EWAS report

study: Illumina methylation data
author: Analyst
date: 30 agosto, 2023

Parameters

## $sig.threshold
## [1] 0.000386
## 
## $max.plots
## [1] 1
## 
## $model
## [1] "sva"
## 
## $qq.inflation.method
## [1] "median"
## 
## $practical.threshold
##   cg21566642 
## 8.297569e-26 
## 
## $winsorize.pct
## [1] 0.05
## 
## $outlier.iqr.factor
## [1] NA
## 
## $rlm
## [1] TRUE
## 
## $most.variable
## [1] 50000
## 
## $random.seed
## [1] 20161123
## 
## $sample.size
## [1] 188

Sample characteristics

For continuous or ordinal variables, the “mean” column provides the mean and the “var” column the standard deviation of the variable. For categorical variables, the “mean” column provides the number of samples with the given “value” and the “var” column the percentage of samples with the given “value”.

variable	value	mean	var
variable of interest	never	99	52.7
variable of interest	current	89	47.3
Age		52.73936	11.63027
Sex	F	144	76.6
Sex	M	44	23.4
Bcell		0.06601765	0.02948774
CD4T		0.188321	0.06010949
CD8T		0.1090449	0.04596973
Mono		0.09398571	0.02091805
Neu		0.5042772	0.0978032
NK		0.08488758	0.03298624

Covariate associations

Covariate Age

statistics

var1	var2	F	p-value	R	p-value
variable	Age	0.0001012	0.9919836	-0.0271044	0.7119591

cases

variable	mean	var	n	t.stat	p.value
never	52.74747	156.7621	99	0.0101488	0.9919135
current	52.73034	112.8583	89	-0.0101488	0.9919135

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Covariate Sex

statistics

var1	var2	R	p-value
variable	Sex	0.054606	0.4567064

frequencies

	F	M
never	78	21
current	66	23

enrichment p-values

	F	M
never	0.2820187	0.8215467
current	0.8215467	0.2820187

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Covariate Bcell

statistics

var1	var2	F	p-value	R	p-value
variable	Bcell	0.2366181	0.6272321	-0.1165057	0.1113357

cases

variable	mean	var	n	t.stat	p.value
never	0.0670116	0.0004847	99	0.4746479	0.6357655
current	0.0649121	0.0013056	89	-0.4746479	0.6357655

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Covariate CD4T

statistics

var1	var2	F	p-value	R	p-value
variable	CD4T	1.708011	0.1928572	0.0797971	0.2763471

cases

variable	mean	var	n	t.stat	p.value
never	0.1828989	0.0033585	99	-1.301991	0.1945799
current	0.1943523	0.0038679	89	1.301991	0.1945799

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Covariate CD8T

statistics

var1	var2	F	p-value	R	p-value
variable	CD8T	3.076023	0.0811016	-0.1161131	0.1125543

cases

variable	mean	var	n	t.stat	p.value
never	0.1145895	0.0023595	99	1.766782	0.0789065
current	0.1028774	0.0017899	89	-1.766782	0.0789065

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Covariate Mono

statistics

var1	var2	F	p-value	R	p-value
variable	Mono	6.977278	0.0089576	-0.1655813	0.0231534

cases

variable	mean	var	n	t.stat	p.value
never	0.0977469	0.0004783	99	2.660786	0.0084779
current	0.0898019	0.0003635	89	-2.660786	0.0084779

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Covariate Neu

statistics

var1	var2	F	p-value	R	p-value
variable	Neu	1.790709	0.1824734	0.1221984	0.0948021

cases

variable	mean	var	n	t.stat	p.value
never	0.4952459	0.0088404	99	-1.332769	0.184292
current	0.5143232	0.0102878	89	1.332769	0.184292

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Covariate NK

statistics

var1	var2	F	p-value	R	p-value
variable	NK	7.140693	0.0082045	-0.1695074	0.0200441

cases

variable	mean	var	n	t.stat	p.value
never	0.0908853	0.0013115	99	2.709977	0.0073742
current	0.0782160	0.0007662	89	-2.709977	0.0073742

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QQ plots

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Manhattan plots

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Significant CpG sites

There were 1365 CpG sites with association p-values < 3.86 × 10^-4. These are listed in the file associations.csv.

The following table shows overlaps between associations under different sets of covariates:

	p.value.none	p.value.all	p.value.sva
p.value.none	661	367	114
p.value.all	367	931	135
p.value.sva	114	135	289

Below are the 1 CpG sites with association p-values < 8.2975685 × 10^-26 in the sva regression model.

	chromosome	position	p.value.none	p.value.all	p.value.sva	coefficient.none	coefficient.all	coefficient.sva
cg05575921	chr5	373378	0	0	0	-0.2458808	-0.2451238	-0.1572324

Plots of these sites follow, one for each covariate set. “p[lm]” denotes the p-value obtained using a linear model and “p[beta]” the p-value obtained using beta regression.

CpG site cg05575921

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Selected CpG sites

Number of CpG sites selected: 1.

	chromosome	position	p.value.none	p.value.all	p.value.sva	coefficient.none	coefficient.all	coefficient.sva
cg05575921	chr5	373378	0	0	0	-0.2458808	-0.2451238	-0.1572324

CpG site cg05575921

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R session information

## R version 4.1.3 (2022-03-10)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 19045)
## 
## Matrix products: default
## 
## locale:
## [1] LC_COLLATE=Spanish_Spain.1252  LC_CTYPE=Spanish_Spain.1252    LC_MONETARY=Spanish_Spain.1252 LC_NUMERIC=C                   LC_TIME=Spanish_Spain.1252    
## 
## attached base packages:
## [1] stats4    parallel  stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] karyoploteR_1.20.3    regioneR_1.26.1       GenomicRanges_1.46.1  GenomeInfoDb_1.30.1   IRanges_2.28.0        S4Vectors_0.32.4      ggrepel_0.9.2        
##  [8] qqman_0.1.8           meffil_1.3.6          preprocessCore_1.56.0 SmartSVA_0.1.3        RSpectra_0.16-1       isva_1.9              JADE_2.0-3           
## [15] qvalue_2.26.0         gdsfmt_1.30.0         statmod_1.5.0         quadprog_1.5-8        DNAcopy_1.68.0        fastICA_1.2-3         lme4_1.1-31          
## [22] Matrix_1.5-1          multcomp_1.4-20       TH.data_1.1-1         survival_3.2-13       mvtnorm_1.1-3         matrixStats_0.63.0    markdown_1.4         
## [29] gridExtra_2.3         Cairo_1.6-0           knitr_1.43            reshape2_1.4.4        plyr_1.8.8            ggplot2_3.4.2         sva_3.42.0           
## [36] BiocParallel_1.28.3   genefilter_1.76.0     mgcv_1.8-39           nlme_3.1-155          limma_3.50.3          sandwich_3.0-2        lmtest_0.9-40        
## [43] zoo_1.8-11            MASS_7.3-55           illuminaio_0.36.0     Biobase_2.54.0        BiocGenerics_0.40.0  
## 
## loaded via a namespace (and not attached):
##   [1] backports_1.4.1             Hmisc_5.0-1                 BiocFileCache_2.2.1         lazyeval_0.2.2              splines_4.1.3              
##   [6] digest_0.6.29               ensembldb_2.18.4            htmltools_0.5.4             fansi_1.0.3                 checkmate_2.1.0            
##  [11] magrittr_2.0.3              memoise_2.0.1               BSgenome_1.62.0             cluster_2.1.2               Biostrings_2.62.0          
##  [16] annotate_1.72.0             askpass_1.1                 prettyunits_1.1.1           colorspace_2.1-0            blob_1.2.4                 
##  [21] rappdirs_0.3.3              xfun_0.39                   dplyr_1.1.2                 crayon_1.5.2                RCurl_1.98-1.9             
##  [26] VariantAnnotation_1.40.0    glue_1.6.2                  gtable_0.3.3                zlibbioc_1.40.0             XVector_0.34.0             
##  [31] DelayedArray_0.20.0         scales_1.2.1                bezier_1.1.2                DBI_1.1.3                   edgeR_3.36.0               
##  [36] Rcpp_1.0.9                  htmlTable_2.4.1             xtable_1.8-4                progress_1.2.2              clue_0.3-64                
##  [41] foreign_0.8-82              bit_4.0.5                   Formula_1.2-5               htmlwidgets_1.6.0           httr_1.4.6                 
##  [46] RColorBrewer_1.1-3          calibrate_1.7.7             farver_2.1.1                pkgconfig_2.0.3             XML_3.99-0.13              
##  [51] nnet_7.3-17                 dbplyr_2.3.2                locfit_1.5-9.6              utf8_1.2.2                  labeling_0.4.2             
##  [56] tidyselect_1.2.0            rlang_1.1.1                 AnnotationDbi_1.56.2        munsell_0.5.0               tools_4.1.3                
##  [61] cachem_1.0.6                cli_3.4.1                   generics_0.1.3              RSQLite_2.2.18              evaluate_0.21              
##  [66] stringr_1.5.0               fastmap_1.1.0               yaml_2.3.7                  bit64_4.0.5                 AnnotationFilter_1.18.0    
##  [71] KEGGREST_1.34.0             xml2_1.3.3                  biomaRt_2.50.3              compiler_4.1.3              rstudioapi_0.14            
##  [76] filelock_1.0.2              curl_4.3.3                  png_0.1-8                   tibble_3.2.1                stringi_1.7.6              
##  [81] highr_0.10                  GenomicFeatures_1.46.5      lattice_0.20-45             ProtGenerics_1.26.0         nloptr_2.0.3               
##  [86] vctrs_0.6.3                 pillar_1.9.0                lifecycle_1.0.3             BiocManager_1.30.19         data.table_1.14.8          
##  [91] bitops_1.0-7                rtracklayer_1.54.0          R6_2.5.1                    BiocIO_1.4.0                codetools_0.2-18           
##  [96] dichromat_2.0-0.1           boot_1.3-28                 SummarizedExperiment_1.24.0 openssl_2.0.6               rjson_0.2.21               
## [101] withr_2.5.0                 GenomicAlignments_1.30.0    Rsamtools_2.10.0            GenomeInfoDbData_1.2.7      hms_1.1.3                  
## [106] rpart_4.1.16                grid_4.1.3                  bamsignals_1.26.0           base64_2.0.1                minqa_1.2.5                
## [111] rmarkdown_2.23              MatrixGenerics_1.6.0        biovizBase_1.42.0           base64enc_0.1-3             restfulr_0.0.15