Investigating health measures in relation to number of children

library(TwoSampleMR)
## TwoSampleMR version 0.5.6 
## [>] New: Option to use non-European LD reference panels for clumping etc
## [>] Some studies temporarily quarantined to verify effect allele
## [>] See news(package='TwoSampleMR') and https://gwas.mrcieu.ac.uk for further details

Overall

Overall health rating

d <- make_dat("ukb-b-6306", "ieu-b-4760")
## API: public: http://gwas-api.mrcieu.ac.uk/
## Extracting data for 109 SNP(s) from 1 GWAS(s)
## Finding proxies for 6 SNPs in outcome ieu-b-4760
## Extracting data for 6 SNP(s) from 1 GWAS(s)
## Harmonising Overall health rating || id:ukb-b-6306 (ukb-b-6306) and Number of children || id:ieu-b-4760 (ieu-b-4760)
d_mr<-mr(d)
## Analysing 'ukb-b-6306' on 'ieu-b-4760'
d_mr
##   id.exposure id.outcome                             outcome
## 1  ukb-b-6306 ieu-b-4760 Number of children || id:ieu-b-4760
## 2  ukb-b-6306 ieu-b-4760 Number of children || id:ieu-b-4760
## 3  ukb-b-6306 ieu-b-4760 Number of children || id:ieu-b-4760
## 4  ukb-b-6306 ieu-b-4760 Number of children || id:ieu-b-4760
## 5  ukb-b-6306 ieu-b-4760 Number of children || id:ieu-b-4760
##                                 exposure                    method nsnp
## 1 Overall health rating || id:ukb-b-6306                  MR Egger  108
## 2 Overall health rating || id:ukb-b-6306           Weighted median  108
## 3 Overall health rating || id:ukb-b-6306 Inverse variance weighted  108
## 4 Overall health rating || id:ukb-b-6306               Simple mode  108
## 5 Overall health rating || id:ukb-b-6306             Weighted mode  108
##            b         se         pval
## 1 0.25264155 0.17178157 0.1443308230
## 2 0.08621421 0.03367908 0.0104710075
## 3 0.11474417 0.03422423 0.0008002236
## 4 0.08139276 0.09642233 0.4004813709
## 5 0.07576464 0.09138677 0.4089190362
mr_scatter_plot(d_mr,d)
## $`ukb-b-6306.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-6306 ieu-b-4760
d <- make_dat("ieu-b-4760", "ukb-b-6306")
## Extracting data for 9 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ukb-b-6306
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Overall health rating || id:ukb-b-6306 (ukb-b-6306)
d_mr<-mr(d)
## Analysing 'ieu-b-4760' on 'ukb-b-6306'
d_mr
##   id.exposure id.outcome                                outcome
## 1  ieu-b-4760 ukb-b-6306 Overall health rating || id:ukb-b-6306
## 2  ieu-b-4760 ukb-b-6306 Overall health rating || id:ukb-b-6306
## 3  ieu-b-4760 ukb-b-6306 Overall health rating || id:ukb-b-6306
## 4  ieu-b-4760 ukb-b-6306 Overall health rating || id:ukb-b-6306
## 5  ieu-b-4760 ukb-b-6306 Overall health rating || id:ukb-b-6306
##                              exposure                    method nsnp
## 1 Number of children || id:ieu-b-4760                  MR Egger    8
## 2 Number of children || id:ieu-b-4760           Weighted median    8
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8
## 4 Number of children || id:ieu-b-4760               Simple mode    8
## 5 Number of children || id:ieu-b-4760             Weighted mode    8
##             b         se         pval
## 1 -1.04071285 0.60540857 0.1364079350
## 2 -0.21427039 0.06293617 0.0006626912
## 3 -0.03319569 0.11815412 0.7787468627
## 4 -0.21866602 0.10090367 0.0669051523
## 5 -0.21866602 0.06312163 0.0104877888
mr_scatter_plot(d_mr,d)
## $`ieu-b-4760.ukb-b-6306`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ieu-b-4760 ukb-b-6306

Number of self-reported cancers

d <- make_dat("ukb-b-660", "ieu-b-4760")
## Extracting data for 13 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ieu-b-4760
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Number of self-reported cancers || id:ukb-b-660 (ukb-b-660) and Number of children || id:ieu-b-4760 (ieu-b-4760)
d_mr<-mr(d)
## Analysing 'ukb-b-660' on 'ieu-b-4760'
d_mr
##   id.exposure id.outcome                             outcome
## 1   ukb-b-660 ieu-b-4760 Number of children || id:ieu-b-4760
## 2   ukb-b-660 ieu-b-4760 Number of children || id:ieu-b-4760
## 3   ukb-b-660 ieu-b-4760 Number of children || id:ieu-b-4760
## 4   ukb-b-660 ieu-b-4760 Number of children || id:ieu-b-4760
## 5   ukb-b-660 ieu-b-4760 Number of children || id:ieu-b-4760
##                                          exposure                    method
## 1 Number of self-reported cancers || id:ukb-b-660                  MR Egger
## 2 Number of self-reported cancers || id:ukb-b-660           Weighted median
## 3 Number of self-reported cancers || id:ukb-b-660 Inverse variance weighted
## 4 Number of self-reported cancers || id:ukb-b-660               Simple mode
## 5 Number of self-reported cancers || id:ukb-b-660             Weighted mode
##   nsnp          b        se        pval
## 1   13 -0.3446832 0.7218644 0.642359806
## 2   13 -0.5032749 0.1866383 0.007006701
## 3   13 -0.6380858 0.2004950 0.001459831
## 4   13 -0.2447197 0.3071517 0.441081748
## 5   13 -0.2535668 0.3278818 0.454281307
mr_scatter_plot(d_mr,d)
## $`ukb-b-660.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1   ukb-b-660 ieu-b-4760
d <- make_dat("ieu-b-4760", "ukb-b-660")
## Extracting data for 9 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ukb-b-660
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Number of self-reported cancers || id:ukb-b-660 (ukb-b-660)
d_mr<-mr(d)
## Analysing 'ieu-b-4760' on 'ukb-b-660'
d_mr
##   id.exposure id.outcome                                         outcome
## 1  ieu-b-4760  ukb-b-660 Number of self-reported cancers || id:ukb-b-660
## 2  ieu-b-4760  ukb-b-660 Number of self-reported cancers || id:ukb-b-660
## 3  ieu-b-4760  ukb-b-660 Number of self-reported cancers || id:ukb-b-660
## 4  ieu-b-4760  ukb-b-660 Number of self-reported cancers || id:ukb-b-660
## 5  ieu-b-4760  ukb-b-660 Number of self-reported cancers || id:ukb-b-660
##                              exposure                    method nsnp
## 1 Number of children || id:ieu-b-4760                  MR Egger    8
## 2 Number of children || id:ieu-b-4760           Weighted median    8
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8
## 4 Number of children || id:ieu-b-4760               Simple mode    8
## 5 Number of children || id:ieu-b-4760             Weighted mode    8
##              b         se       pval
## 1 -0.172055738 0.28253540 0.56487308
## 2 -0.044169325 0.02501436 0.07743636
## 3 -0.058180023 0.04601184 0.20606584
## 4 -0.001677668 0.03568908 0.96381997
## 5 -0.016587154 0.02936666 0.58982350
mr_scatter_plot(d_mr,d)
## $`ieu-b-4760.ukb-b-660`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ieu-b-4760  ukb-b-660

Eyes

Age started wearing glasses or contact lenses

d <- make_dat("ukb-b-5801", "ieu-b-4760")
## Extracting data for 84 SNP(s) from 1 GWAS(s)
## Finding proxies for 7 SNPs in outcome ieu-b-4760
## Extracting data for 7 SNP(s) from 1 GWAS(s)
## Harmonising Age started wearing glasses or contact lenses || id:ukb-b-5801 (ukb-b-5801) and Number of children || id:ieu-b-4760 (ieu-b-4760)
d_mr<-mr(d)
## Analysing 'ukb-b-5801' on 'ieu-b-4760'
d_mr
##   id.exposure id.outcome                             outcome
## 1  ukb-b-5801 ieu-b-4760 Number of children || id:ieu-b-4760
## 2  ukb-b-5801 ieu-b-4760 Number of children || id:ieu-b-4760
## 3  ukb-b-5801 ieu-b-4760 Number of children || id:ieu-b-4760
## 4  ukb-b-5801 ieu-b-4760 Number of children || id:ieu-b-4760
## 5  ukb-b-5801 ieu-b-4760 Number of children || id:ieu-b-4760
##                                                         exposure
## 1 Age started wearing glasses or contact lenses || id:ukb-b-5801
## 2 Age started wearing glasses or contact lenses || id:ukb-b-5801
## 3 Age started wearing glasses or contact lenses || id:ukb-b-5801
## 4 Age started wearing glasses or contact lenses || id:ukb-b-5801
## 5 Age started wearing glasses or contact lenses || id:ukb-b-5801
##                      method nsnp          b         se         pval
## 1                  MR Egger   83 0.02711594 0.06295694 0.6678260126
## 2           Weighted median   83 0.07338842 0.02315684 0.0015286420
## 3 Inverse variance weighted   83 0.08315212 0.02332925 0.0003648489
## 4               Simple mode   83 0.06461289 0.05740728 0.2636533575
## 5             Weighted mode   83 0.09058136 0.03701802 0.0165437238
mr_scatter_plot(d_mr,d)
## $`ukb-b-5801.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-5801 ieu-b-4760
d <- make_dat("ieu-b-4760", "ukb-b-5801")
## Extracting data for 9 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ukb-b-5801
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Age started wearing glasses or contact lenses || id:ukb-b-5801 (ukb-b-5801)
d_mr<-mr(d)
## Analysing 'ieu-b-4760' on 'ukb-b-5801'
d_mr
##   id.exposure id.outcome
## 1  ieu-b-4760 ukb-b-5801
## 2  ieu-b-4760 ukb-b-5801
## 3  ieu-b-4760 ukb-b-5801
## 4  ieu-b-4760 ukb-b-5801
## 5  ieu-b-4760 ukb-b-5801
##                                                          outcome
## 1 Age started wearing glasses or contact lenses || id:ukb-b-5801
## 2 Age started wearing glasses or contact lenses || id:ukb-b-5801
## 3 Age started wearing glasses or contact lenses || id:ukb-b-5801
## 4 Age started wearing glasses or contact lenses || id:ukb-b-5801
## 5 Age started wearing glasses or contact lenses || id:ukb-b-5801
##                              exposure                    method nsnp         b
## 1 Number of children || id:ieu-b-4760                  MR Egger    8 2.0096112
## 2 Number of children || id:ieu-b-4760           Weighted median    8 0.2782385
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8 0.3452397
## 4 Number of children || id:ieu-b-4760               Simple mode    8 0.2003019
## 5 Number of children || id:ieu-b-4760             Weighted mode    8 0.1689255
##          se         pval
## 1 0.3335580 0.0009438956
## 2 0.1011458 0.0059438078
## 3 0.1216923 0.0045541140
## 4 0.1729509 0.2847878703
## 5 0.1850051 0.3915605244
mr_scatter_plot(d_mr,d)
## $`ieu-b-4760.ukb-b-5801`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ieu-b-4760 ukb-b-5801

Spherical power (right)

d <- make_dat("ukb-b-19994", "ieu-b-4760")
## Extracting data for 142 SNP(s) from 1 GWAS(s)
## Finding proxies for 4 SNPs in outcome ieu-b-4760
## Extracting data for 4 SNP(s) from 1 GWAS(s)
## Harmonising Spherical power (right) || id:ukb-b-19994 (ukb-b-19994) and Number of children || id:ieu-b-4760 (ieu-b-4760)
d_mr<-mr(d)
## Analysing 'ukb-b-19994' on 'ieu-b-4760'
d_mr
##   id.exposure id.outcome                             outcome
## 1 ukb-b-19994 ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-b-19994 ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-b-19994 ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-b-19994 ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-b-19994 ieu-b-4760 Number of children || id:ieu-b-4760
##                                    exposure                    method nsnp
## 1 Spherical power (right) || id:ukb-b-19994                  MR Egger  141
## 2 Spherical power (right) || id:ukb-b-19994           Weighted median  141
## 3 Spherical power (right) || id:ukb-b-19994 Inverse variance weighted  141
## 4 Spherical power (right) || id:ukb-b-19994               Simple mode  141
## 5 Spherical power (right) || id:ukb-b-19994             Weighted mode  141
##              b          se        pval
## 1 -0.004801612 0.015979125 0.764250267
## 2  0.009450912 0.007935597 0.233672589
## 3  0.019220235 0.006061735 0.001520468
## 4 -0.002982299 0.021761546 0.891192559
## 5 -0.002982299 0.015504055 0.847742059
mr_scatter_plot(d_mr,d)
## $`ukb-b-19994.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1 ukb-b-19994 ieu-b-4760
d <- make_dat("ieu-b-4760", "ukb-b-19994")
## Extracting data for 9 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ukb-b-19994
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Spherical power (right) || id:ukb-b-19994 (ukb-b-19994)
d_mr<-mr(d)
## Analysing 'ieu-b-4760' on 'ukb-b-19994'
d_mr
##   id.exposure  id.outcome                                   outcome
## 1  ieu-b-4760 ukb-b-19994 Spherical power (right) || id:ukb-b-19994
## 2  ieu-b-4760 ukb-b-19994 Spherical power (right) || id:ukb-b-19994
## 3  ieu-b-4760 ukb-b-19994 Spherical power (right) || id:ukb-b-19994
## 4  ieu-b-4760 ukb-b-19994 Spherical power (right) || id:ukb-b-19994
## 5  ieu-b-4760 ukb-b-19994 Spherical power (right) || id:ukb-b-19994
##                              exposure                    method nsnp         b
## 1 Number of children || id:ieu-b-4760                  MR Egger    8 1.1149188
## 2 Number of children || id:ieu-b-4760           Weighted median    8 0.8323719
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8 0.8123337
## 4 Number of children || id:ieu-b-4760               Simple mode    8 0.7423016
## 5 Number of children || id:ieu-b-4760             Weighted mode    8 0.8281055
##          se         pval
## 1 1.3486002 4.400256e-01
## 2 0.1702550 1.013639e-06
## 3 0.2175810 1.888545e-04
## 4 0.2531901 2.196808e-02
## 5 0.2029278 4.685028e-03
mr_scatter_plot(d_mr,d)
## $`ieu-b-4760.ukb-b-19994`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure  id.outcome
## 1  ieu-b-4760 ukb-b-19994

Blood

Haematocrit percentage

d <- make_dat("ukb-d-30030_irnt", "ieu-b-4760")
## Extracting data for 274 SNP(s) from 1 GWAS(s)
## Finding proxies for 60 SNPs in outcome ieu-b-4760
## Extracting data for 60 SNP(s) from 1 GWAS(s)
## Harmonising Haematocrit percentage || id:ukb-d-30030_irnt (ukb-d-30030_irnt) and Number of children || id:ieu-b-4760 (ieu-b-4760)
## Removing the following SNPs for incompatible alleles:
## rs8070692
d_mr<-mr(d)
## Analysing 'ukb-d-30030_irnt' on 'ieu-b-4760'
d_mr
##        id.exposure id.outcome                             outcome
## 1 ukb-d-30030_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-d-30030_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-d-30030_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-d-30030_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-d-30030_irnt ieu-b-4760 Number of children || id:ieu-b-4760
##                                        exposure                    method nsnp
## 1 Haematocrit percentage || id:ukb-d-30030_irnt                  MR Egger  236
## 2 Haematocrit percentage || id:ukb-d-30030_irnt           Weighted median  236
## 3 Haematocrit percentage || id:ukb-d-30030_irnt Inverse variance weighted  236
## 4 Haematocrit percentage || id:ukb-d-30030_irnt               Simple mode  236
## 5 Haematocrit percentage || id:ukb-d-30030_irnt             Weighted mode  236
##             b          se      pval
## 1 -0.00320144 0.017915339 0.8583293
## 2  0.01617213 0.013002407 0.2135807
## 3  0.01879354 0.008912533 0.0349736
## 4  0.02580420 0.032482865 0.4277675
## 5  0.01603585 0.017524003 0.3610882
mr_scatter_plot(d_mr,d)
## $`ukb-d-30030_irnt.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##        id.exposure id.outcome
## 1 ukb-d-30030_irnt ieu-b-4760
d <- make_dat("ieu-b-4760", "ukb-d-30030_irnt")
## Extracting data for 9 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ukb-d-30030_irnt
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Haematocrit percentage || id:ukb-d-30030_irnt (ukb-d-30030_irnt)
d_mr<-mr(d)
## Analysing 'ieu-b-4760' on 'ukb-d-30030_irnt'
d_mr
##   id.exposure       id.outcome                                       outcome
## 1  ieu-b-4760 ukb-d-30030_irnt Haematocrit percentage || id:ukb-d-30030_irnt
## 2  ieu-b-4760 ukb-d-30030_irnt Haematocrit percentage || id:ukb-d-30030_irnt
## 3  ieu-b-4760 ukb-d-30030_irnt Haematocrit percentage || id:ukb-d-30030_irnt
## 4  ieu-b-4760 ukb-d-30030_irnt Haematocrit percentage || id:ukb-d-30030_irnt
## 5  ieu-b-4760 ukb-d-30030_irnt Haematocrit percentage || id:ukb-d-30030_irnt
##                              exposure                    method nsnp
## 1 Number of children || id:ieu-b-4760                  MR Egger    8
## 2 Number of children || id:ieu-b-4760           Weighted median    8
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8
## 4 Number of children || id:ieu-b-4760               Simple mode    8
## 5 Number of children || id:ieu-b-4760             Weighted mode    8
##             b         se      pval
## 1 -0.65989788 1.62701058 0.6991114
## 2  0.08144968 0.07139143 0.2539162
## 3  0.26616779 0.26831867 0.3212054
## 4  0.11395100 0.09668801 0.2770852
## 5  0.03959475 0.08639759 0.6606356
mr_scatter_plot(d_mr,d)
## $`ieu-b-4760.ukb-d-30030_irnt`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure       id.outcome
## 1  ieu-b-4760 ukb-d-30030_irnt

High light scatter reticulocyte count

d <- make_dat("ukb-d-30300_irnt", "ieu-b-4760")
## Extracting data for 309 SNP(s) from 1 GWAS(s)
## Finding proxies for 63 SNPs in outcome ieu-b-4760
## Extracting data for 63 SNP(s) from 1 GWAS(s)
## Harmonising High light scatter reticulocyte count || id:ukb-d-30300_irnt (ukb-d-30300_irnt) and Number of children || id:ieu-b-4760 (ieu-b-4760)
d_mr<-mr(d)
## Analysing 'ukb-d-30300_irnt' on 'ieu-b-4760'
d_mr
##        id.exposure id.outcome                             outcome
## 1 ukb-d-30300_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-d-30300_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-d-30300_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-d-30300_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-d-30300_irnt ieu-b-4760 Number of children || id:ieu-b-4760
##                                                       exposure
## 1 High light scatter reticulocyte count || id:ukb-d-30300_irnt
## 2 High light scatter reticulocyte count || id:ukb-d-30300_irnt
## 3 High light scatter reticulocyte count || id:ukb-d-30300_irnt
## 4 High light scatter reticulocyte count || id:ukb-d-30300_irnt
## 5 High light scatter reticulocyte count || id:ukb-d-30300_irnt
##                      method nsnp           b          se        pval
## 1                  MR Egger  272 0.009767459 0.010429280 0.349831110
## 2           Weighted median  272 0.016371879 0.008771920 0.061985951
## 3 Inverse variance weighted  272 0.015183400 0.005866493 0.009649122
## 4               Simple mode  272 0.047662787 0.019051654 0.012947496
## 5             Weighted mode  272 0.018500304 0.008823001 0.036935803
mr_scatter_plot(d_mr,d)
## $`ukb-d-30300_irnt.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##        id.exposure id.outcome
## 1 ukb-d-30300_irnt ieu-b-4760
d <- make_dat("ieu-b-4760", "ukb-d-30300_irnt")
## Extracting data for 9 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ukb-d-30300_irnt
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and High light scatter reticulocyte count || id:ukb-d-30300_irnt (ukb-d-30300_irnt)
d_mr<-mr(d)
## Analysing 'ieu-b-4760' on 'ukb-d-30300_irnt'
d_mr
##   id.exposure       id.outcome
## 1  ieu-b-4760 ukb-d-30300_irnt
## 2  ieu-b-4760 ukb-d-30300_irnt
## 3  ieu-b-4760 ukb-d-30300_irnt
## 4  ieu-b-4760 ukb-d-30300_irnt
## 5  ieu-b-4760 ukb-d-30300_irnt
##                                                        outcome
## 1 High light scatter reticulocyte count || id:ukb-d-30300_irnt
## 2 High light scatter reticulocyte count || id:ukb-d-30300_irnt
## 3 High light scatter reticulocyte count || id:ukb-d-30300_irnt
## 4 High light scatter reticulocyte count || id:ukb-d-30300_irnt
## 5 High light scatter reticulocyte count || id:ukb-d-30300_irnt
##                              exposure                    method nsnp
## 1 Number of children || id:ieu-b-4760                  MR Egger    8
## 2 Number of children || id:ieu-b-4760           Weighted median    8
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8
## 4 Number of children || id:ieu-b-4760               Simple mode    8
## 5 Number of children || id:ieu-b-4760             Weighted mode    8
##              b         se      pval
## 1 -0.655128337 1.85835308 0.7364926
## 2  0.066223250 0.09829255 0.5004790
## 3  0.264383290 0.30449263 0.3852439
## 4 -0.097819791 0.12089475 0.4450665
## 5 -0.007763387 0.09424809 0.9366570
mr_scatter_plot(d_mr,d)
## $`ieu-b-4760.ukb-d-30300_irnt`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure       id.outcome
## 1  ieu-b-4760 ukb-d-30300_irnt

High light scatter reticulocyte percentage

d <- make_dat("ukb-d-30290_irnt", "ieu-b-4760")
## Extracting data for 317 SNP(s) from 1 GWAS(s)
## Finding proxies for 67 SNPs in outcome ieu-b-4760
## Extracting data for 67 SNP(s) from 1 GWAS(s)
## Harmonising High light scatter reticulocyte percentage || id:ukb-d-30290_irnt (ukb-d-30290_irnt) and Number of children || id:ieu-b-4760 (ieu-b-4760)
d_mr<-mr(d)
## Analysing 'ukb-d-30290_irnt' on 'ieu-b-4760'
d_mr
##        id.exposure id.outcome                             outcome
## 1 ukb-d-30290_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-d-30290_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-d-30290_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-d-30290_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-d-30290_irnt ieu-b-4760 Number of children || id:ieu-b-4760
##                                                            exposure
## 1 High light scatter reticulocyte percentage || id:ukb-d-30290_irnt
## 2 High light scatter reticulocyte percentage || id:ukb-d-30290_irnt
## 3 High light scatter reticulocyte percentage || id:ukb-d-30290_irnt
## 4 High light scatter reticulocyte percentage || id:ukb-d-30290_irnt
## 5 High light scatter reticulocyte percentage || id:ukb-d-30290_irnt
##                      method nsnp           b          se       pval
## 1                  MR Egger  278  0.00937759 0.009757336 0.33735266
## 2           Weighted median  278  0.01608313 0.008472734 0.05766679
## 3 Inverse variance weighted  278  0.01161524 0.005522376 0.03543920
## 4               Simple mode  278 -0.02709323 0.018597350 0.14629522
## 5             Weighted mode  278  0.01798072 0.008599050 0.03743807
mr_scatter_plot(d_mr,d)
## $`ukb-d-30290_irnt.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##        id.exposure id.outcome
## 1 ukb-d-30290_irnt ieu-b-4760
d <- make_dat("ieu-b-4760", "ukb-d-30290_irnt")
## Extracting data for 9 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ukb-d-30290_irnt
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and High light scatter reticulocyte percentage || id:ukb-d-30290_irnt (ukb-d-30290_irnt)
d_mr<-mr(d)
## Analysing 'ieu-b-4760' on 'ukb-d-30290_irnt'
d_mr
##   id.exposure       id.outcome
## 1  ieu-b-4760 ukb-d-30290_irnt
## 2  ieu-b-4760 ukb-d-30290_irnt
## 3  ieu-b-4760 ukb-d-30290_irnt
## 4  ieu-b-4760 ukb-d-30290_irnt
## 5  ieu-b-4760 ukb-d-30290_irnt
##                                                             outcome
## 1 High light scatter reticulocyte percentage || id:ukb-d-30290_irnt
## 2 High light scatter reticulocyte percentage || id:ukb-d-30290_irnt
## 3 High light scatter reticulocyte percentage || id:ukb-d-30290_irnt
## 4 High light scatter reticulocyte percentage || id:ukb-d-30290_irnt
## 5 High light scatter reticulocyte percentage || id:ukb-d-30290_irnt
##                              exposure                    method nsnp
## 1 Number of children || id:ieu-b-4760                  MR Egger    8
## 2 Number of children || id:ieu-b-4760           Weighted median    8
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8
## 4 Number of children || id:ieu-b-4760               Simple mode    8
## 5 Number of children || id:ieu-b-4760             Weighted mode    8
##             b         se      pval
## 1 -0.52640674 1.59252833 0.7522235
## 2  0.10462590 0.10294563 0.3094761
## 3  0.23352812 0.26057047 0.3701360
## 4 -0.08193586 0.11591079 0.5024823
## 5  0.01287495 0.09193914 0.8925744
mr_scatter_plot(d_mr,d)
## $`ieu-b-4760.ukb-d-30290_irnt`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure       id.outcome
## 1  ieu-b-4760 ukb-d-30290_irnt

Reticulocyte count

d <- make_dat("ukb-d-30250_irnt", "ieu-b-4760")
## Extracting data for 291 SNP(s) from 1 GWAS(s)
## Finding proxies for 55 SNPs in outcome ieu-b-4760
## Extracting data for 55 SNP(s) from 1 GWAS(s)
## Harmonising Reticulocyte count || id:ukb-d-30250_irnt (ukb-d-30250_irnt) and Number of children || id:ieu-b-4760 (ieu-b-4760)
d_mr<-mr(d)
## Analysing 'ukb-d-30250_irnt' on 'ieu-b-4760'
d_mr
##        id.exposure id.outcome                             outcome
## 1 ukb-d-30250_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-d-30250_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-d-30250_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-d-30250_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-d-30250_irnt ieu-b-4760 Number of children || id:ieu-b-4760
##                                    exposure                    method nsnp
## 1 Reticulocyte count || id:ukb-d-30250_irnt                  MR Egger  254
## 2 Reticulocyte count || id:ukb-d-30250_irnt           Weighted median  254
## 3 Reticulocyte count || id:ukb-d-30250_irnt Inverse variance weighted  254
## 4 Reticulocyte count || id:ukb-d-30250_irnt               Simple mode  254
## 5 Reticulocyte count || id:ukb-d-30250_irnt             Weighted mode  254
##             b          se       pval
## 1 0.006651743 0.010536133 0.52839910
## 2 0.017530653 0.008855124 0.04773515
## 3 0.012237878 0.006022629 0.04215541
## 4 0.002504768 0.019507216 0.89793275
## 5 0.011951065 0.009102348 0.19038439
mr_scatter_plot(d_mr,d)
## $`ukb-d-30250_irnt.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##        id.exposure id.outcome
## 1 ukb-d-30250_irnt ieu-b-4760
d <- make_dat("ieu-b-4760", "ukb-d-30250_irnt")
## Extracting data for 9 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ukb-d-30250_irnt
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Reticulocyte count || id:ukb-d-30250_irnt (ukb-d-30250_irnt)
d_mr<-mr(d)
## Analysing 'ieu-b-4760' on 'ukb-d-30250_irnt'
d_mr
##   id.exposure       id.outcome                                   outcome
## 1  ieu-b-4760 ukb-d-30250_irnt Reticulocyte count || id:ukb-d-30250_irnt
## 2  ieu-b-4760 ukb-d-30250_irnt Reticulocyte count || id:ukb-d-30250_irnt
## 3  ieu-b-4760 ukb-d-30250_irnt Reticulocyte count || id:ukb-d-30250_irnt
## 4  ieu-b-4760 ukb-d-30250_irnt Reticulocyte count || id:ukb-d-30250_irnt
## 5  ieu-b-4760 ukb-d-30250_irnt Reticulocyte count || id:ukb-d-30250_irnt
##                              exposure                    method nsnp
## 1 Number of children || id:ieu-b-4760                  MR Egger    8
## 2 Number of children || id:ieu-b-4760           Weighted median    8
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8
## 4 Number of children || id:ieu-b-4760               Simple mode    8
## 5 Number of children || id:ieu-b-4760             Weighted mode    8
##              b         se      pval
## 1 -0.452069886 1.84937718 0.8150314
## 2 -0.009805031 0.09243730 0.9155250
## 3  0.248863581 0.30048315 0.4075508
## 4 -0.078441014 0.12106272 0.5376899
## 5 -0.002504102 0.09072677 0.9787512
mr_scatter_plot(d_mr,d)
## $`ieu-b-4760.ukb-d-30250_irnt`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure       id.outcome
## 1  ieu-b-4760 ukb-d-30250_irnt

SHBG

d <- make_dat("ukb-d-30830_irnt", "ieu-b-4760")
## Extracting data for 264 SNP(s) from 1 GWAS(s)
## Finding proxies for 46 SNPs in outcome ieu-b-4760
## Extracting data for 46 SNP(s) from 1 GWAS(s)
## Harmonising SHBG || id:ukb-d-30830_irnt (ukb-d-30830_irnt) and Number of children || id:ieu-b-4760 (ieu-b-4760)
d_mr<-mr(d)
## Analysing 'ukb-d-30830_irnt' on 'ieu-b-4760'
d_mr
##        id.exposure id.outcome                             outcome
## 1 ukb-d-30830_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-d-30830_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-d-30830_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-d-30830_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-d-30830_irnt ieu-b-4760 Number of children || id:ieu-b-4760
##                      exposure                    method nsnp            b
## 1 SHBG || id:ukb-d-30830_irnt                  MR Egger  243 -0.010477449
## 2 SHBG || id:ukb-d-30830_irnt           Weighted median  243 -0.001979962
## 3 SHBG || id:ukb-d-30830_irnt Inverse variance weighted  243 -0.012677536
## 4 SHBG || id:ukb-d-30830_irnt               Simple mode  243 -0.011576918
## 5 SHBG || id:ukb-d-30830_irnt             Weighted mode  243 -0.007299222
##            se       pval
## 1 0.009574560 0.27491557
## 2 0.008134028 0.80768228
## 3 0.006144521 0.03909116
## 4 0.018757861 0.53769833
## 5 0.007129196 0.30692880
mr_scatter_plot(d_mr,d)
## $`ukb-d-30830_irnt.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##        id.exposure id.outcome
## 1 ukb-d-30830_irnt ieu-b-4760
d <- make_dat("ieu-b-4760", "ukb-d-30830_irnt")
## Extracting data for 9 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ukb-d-30830_irnt
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and SHBG || id:ukb-d-30830_irnt (ukb-d-30830_irnt)
d_mr<-mr(d)
## Analysing 'ieu-b-4760' on 'ukb-d-30830_irnt'
d_mr
##   id.exposure       id.outcome                     outcome
## 1  ieu-b-4760 ukb-d-30830_irnt SHBG || id:ukb-d-30830_irnt
## 2  ieu-b-4760 ukb-d-30830_irnt SHBG || id:ukb-d-30830_irnt
## 3  ieu-b-4760 ukb-d-30830_irnt SHBG || id:ukb-d-30830_irnt
## 4  ieu-b-4760 ukb-d-30830_irnt SHBG || id:ukb-d-30830_irnt
## 5  ieu-b-4760 ukb-d-30830_irnt SHBG || id:ukb-d-30830_irnt
##                              exposure                    method nsnp
## 1 Number of children || id:ieu-b-4760                  MR Egger    8
## 2 Number of children || id:ieu-b-4760           Weighted median    8
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8
## 4 Number of children || id:ieu-b-4760               Simple mode    8
## 5 Number of children || id:ieu-b-4760             Weighted mode    8
##             b         se      pval
## 1  0.52222436 1.00478413 0.6218559
## 2 -0.02229886 0.08406413 0.7908091
## 3 -0.01932547 0.16524136 0.9068973
## 4 -0.04523900 0.11388170 0.7030204
## 5 -0.03373937 0.08716145 0.7101886
mr_scatter_plot(d_mr,d)
## $`ieu-b-4760.ukb-d-30830_irnt`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure       id.outcome
## 1  ieu-b-4760 ukb-d-30830_irnt

IGF-1

d <- make_dat("ukb-d-30770_irnt", "ieu-b-4760")
## Extracting data for 364 SNP(s) from 1 GWAS(s)
## Finding proxies for 88 SNPs in outcome ieu-b-4760
## Extracting data for 88 SNP(s) from 1 GWAS(s)
## Harmonising IGF-1 || id:ukb-d-30770_irnt (ukb-d-30770_irnt) and Number of children || id:ieu-b-4760 (ieu-b-4760)
## Removing the following SNPs for incompatible alleles:
## rs2925656
d_mr<-mr(d)
## Analysing 'ukb-d-30770_irnt' on 'ieu-b-4760'
d_mr
##        id.exposure id.outcome                             outcome
## 1 ukb-d-30770_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 2 ukb-d-30770_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 3 ukb-d-30770_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 4 ukb-d-30770_irnt ieu-b-4760 Number of children || id:ieu-b-4760
## 5 ukb-d-30770_irnt ieu-b-4760 Number of children || id:ieu-b-4760
##                       exposure                    method nsnp          b
## 1 IGF-1 || id:ukb-d-30770_irnt                  MR Egger  318 0.02529644
## 2 IGF-1 || id:ukb-d-30770_irnt           Weighted median  318 0.01319453
## 3 IGF-1 || id:ukb-d-30770_irnt Inverse variance weighted  318 0.01850997
## 4 IGF-1 || id:ukb-d-30770_irnt               Simple mode  318 0.01054868
## 5 IGF-1 || id:ukb-d-30770_irnt             Weighted mode  318 0.01054868
##            se        pval
## 1 0.012202944 0.038984480
## 2 0.008457788 0.118749347
## 3 0.006372038 0.003674009
## 4 0.021427027 0.622843099
## 5 0.010728235 0.326227895
mr_scatter_plot(d_mr,d)
## $`ukb-d-30770_irnt.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##        id.exposure id.outcome
## 1 ukb-d-30770_irnt ieu-b-4760
d <- make_dat("ieu-b-4760", "ukb-d-30770_irnt")
## Extracting data for 9 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ukb-d-30770_irnt
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and IGF-1 || id:ukb-d-30770_irnt (ukb-d-30770_irnt)
d_mr<-mr(d)
## Analysing 'ieu-b-4760' on 'ukb-d-30770_irnt'
d_mr
##   id.exposure       id.outcome                      outcome
## 1  ieu-b-4760 ukb-d-30770_irnt IGF-1 || id:ukb-d-30770_irnt
## 2  ieu-b-4760 ukb-d-30770_irnt IGF-1 || id:ukb-d-30770_irnt
## 3  ieu-b-4760 ukb-d-30770_irnt IGF-1 || id:ukb-d-30770_irnt
## 4  ieu-b-4760 ukb-d-30770_irnt IGF-1 || id:ukb-d-30770_irnt
## 5  ieu-b-4760 ukb-d-30770_irnt IGF-1 || id:ukb-d-30770_irnt
##                              exposure                    method nsnp
## 1 Number of children || id:ieu-b-4760                  MR Egger    8
## 2 Number of children || id:ieu-b-4760           Weighted median    8
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8
## 4 Number of children || id:ieu-b-4760               Simple mode    8
## 5 Number of children || id:ieu-b-4760             Weighted mode    8
##             b        se      pval
## 1 -0.33902249 1.1628812 0.7804576
## 2 -0.01057685 0.1001765 0.9159138
## 3  0.17504312 0.1897768 0.3563392
## 4  0.04155000 0.1641582 0.8074560
## 5 -0.11547339 0.1017823 0.2939310
mr_scatter_plot(d_mr,d)
## $`ieu-b-4760.ukb-d-30770_irnt`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure       id.outcome
## 1  ieu-b-4760 ukb-d-30770_irnt

Lungs

Forced vital capacity (FVC)

d <- make_dat("ukb-b-7953", "ieu-b-4760")
## Extracting data for 320 SNP(s) from 1 GWAS(s)
## Finding proxies for 26 SNPs in outcome ieu-b-4760
## Extracting data for 26 SNP(s) from 1 GWAS(s)
## Harmonising Forced vital capacity (FVC) || id:ukb-b-7953 (ukb-b-7953) and Number of children || id:ieu-b-4760 (ieu-b-4760)
## Removing the following SNPs for incompatible alleles:
## rs1040457, rs11191818
d_mr<-mr(d)
## Analysing 'ukb-b-7953' on 'ieu-b-4760'
d_mr
##   id.exposure id.outcome                             outcome
## 1  ukb-b-7953 ieu-b-4760 Number of children || id:ieu-b-4760
## 2  ukb-b-7953 ieu-b-4760 Number of children || id:ieu-b-4760
## 3  ukb-b-7953 ieu-b-4760 Number of children || id:ieu-b-4760
## 4  ukb-b-7953 ieu-b-4760 Number of children || id:ieu-b-4760
## 5  ukb-b-7953 ieu-b-4760 Number of children || id:ieu-b-4760
##                                       exposure                    method nsnp
## 1 Forced vital capacity (FVC) || id:ukb-b-7953                  MR Egger  310
## 2 Forced vital capacity (FVC) || id:ukb-b-7953           Weighted median  310
## 3 Forced vital capacity (FVC) || id:ukb-b-7953 Inverse variance weighted  310
## 4 Forced vital capacity (FVC) || id:ukb-b-7953               Simple mode  310
## 5 Forced vital capacity (FVC) || id:ukb-b-7953             Weighted mode  310
##             b         se      pval
## 1 -0.06305924 0.03272854 0.0549324
## 2 -0.02250207 0.01556873 0.1483631
## 3 -0.02754133 0.01191602 0.0208171
## 4 -0.02097514 0.04865678 0.6667082
## 5 -0.02097514 0.03666140 0.5676489
mr_scatter_plot(d_mr,d)
## $`ukb-b-7953.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ukb-b-7953 ieu-b-4760
d <- make_dat("ieu-b-4760", "ukb-b-7953")
## Extracting data for 9 SNP(s) from 1 GWAS(s)
## Finding proxies for 1 SNPs in outcome ukb-b-7953
## Extracting data for 1 SNP(s) from 1 GWAS(s)
## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and Forced vital capacity (FVC) || id:ukb-b-7953 (ukb-b-7953)
d_mr<-mr(d)
## Analysing 'ieu-b-4760' on 'ukb-b-7953'
d_mr
##   id.exposure id.outcome                                      outcome
## 1  ieu-b-4760 ukb-b-7953 Forced vital capacity (FVC) || id:ukb-b-7953
## 2  ieu-b-4760 ukb-b-7953 Forced vital capacity (FVC) || id:ukb-b-7953
## 3  ieu-b-4760 ukb-b-7953 Forced vital capacity (FVC) || id:ukb-b-7953
## 4  ieu-b-4760 ukb-b-7953 Forced vital capacity (FVC) || id:ukb-b-7953
## 5  ieu-b-4760 ukb-b-7953 Forced vital capacity (FVC) || id:ukb-b-7953
##                              exposure                    method nsnp          b
## 1 Number of children || id:ieu-b-4760                  MR Egger    8  0.4722276
## 2 Number of children || id:ieu-b-4760           Weighted median    8  0.1186476
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    8 -0.1265329
## 4 Number of children || id:ieu-b-4760               Simple mode    8  0.1598594
## 5 Number of children || id:ieu-b-4760             Weighted mode    8  0.1450353
##           se       pval
## 1 1.47942221 0.76039750
## 2 0.06508382 0.06830396
## 3 0.24093481 0.59946168
## 4 0.09506806 0.13654434
## 5 0.07112622 0.08081701
mr_scatter_plot(d_mr,d)
## $`ieu-b-4760.ukb-b-7953`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ieu-b-4760 ukb-b-7953

FVC

d <- make_dat("ieu-b-105", "ieu-b-4760")
## Extracting data for 297 SNP(s) from 1 GWAS(s)
## Finding proxies for 31 SNPs in outcome ieu-b-4760
## Extracting data for 31 SNP(s) from 1 GWAS(s)
## Harmonising FVC || id:ieu-b-105 (ieu-b-105) and Number of children || id:ieu-b-4760 (ieu-b-4760)
## Removing the following SNPs for incompatible alleles:
## rs11191818
d_mr<-mr(d)
## Analysing 'ieu-b-105' on 'ieu-b-4760'
d_mr
##   id.exposure id.outcome                             outcome
## 1   ieu-b-105 ieu-b-4760 Number of children || id:ieu-b-4760
## 2   ieu-b-105 ieu-b-4760 Number of children || id:ieu-b-4760
## 3   ieu-b-105 ieu-b-4760 Number of children || id:ieu-b-4760
## 4   ieu-b-105 ieu-b-4760 Number of children || id:ieu-b-4760
## 5   ieu-b-105 ieu-b-4760 Number of children || id:ieu-b-4760
##              exposure                    method nsnp            b         se
## 1 FVC || id:ieu-b-105                  MR Egger  273 -0.056808812 0.02986531
## 2 FVC || id:ieu-b-105           Weighted median  273 -0.019445091 0.01425703
## 3 FVC || id:ieu-b-105 Inverse variance weighted  273 -0.026500029 0.01117220
## 4 FVC || id:ieu-b-105               Simple mode  273 -0.005330928 0.04278782
## 5 FVC || id:ieu-b-105             Weighted mode  273 -0.017847870 0.03205276
##         pval
## 1 0.05820941
## 2 0.17260078
## 3 0.01769395
## 4 0.90094029
## 5 0.57810285
mr_scatter_plot(d_mr,d)
## $`ieu-b-105.ieu-b-4760`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1   ieu-b-105 ieu-b-4760
d <- make_dat("ieu-b-4760", "ieu-b-105")
## Extracting data for 9 SNP(s) from 1 GWAS(s)
## Harmonising Number of children || id:ieu-b-4760 (ieu-b-4760) and FVC || id:ieu-b-105 (ieu-b-105)
d_mr<-mr(d)
## Analysing 'ieu-b-4760' on 'ieu-b-105'
d_mr
##   id.exposure id.outcome             outcome
## 1  ieu-b-4760  ieu-b-105 FVC || id:ieu-b-105
## 2  ieu-b-4760  ieu-b-105 FVC || id:ieu-b-105
## 3  ieu-b-4760  ieu-b-105 FVC || id:ieu-b-105
## 4  ieu-b-4760  ieu-b-105 FVC || id:ieu-b-105
## 5  ieu-b-4760  ieu-b-105 FVC || id:ieu-b-105
##                              exposure                    method nsnp
## 1 Number of children || id:ieu-b-4760                  MR Egger    9
## 2 Number of children || id:ieu-b-4760           Weighted median    9
## 3 Number of children || id:ieu-b-4760 Inverse variance weighted    9
## 4 Number of children || id:ieu-b-4760               Simple mode    9
## 5 Number of children || id:ieu-b-4760             Weighted mode    9
##             b         se      pval
## 1  0.38028986 1.34037278 0.7848336
## 2  0.07488030 0.06722850 0.2653574
## 3 -0.17012295 0.21848418 0.4361853
## 4  0.05990326 0.09062069 0.5271654
## 5  0.08520910 0.07102070 0.2645485
mr_scatter_plot(d_mr,d)
## $`ieu-b-4760.ieu-b-105`

## 
## attr(,"split_type")
## [1] "data.frame"
## attr(,"split_labels")
##   id.exposure id.outcome
## 1  ieu-b-4760  ieu-b-105