNPs.
Dropped 6754 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, 1284636 SNPs remain.
After merging with regression SNP LD, 1284636 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0507 (0.0098)
Lambda GC: 1.0498
Mean Chi^2: 1.0541
Intercept: 1.001 (0.0067)
Ratio: 0.018 (0.1243)
Analysis finished at Thu Oct 17 14:41:58 2019
Total time elapsed: 1.0m:40.22s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9449,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 1.4463e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "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": 78342,
    "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": 1284636,
    "ldsc_nsnp_merge_regression_ld": 1284636,
    "ldsc_observed_scale_h2_beta": 0.0507,
    "ldsc_observed_scale_h2_se": 0.0098,
    "ldsc_intercept_beta": 1.001,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.0498,
    "ldsc_mean_chisq": 1.0541,
    "ldsc_ratio": 0.0185
}

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 1.000000 3 58 0 8315169 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 8321893 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 8.655210e+00 5.762261e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.873388e+07 5.638614e+07 828.0000000 3.232578e+07 6.922569e+07 1.145487e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA 1.400000e-06 1.679770e-02 -0.2286070 -7.372300e-03 3.180000e-05 7.432800e-03 1.800290e-01 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 1.395030e-02 8.980800e-03 0.0059124 6.919800e-03 9.915200e-03 1.861760e-02 9.054600e-02 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.932464e-01 2.908996e-01 0.0000000 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.932452e-01 2.908735e-01 0.0000000 2.392751e-01 4.911080e-01 7.459911e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA NA NA 2.368605e-01 2.601867e-01 0.0066380 2.984800e-02 1.246160e-01 3.750950e-01 9.933620e-01 ▇▂▂▁▁
numeric AF_reference 78342 0.990586 NA NA NA NA NA NA NA 2.363901e-01 2.520958e-01 0.0000000 2.955270e-02 1.405750e-01 3.714060e-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 -0.0095886 0.0109261 0.3800004 0.3801661 0.622211 0.7821490 NA
1 54676 rs2462492 C T 0.0081798 0.0108594 0.4500005 0.4513021 0.400240 NA NA
1 86028 rs114608975 T C 0.0007688 0.0172822 0.9599999 0.9645177 0.103863 0.0277556 NA
1 91536 rs6702460 G T 0.0209209 0.0106824 0.0500000 0.0501777 0.455379 0.4207270 NA
1 234313 rs8179466 C T -0.0039609 0.0207242 0.8499999 0.8484285 0.075272 NA NA
1 534192 rs6680723 C T -0.0146541 0.0122366 0.2300001 0.2310872 0.240321 NA NA
1 546697 rs12025928 A G 0.0079936 0.0151257 0.5999997 0.5971690 0.912567 NA NA
1 693731 rs12238997 A G -0.0193373 0.0101908 0.0580003 0.0577587 0.117227 0.1417730 NA
1 705882 rs72631875 G A 0.0050259 0.0148224 0.7300002 0.7345530 0.068033 0.0315495 NA
1 706368 rs55727773 A G 0.0116295 0.0075244 0.1199999 0.1222065 0.516269 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0005877 0.0091209 0.9500000 0.9486210 0.137243 0.2052720 NA
22 51219387 rs9616832 T C 0.0030392 0.0118836 0.8000000 0.7981485 0.072427 0.0654952 NA
22 51219704 rs147475742 G A 0.0084686 0.0157429 0.5900000 0.5906266 0.042129 0.0473243 NA
22 51221190 rs369304721 G A 0.0064513 0.0158586 0.6800001 0.6841534 0.049069 NA NA
22 51221731 rs115055839 T C 0.0027438 0.0118855 0.8200001 0.8174273 0.071981 0.0625000 NA
22 51222100 rs114553188 G T 0.0021136 0.0138813 0.8800001 0.8789806 0.054683 0.0880591 NA
22 51223637 rs375798137 G A 0.0025708 0.0139501 0.8499999 0.8537879 0.054316 0.0788738 NA
22 51229805 rs9616985 T C 0.0033529 0.0119279 0.7800007 0.7786358 0.071879 0.0730831 NA
22 51232488 rs376461333 A G -0.0207120 0.0281550 0.4600002 0.4619486 0.020013 NA NA
22 51237063 rs3896457 T C 0.0125491 0.0072515 0.0840001 0.0835333 0.299429 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.622211 ES:SE:LP:AF:ID  -0.00958864:0.0109261:0.420216:0.622211:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40024  ES:SE:LP:AF:ID  0.0081798:0.0108594:0.346787:0.40024:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103863 ES:SE:LP:AF:ID  0.0007688:0.0172822:0.0177288:0.103863:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.455379 ES:SE:LP:AF:ID  0.0209209:0.0106824:1.30103:0.455379:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.075272 ES:SE:LP:AF:ID  -0.00396089:0.0207242:0.0705811:0.075272:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240321 ES:SE:LP:AF:ID  -0.0146541:0.0122366:0.638272:0.240321:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.912567 ES:SE:LP:AF:ID  0.00799357:0.0151257:0.221849:0.912567:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.117227 ES:SE:LP:AF:ID  -0.0193373:0.0101908:1.23657:0.117227:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.068033 ES:SE:LP:AF:ID  0.00502591:0.0148224:0.136677:0.068033:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.516269 ES:SE:LP:AF:ID  0.0116295:0.00752437:0.920819:0.516269:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033382 ES:SE:LP:AF:ID  -0.0454791:0.018876:1.79588:0.033382:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03707  ES:SE:LP:AF:ID  -0.0393096:0.0171533:1.65758:0.03707:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.037139 ES:SE:LP:AF:ID  -0.039839:0.0171019:1.69897:0.037139:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036858 ES:SE:LP:AF:ID  -0.0397871:0.017215:1.67778:0.036858:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016505 ES:SE:LP:AF:ID  -0.0199007:0.0266358:0.346787:0.016505:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.037408 ES:SE:LP:AF:ID  -0.0392451:0.0170269:1.67778:0.037408:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.03749  ES:SE:LP:AF:ID  -0.0382422:0.0169724:1.61979:0.03749:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.100113 ES:SE:LP:AF:ID  -0.00151125:0.0125176:0.0457575:0.100113:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.958145 ES:SE:LP:AF:ID  0.0340732:0.0162978:1.4318:0.958145:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031578 ES:SE:LP:AF:ID  -0.00743693:0.0300982:0.09691:0.031578:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053174 ES:SE:LP:AF:ID  0.0370941:0.0237402:0.920819:0.053174:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036964 ES:SE:LP:AF:ID  -0.0365258:0.0170868:1.48149:0.036964:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.037317 ES:SE:LP:AF:ID  -0.0358521:0.0169378:1.46852:0.037317:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.841747 ES:SE:LP:AF:ID  0.025375:0.00882096:2.39794:0.841747:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055918 ES:SE:LP:AF:ID  -0.0236967:0.0143538:1.00436:0.055918:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123095 ES:SE:LP:AF:ID  -0.0180693:0.00968038:1.20761:0.123095:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025654 ES:SE:LP:AF:ID  0.00174044:0.0239012:0.0268721:0.025654:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.122285 ES:SE:LP:AF:ID  -0.0181919:0.00968481:1.22185:0.122285:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132909 ES:SE:LP:AF:ID  -0.0258049:0.00952468:2.17393:0.132909:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011218 ES:SE:LP:AF:ID  -0.0242697:0.0343197:0.318759:0.011218:rs181876450
1   752478  rs146277091 G   A   .   PASS    AF=0.037301 ES:SE:LP:AF:ID  -0.0367202:0.0167464:1.55284:0.037301:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.837926 ES:SE:LP:AF:ID  0.024312:0.00854303:2.35655:0.837926:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.837449 ES:SE:LP:AF:ID  0.0236502:0.00853143:2.25181:0.837449:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868914 ES:SE:LP:AF:ID  0.0176594:0.00916735:1.26761:0.868914:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.130626 ES:SE:LP:AF:ID  -0.0164065:0.00918903:1.13077:0.130626:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037737 ES:SE:LP:AF:ID  -0.0350562:0.0164829:1.48149:0.037737:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.038016 ES:SE:LP:AF:ID  -0.0348023:0.016373:1.46852:0.038016:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.868257 ES:SE:LP:AF:ID  0.0167004:0.00914967:1.16749:0.868257:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.868337 ES:SE:LP:AF:ID  0.0165594:0.00915333:1.1549:0.868337:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03794  ES:SE:LP:AF:ID  -0.0336536:0.0164421:1.38722:0.03794:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.868227 ES:SE:LP:AF:ID  0.0167825:0.00914857:1.17393:0.868227:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837023 ES:SE:LP:AF:ID  0.0234461:0.00851381:2.22915:0.837023:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.03797  ES:SE:LP:AF:ID  -0.0345195:0.0164627:1.4437:0.03797:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83762  ES:SE:LP:AF:ID  0.0234355:0.00853699:2.22185:0.83762:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013162 ES:SE:LP:AF:ID  0.0575027:0.03064:1.21467:0.013162:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839026 ES:SE:LP:AF:ID  0.0229187:0.00866014:2.09152:0.839026:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868587 ES:SE:LP:AF:ID  0.017759:0.00914018:1.284:0.868587:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.86821  ES:SE:LP:AF:ID  0.0182233:0.00911945:1.33724:0.86821:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86689  ES:SE:LP:AF:ID  0.0159794:0.00909339:1.10237:0.86689:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868331 ES:SE:LP:AF:ID  0.017898:0.00912716:1.30103:0.868331:rs4951929