Imputation using MOFA for 2020 Data set

Load libraries

suppressPackageStartupMessages({library(MOFA2)
library(kableExtra)
library(data.table)
library(ggplot2)
library(tidyverse)
library(here)})

Load data and Generate Mofa object

set.seed(1)
knitr::opts_chunk$set(warning = FALSE, message = FALSE)

add_cols <- function(df, cols) {
  add <- cols[!cols %in% names(df)]
  if(length(add) != 0) df[add] <- NA
  return(as.matrix(df[, sort(cols)]))
}

df_source<- readRDS(here("./data/master_normalized_data_challenge2_train_Aug25.RDS"))

metaDf <- df_source[["subject_specimen"]]
metaDf["age_at_boost"] <- as.numeric(round(difftime(metaDf$date_of_boost, metaDf$year_of_birth,units="weeks")/52, 2))

normalizedData <- list()

normalizedData[["abtiter"]] <- as.data.frame(df_source[["abtiter_wide"]]$batchCorrected_data)
normalizedData[["cytof"]] <- as.data.frame(df_source[["pbmc_cell_frequency"]]$batchCorrected_data)
normalizedData[["rnaseq"]] <- as.data.frame(df_source[["pbmc_gene_expression"]]$batchCorrected_data)
normalizedData[["olink"]] <- as.data.frame(df_source[["plasma_cytokine_concentrations"]]$batchCorrected_data)

int_cols <- Reduce(intersect, lapply(normalizedData[c("abtiter", "cytof", "olink")], colnames))
cols <- unique(c(int_cols, colnames(normalizedData[["rnaseq"]])))

dataset_cols <- metaDf[metaDf$dataset=="2020_dataset", ]$specimen_id
cols <- intersect(cols, dataset_cols)

normalizedData[["abtiter"]] <- add_cols(normalizedData[["abtiter"]],  cols)
normalizedData[["cytof"]] <- add_cols(normalizedData[["cytof"]],  cols)
normalizedData[["rnaseq"]] <- add_cols(normalizedData[["rnaseq"]],  cols)
normalizedData[["olink"]] <- add_cols(normalizedData[["olink"]],  cols)

normalizedData[["abtiter"]] <- normalizedData$abtiter[, !duplicated(cols)]
normalizedData[["cytof"]] <- normalizedData$cytof[, !duplicated(cols)]
normalizedData[["rnaseq"]] <- normalizedData$rnaseq[, !duplicated(cols)]

#
MOFAobject <- create_mofa(normalizedData)

## Creating MOFA object from a list of matrices (features as rows, sample as columns)...

Plot multiomic missing values

plot_data_overview(MOFAobject)

metaDf1 <- data.frame(metaDf[metaDf$specimen_id %in% cols, ])
colnames(metaDf1)[colnames(metaDf1)=="specimen_id"] <- "sample"
rownames(metaDf1) <- metaDf1$sample
metaDf1$sample <- as.character(metaDf1$sample)
metaDf1 <- metaDf1[cols,]
samples_metadata(MOFAobject) <- metaDf1

Setting data Options

knitr::opts_chunk$set(warning = FALSE, message = FALSE)

data_opts <- get_default_data_options(MOFAobject)
data_opts

## $scale_views
## [1] FALSE
## 
## $scale_groups
## [1] FALSE
## 
## $center_groups
## [1] TRUE
## 
## $use_float32
## [1] TRUE
## 
## $views
## [1] "abtiter" "cytof"   "rnaseq"  "olink"  
## 
## $groups
## [1] "group1"

Setting model Options

knitr::opts_chunk$set(warning = FALSE, message = FALSE)
model_opts <- get_default_model_options(MOFAobject)
model_opts$num_factors <- 15

model_opts

## $likelihoods
##    abtiter      cytof     rnaseq      olink 
## "gaussian" "gaussian" "gaussian" "gaussian" 
## 
## $num_factors
## [1] 15
## 
## $spikeslab_factors
## [1] FALSE
## 
## $spikeslab_weights
## [1] FALSE
## 
## $ard_factors
## [1] FALSE
## 
## $ard_weights
## [1] TRUE

Setting training Options

knitr::opts_chunk$set(warning = FALSE, message = FALSE)
train_opts <- get_default_training_options(MOFAobject)
train_opts$convergence_mode <- "medium"
train_opts$seed <- 42

train_opts

## $maxiter
## [1] 1000
## 
## $convergence_mode
## [1] "medium"
## 
## $drop_factor_threshold
## [1] -1
## 
## $verbose
## [1] FALSE
## 
## $startELBO
## [1] 1
## 
## $freqELBO
## [1] 5
## 
## $stochastic
## [1] FALSE
## 
## $gpu_mode
## [1] FALSE
## 
## $seed
## [1] 42
## 
## $outfile
## NULL
## 
## $weight_views
## [1] FALSE
## 
## $save_interrupted
## [1] FALSE

Training Model

MOFAobject <- prepare_mofa(MOFAobject,
  data_options = data_opts,
  model_options = model_opts,
  training_options = train_opts
)
MOFAobject <- run_mofa(MOFAobject, outfile=".../MOFA2_2ndChallenge_F40.hdf5", use_basilisk = TRUE)

MOFAobject

## Trained MOFA with the following characteristics: 
##  Number of views: 4 
##  Views names: abtiter cytof rnaseq olink 
##  Number of features (per view): 27 20 10269 30 
##  Number of groups: 1 
##  Groups names: group1 
##  Number of samples (per group): 190 
##  Number of factors: 15

Impute Data

imputed_data <- impute(MOFAobject, views = "all")

Add meta data to Mofa and Imputed objects

metaDf1 <- data.frame(metaDf[metaDf$specimen_id %in% cols, ])
colnames(metaDf1)[colnames(metaDf1)=="specimen_id"] <- "sample"
rownames(metaDf1) <- metaDf1$sample
metaDf1$sample <- as.character(metaDf1$sample)
metaDf1 <- metaDf1[cols,]

samples_metadata(MOFAobject) <- metaDf1
samples_metadata(imputed_data) <- metaDf1

Mofa object

MOFAobject

## Trained MOFA with the following characteristics: 
##  Number of views: 4 
##  Views names: abtiter cytof rnaseq olink 
##  Number of features (per view): 27 20 10269 30 
##  Number of groups: 1 
##  Groups names: group1 
##  Number of samples (per group): 190 
##  Number of factors: 15

slotNames(MOFAobject)

##  [1] "data"               "covariates"         "covariates_warped" 
##  [4] "intercepts"         "imputed_data"       "interpolated_Z"    
##  [7] "samples_metadata"   "features_metadata"  "expectations"      
## [10] "training_stats"     "data_options"       "model_options"     
## [13] "training_options"   "stochastic_options" "mefisto_options"   
## [16] "dimensions"         "on_disk"            "dim_red"           
## [19] "cache"              "status"

Imputed data

imputed_data

## Trained MOFA with the following characteristics: 
##  Number of views: 4 
##  Views names: abtiter cytof rnaseq olink 
##  Number of features (per view): 27 20 10269 30 
##  Number of groups: 1 
##  Groups names: group1 
##  Number of samples (per group): 190 
##  Number of factors: 15

slotNames(imputed_data)

##  [1] "data"               "covariates"         "covariates_warped" 
##  [4] "intercepts"         "imputed_data"       "interpolated_Z"    
##  [7] "samples_metadata"   "features_metadata"  "expectations"      
## [10] "training_stats"     "data_options"       "model_options"     
## [13] "training_options"   "stochastic_options" "mefisto_options"   
## [16] "dimensions"         "on_disk"            "dim_red"           
## [19] "cache"              "status"

Results for Actual Data

plot_object = MOFAobject

plot_factor_cor(plot_object)

plot_factor(plot_object,
  factors = 1,
  color_by = "Factor1"
)

plot_variance_explained(plot_object, max_r2=1)

plot_variance_explained(plot_object, plot_total = T)[[2]]

correlate_factors_with_covariates(plot_object,
  covariates = c("timepoint", "infancy_vac", "biological_sex", "ethnicity", "race"),
  plot="log_pval"
)

plot_weights(plot_object,
 view = "cytof",
 factor = 12,
 nfeatures = 10,     # Top number of features to highlight
 scale = T           # Scale weights from -1 to 1
)

plot_data_heatmap(plot_object,
  view = "cytof",
  factor = 14,
  features = 25,
  cluster_rows = FALSE, cluster_cols = FALSE,
  show_rownames = TRUE, show_colnames = FALSE,
  scale = "row"
)

plot_factor(plot_object,
  factors = 1,
  color_by = "infancy_vac",
  dodge = TRUE,
  add_violin = TRUE
)

plot_factor(plot_object,
  factors = 14,
  color_by = "infancy_vac",
  dodge = TRUE,
  add_violin = TRUE
)

Results for Imputed Data

plot_object = imputed_data

plot_factor_cor(plot_object)

plot_factor(plot_object,
  factors = 1,
  color_by = "Factor1"
)

plot_variance_explained(plot_object, max_r2=1)

plot_variance_explained(plot_object, plot_total = T)[[2]]

correlate_factors_with_covariates(plot_object,
  covariates = c("timepoint", "infancy_vac", "biological_sex", "ethnicity", "race"),
  plot="log_pval"
)

plot_weights(plot_object,
 view = "cytof",
 factor = 12,
 nfeatures = 10,     # Top number of features to highlight
 scale = T           # Scale weights from -1 to 1
)

plot_object = imputed_data
plot_data_heatmap(plot_object,
  view = "cytof",
  factor = 12,
  features = 25,
  cluster_rows = FALSE, cluster_cols = FALSE,
  show_rownames = TRUE, show_colnames = FALSE,
  scale = "row"
)

plot_factor(plot_object,
  factors = 1,
  color_by = "infancy_vac",
  dodge = TRUE,
  add_violin = TRUE
)

plot_factor(plot_object,
  factors = 14,
  color_by = "infancy_vac",
  dodge = TRUE,
  add_violin = TRUE
)

results <- imputed_data@imputed_data

saveRDS(results, file = here("./results/imputedData_2020.RDS"))

knitr::kable(MOFAobject@data$abtiter$group1[1:10,], "html", align = "lccrr", booktabs=TRUE, border_left = T, 
             border_right = T, caption = "Ab-titer Before Imputation")  %>% 
  kable_styling("striped", full_width = T) %>% 
  scroll_box(width = "100%", height = "400px")

Ab-titer Before Imputation
	1	102	103	104	105	106	114	115	116	117	118	131	132	133	134	135	138	139	140	141	142	146	147	148	149	150	153	154	155	156	157	160	161	162	163	164	167	168	169	170	171	174	175	176	177	178	181	182	183	184	185	19	191	192	193	194	195	2	20	201	202	203	204	205	208	209	21	210	211	212	22	223	224	225	226	227	23	241	242	243	244	245	248	249	250	251	252	255	256	257	258	259	27	274	275	276	277	278	28	281	282	283	284	285	29	293	294	295	296	297	3	30	31	324	325	326	327	328	332	333	334	335	336	342	343	344	345	346	349	350	351	352	353	355	356	357	358	359	360	361	362	363	364	369	37	370	371	372	373	38	385	386	387	388	389	39	397	398	399	4	40	400	401	405	406	407	408	409	41	45	46	47	48	49	5	70	71	72	73	74	77	78	79	80	81	87	88	89	90	91
IgG_PT	0.2162395	-1.8795129	-1.4625466	-1.2025638	-1.2820847	-0.3403251	-3.1228967	-3.2305064	-2.3495264	-2.5594282	1.9076943	6.2760625	4.3789663	4.1873889	5.1985669	5.5324693	-1.2579141	-1.9355637	-2.2866397	6.6865525	6.2745337	-0.0351729	0.1299930	0.6535320	5.5309892	5.6004415	1.3053193	1.5541043	-2.1007838	2.4994984	3.6445479	2.2629499	-2.9047189	-3.2553053	-2.0592632	-1.5427165	-0.0322740	-3.1091046	-3.3125329	3.8515038	1.3513632	-3.1043844	-3.0811670	-3.1358461	0.8182712	3.5889134	-3.2167146	NA	-3.2579985	-3.2648091	-2.1646051	-2.3508842	-2.7542894	NA	-3.1064792	-2.9302456	-2.1928110	NA	-2.7238855	-2.7799356	-3.2154789	-2.8096392	-2.4132595	-0.9927273	-2.7301645	-3.2154789	-2.9147854	-2.9271395	-3.3883328	-1.0875316	2.8285112	-2.4487634	-2.6552911	-2.4421184	-1.5546074	0.5619464	3.4288120	-3.2985985	-3.2593515	-3.3314695	-2.4494638	-1.6680670	-1.8167692	-1.9614874	-1.8700733	4.3144526	11.0331707	-2.8757901	NA	NA	-2.8063593	-2.7082739	-1.4270308	-2.1662211	-1.6866584	-1.2127879	0.4752617	0.6811481	NA	-2.3887835	-2.9082122	-2.8402841	-1.9987468	-1.2231419	-1.8345847	-2.7293787	-2.8903990	-2.9485860	1.3650422	3.0030994	-1.2239819	-2.0350289	4.2600074	-2.2809772	-2.3617656	-2.3641508	4.3321805	5.2002749	-2.4403722	NA	-2.6379113	-2.6651742	-2.0121651	-2.5383792	-2.6371589	-2.5506976	8.8131504	12.1545258	-3.3165298	-3.2859955	-3.3883328	-3.0052810	-1.3768620	6.1518998	6.9405723	5.7577386	9.2637196	7.2459083	1.7489357	1.5885625	2.0888925	8.5115528	11.4663467	-3.3883328	0.2755566	-3.3883328	-3.3883328	-3.2273388	-3.3883328	-0.3481135	-3.0066986	-3.0461855	-3.2324171	-2.5391021	-0.6147802	-1.2410748	-0.5749409	-0.8000710	-3.3883328	-0.2568376	2.4132910	0.0203800	2.4115028	13.1974850	5.2020545	2.5524101	3.1299939	8.2017670	1.7621870	-3.2093427	NA	-3.2229373	-3.2466679	5.4580503	7.1546969	-3.2020690	-3.2286034	-3.0765958	-2.5340452	-2.4942813	-3.3883328	NA	-3.3883328	-3.1709778	-3.2142460	-1.0572040	-1.5019577	-1.5496747	24.8651371	18.5462608
IgG_PRN	-0.1889729	-1.3309789	-1.1566325	-1.9575906	8.7186117	10.0289268	-1.4459772	-1.6291103	-0.5443974	2.2180693	12.4969530	-1.9628996	-1.9811385	-1.9799095	-1.9516526	-1.9328809	-0.7020391	-1.2724810	-1.5592005	-1.7350292	-1.8329828	-0.2030611	-1.9471817	-1.9395058	-1.8708514	-1.8434970	-1.8784099	-1.8727082	-0.3736796	-1.9413210	-1.9298513	-0.5088065	9.3344002	2.9681294	7.5169353	9.0607500	-1.1031904	-0.6991929	-1.6399471	-1.8591099	-1.8785644	-2.0025468	-1.9749088	-2.0464792	-1.8229613	26.3044643	-1.4062631	NA	-1.4966682	-1.5348806	1.2647295	3.8817327	-1.6891785	NA	-1.9642934	-1.8247217	2.7664292	NA	1.9785283	-1.3387965	-1.9821522	-1.4091731	1.9934618	-1.9436532	-1.6425174	-2.0651512	0.6762407	-1.7985314	-1.8620324	-1.8955178	6.1580935	2.8323352	1.8059552	3.0071661	4.0929918	-1.8729805	4.2236748	0.1940334	0.4434087	-0.2714157	1.3618691	1.8997853	-1.0946478	-1.1656736	-1.2043180	-1.7966840	-1.6640520	-2.1393678	NA	NA	-2.1232429	-2.1118371	2.2839849	-1.1943642	-0.6418889	0.1922684	-1.9195601	3.9234259	NA	0.9739451	-0.6839869	-0.3192329	1.2292337	1.4093001	0.9989393	-1.9002581	-1.9795043	-2.0248218	-1.8986579	-1.8264291	-1.1819732	0.0959880	3.9774020	1.6614058	1.2170954	1.2144537	-1.8464347	-1.8196082	-1.0945985	NA	-1.2979096	-1.3368547	5.8246469	-1.7569058	-1.8107791	-1.7797060	-1.7747414	-1.7037284	-2.1738453	-2.1622558	-2.2312074	-1.1561462	7.5797777	-2.0236588	-2.0127337	-2.0278535	-1.8378595	-1.8534908	-1.9169319	-1.9112070	-1.9108484	-1.8332422	-1.7597495	-1.4450426	1.9598544	-1.8435194	-2.2473633	1.8262680	-1.8133500	1.4091384	-2.0858741	-2.1005998	-2.1812534	-0.3591657	-1.7821889	0.4583626	-0.7134614	-0.7858959	-1.9617440	-0.4849591	1.9776247	-1.9217402	-1.8499405	-1.9756877	-2.0978007	-2.1416435	-1.9762318	-1.9041333	1.7939112	-2.2138729	NA	-2.2144094	-2.2178013	-0.4679511	3.8876336	-2.1612997	-2.1656840	-0.4725802	0.9467227	0.9787562	-2.2327645	NA	-2.2271185	6.4292469	5.6479635	4.2330637	2.9340236	2.6369908	5.5376806	3.9786575
IgG_FHA	27.9851799	-2.6554804	1.0327916	-1.5103142	66.3398590	16.8964481	-2.5574467	-2.8473110	-3.1338518	-2.6447208	-3.6096501	-1.4098172	-1.5238965	-1.5245118	-1.4359431	-1.3364060	6.0391893	1.4065962	-2.9427569	-0.7567778	-0.7919493	-2.7018359	-1.9727592	-1.9277668	-1.5390351	-1.6009305	-1.9135256	-1.9176648	7.5671997	-1.4442801	-1.3300464	9.5607548	-2.8607042	-3.3680506	12.4145145	-3.6096501	-0.5152659	-3.2046971	-3.4365439	-1.4197130	-1.5202460	-1.6181982	-1.7384155	-1.9284513	-0.7919493	58.8420258	-3.2004883	NA	-3.2201340	-3.2289984	-1.7290912	-2.6682935	-3.4364529	NA	-3.5416720	-3.4937799	-2.4392889	NA	-2.9901245	-2.7801807	-3.3332756	-2.8006980	-1.4706826	-1.7224591	-1.6375394	-2.9614015	-3.1247363	-2.0548837	-1.5794377	-1.6068883	-3.6096501	0.9462256	0.1444077	1.9786258	7.6007204	-1.2957013	7.0685558	-3.3844476	-3.3456044	-3.4230685	-1.3583059	2.0386071	-2.9949644	-3.0678883	-3.0407491	-1.5670056	-0.5795503	-3.1388481	NA	NA	-3.0610936	-3.0382886	-2.7131107	-1.4694400	-0.4708824	3.0691433	-1.5357995	-3.6096501	NA	-0.8889480	-2.3650196	-2.2007592	-1.4389362	-0.5152659	-2.9256096	-2.9773986	-3.0910242	-3.1405346	-1.5140314	-0.9384589	0.4408212	-3.0315197	-0.9617105	-2.9196861	-2.9750078	-2.9391015	-1.6771452	-1.2535291	-2.7358506	NA	-2.9056578	-2.9404731	0.3413501	-3.2761731	-3.3113790	-3.2796702	-1.4625318	-1.0028934	-3.4404163	-3.4281178	-3.5548835	0.2129889	-3.6096501	-1.7605081	-1.7241580	-1.7674677	-1.3829269	-1.3704772	-1.8648117	-1.8339312	-1.8486264	-1.3485787	-0.9027724	-3.3192630	-3.6096501	-3.4945860	-3.6096501	-1.7084715	-1.3251045	6.1079111	-3.1962519	-3.2113400	-3.4035535	-2.3899014	-1.1958599	0.6528783	-3.6096501	51.2839508	-1.5043685	5.9275579	-3.6096501	-1.3804021	-0.8708344	-1.1366110	-0.8973508	-1.6131766	-1.6853144	-0.8824954	-3.6096501	-3.3353853	NA	-3.3317432	-3.3303442	5.6924562	-3.6096501	-3.3384950	-3.3762093	-3.0885019	1.7387786	1.8847485	-3.5908084	NA	-3.5888810	-1.3824735	-1.6074181	0.5486670	-0.8635044	-1.0314713	14.4577160	29.7881775
IgG1_PT	5.1357718	-4.6914430	-5.7695112	-3.9233990	-1.0982180	28.0436783	-12.9887581	-12.9514494	-12.8110695	-12.5095348	-4.3559813	36.9365959	30.6726074	24.5078888	4.6588459	42.3302803	-5.3894281	-6.4962549	-7.1586599	4.1980982	35.8749390	0.7439785	8.0803823	0.9632635	3.1669369	29.5463333	-11.0875702	-11.1004715	-11.0473471	11.3118486	14.6620817	-12.7419558	-12.6995144	-12.6806507	-7.1797233	-6.7623787	-12.8716393	-12.8724251	-12.8158360	18.9518471	23.1111412	-12.8865728	-12.8331270	-12.9148674	2.3303823	19.7716026	-12.9282284	NA	-12.9565229	-12.9588814	-9.3273277	-9.5675201	-11.4152565	NA	-11.8593235	-12.0731049	-11.5370140	NA	-8.5387115	-10.9138155	-11.0285654	-11.2674971	0.7954178	19.4587898	-12.5431080	-12.5690451	-10.4699402	-12.6350651	-6.1858654	5.7426243	13.1252623	-12.2365122	-12.0900936	-11.8787842	-9.7324190	-1.1877198	29.4733009	-13.0401516	-13.0584536	-13.0418148	-9.1453648	-7.0747542	-9.0061483	-7.5793972	-8.5762358	24.8253403	39.4966965	-11.1383715	NA	NA	-10.0968018	-12.5350475	-3.4367957	-5.7816081	-5.7408438	-6.8968496	0.3873520	9.9843130	NA	-10.2648506	-11.3979321	-11.1360836	-8.2319574	-3.7835207	-2.1467819	-11.4400043	-11.3214006	-11.7237453	7.9565306	14.9376364	7.4984102	-1.9470868	22.7780380	-9.9384775	-10.7014980	-7.8732796	19.8870850	35.5282059	-12.7004833	NA	-12.9382973	-12.3055735	-11.2682447	-9.8123589	-11.4791355	-9.5191317	42.8580818	46.4351311	-13.0378513	-13.0985794	-13.0804167	-12.9716396	-12.9338036	25.5182991	7.4549379	35.6030884	38.7576408	33.3826065	17.6262016	18.6668739	19.6513901	44.3225784	41.1500893	-13.0970898	5.4382629	-13.0985107	-13.0970898	-13.0405712	-12.8312626	1.5631666	-12.8561134	-13.0217400	-12.9307518	-12.0933456	-3.7768030	2.3509932	-10.2110720	-10.9780703	-9.2158928	3.2028570	20.9125290	-5.1360803	-6.9279289	8.2608633	10.7701330	11.2293367	21.1424561	28.8401031	19.1228561	-12.9008284	NA	-12.9412727	-13.0086803	-10.9594889	35.1170082	-13.0985794	-13.0985794	-13.0985794	-12.9513845	-11.8663864	-13.0985794	NA	-13.0985794	-13.0985794	-13.0400581	-9.0091562	-8.0593367	-6.3672285	56.8058472	52.6902237
IgG1_PRN	0.5814521	-0.2204168	-0.4360607	-0.4961522	0.7791111	1.5162718	-1.7097256	-1.6897355	-1.6666890	-1.5205240	-0.4315710	-0.1554860	-0.3621595	-0.5665646	-0.7674566	0.8695858	-0.1859612	-0.2890605	-0.5299151	0.2149602	1.3490317	-0.1853375	0.2208005	-0.3410408	-0.1312194	0.9275484	-0.8260263	-0.7032492	-0.6471233	0.2052603	0.1998842	1.1089544	1.5321951	1.2010410	1.6394014	1.3040884	-0.2234455	-0.2472692	-0.1438948	0.8904426	0.9083846	-1.5305961	-1.4923358	-1.5419436	0.7311034	0.7455106	-0.2143557	NA	-0.3184727	-0.3260772	0.3486407	1.6619074	-1.2375240	NA	-1.3294618	-1.3619000	0.2852159	NA	1.7581527	-0.4924268	-0.5205576	-0.7555411	-0.5320246	0.0979060	-1.3000833	-1.3353732	1.6219120	-1.3629396	0.4266324	0.8614056	1.8239694	0.9175973	1.0732753	1.0984306	1.2160809	1.4556928	2.0822766	0.4053707	0.2067641	0.3710649	0.9692354	0.9057138	-1.6084241	-1.5606568	-1.6003100	1.3496330	1.3235166	-1.7249577	NA	NA	-1.7145667	-1.7629836	1.0373373	0.6335371	0.6005342	0.3242557	0.8175402	1.2465706	NA	0.7296300	0.5308993	0.4090734	0.4538620	0.6714585	1.0905793	-1.4365327	-1.3945205	-1.4396448	0.6446710	0.9600825	0.6665306	1.1032178	1.4250700	0.8137336	0.6139755	1.0745528	1.4113228	1.7738109	-0.4605545	NA	-0.8450153	-0.1394258	1.1886744	-0.9455864	-1.2468638	-0.9290427	1.3661134	1.3869886	-1.7647114	-1.7722945	-1.7770439	-0.3347920	0.4783471	-1.5281361	-1.5982403	-1.3869429	1.1817563	1.0620999	0.1850666	0.2227334	0.2253157	1.3393221	1.3510544	-1.2475643	1.2222767	-1.3056083	-1.2256997	0.9433432	1.3305380	1.0224910	-1.6623766	-1.7332476	-1.6956650	-0.1922933	1.0970693	1.0957627	-0.4867054	-0.6598550	-0.2804641	0.4445395	1.4309893	0.9001493	1.1863685	-1.7562631	-1.7383279	-1.7286165	-0.7846989	0.0853503	1.4605861	-1.7718211	NA	-1.7733569	-1.7796602	-1.5379912	1.4184468	-1.7407526	-1.7570068	-1.7602065	-0.6252611	0.4424355	-1.7639500	NA	-1.7846837	0.6724501	1.0909710	1.1954069	1.3300803	1.4962983	1.9614177	1.8590908
IgG1_FHA	2.2118869	-0.4605175	1.0071276	0.9482054	0.8419954	2.6981077	-0.6679863	-0.4716072	-0.7025899	-0.7524486	1.6946925	1.3099750	1.1015052	0.8986899	-0.1552714	1.9109200	1.0730880	0.9055880	0.5988380	0.7483064	2.4969034	-1.1973629	-0.6543775	-1.2093182	-0.5098917	0.8082439	-2.2775788	-2.2302864	-2.2419372	0.8658074	0.9651655	-1.1992862	-1.0854659	-1.0582547	2.1808815	2.0144658	-1.6458211	-1.6515354	-1.5416024	1.5334119	1.8697027	0.2404941	0.3034683	0.1307943	1.9586831	1.9056603	-1.3305217	NA	-1.3962948	-1.3861879	0.1815795	-0.5857872	-2.1944366	NA	-2.2434943	-2.2960505	-1.1289095	NA	-0.3972658	-0.9148909	-0.9500322	-1.2637767	0.1233196	1.5262593	-0.2916781	-0.2611628	-0.8402911	-0.3370041	0.2614049	1.4614967	1.7306288	0.7247478	0.9175199	0.9324917	1.1197606	1.8123480	2.2438216	-2.0229416	-2.1046793	-2.0105596	0.6505173	0.8358999	-1.7009264	-1.5241783	-1.7487215	0.8210758	1.9145418	-1.2342918	NA	NA	-0.8621010	-1.8490430	-0.6144717	0.8970450	0.8258277	0.6134568	1.2028195	1.8079678	NA	0.6610571	0.2104464	0.1375594	0.1021416	0.5596889	-0.4803127	-1.7850208	-1.7843397	-1.8412727	0.7672280	1.9367381	2.3453140	-0.3730506	0.5822736	-1.1880319	-1.3655970	-0.7623203	0.3577107	2.3800793	-0.9826308	NA	-1.5603294	-0.6027577	0.5815109	-1.8549910	-2.1778343	-1.8802894	1.5389658	2.0150366	-2.3437505	-2.4247923	-2.4493060	0.5447923	0.7025310	-0.5042603	-1.1404624	0.0575000	1.3299166	1.1886734	-0.0543756	-0.0452875	0.0029615	2.0303755	2.2149477	-2.0594015	1.9712781	-2.1468482	-2.1015179	0.3862149	1.9932848	1.6799637	-1.9349003	-2.1827207	-2.0558550	-0.9095848	1.4323589	1.8960322	0.7623090	0.4170300	0.9092723	2.0276723	2.3509212	1.8208121	1.9099571	-0.2966546	-0.2438246	-0.1504301	0.2356185	1.6455945	2.3602657	-1.6124976	NA	-1.6324873	-1.8466054	-0.1543820	3.0331330	-1.9918969	-2.1621349	-2.1480770	-0.4064481	1.2734717	-2.5958154	NA	-2.6287255	-2.1825311	0.4727839	0.1620429	0.4086334	0.9252261	2.4624510	3.6363363
IgG1_TT	0.2533940	-0.2435075	0.1384717	0.1762115	0.5559868	0.6872101	-1.2768636	-1.2696888	-1.2548850	-0.3711975	0.4413632	0.0790581	-0.0478534	-0.1320554	-0.2246913	0.3631752	0.3112973	0.2591966	0.1492991	0.3572214	0.7448088	-0.0860789	0.1630121	-0.1394652	0.3262918	0.6502006	-0.6528349	-0.5443359	-0.5320455	-0.0299782	-0.0642236	0.1625590	0.2356606	0.2291822	0.9191879	0.6805482	-0.6478363	-0.6649919	-0.5843323	0.4807587	0.5103912	-0.7766237	-0.7198581	-0.7940793	0.5529004	0.4734006	-0.2192246	NA	-0.2719912	-0.2583946	0.2795370	0.1975110	-0.3714461	NA	-0.4350500	-0.4538053	0.3741770	NA	0.2690183	-0.1375052	-0.1104320	-0.2425986	0.4590368	0.6116457	-0.0858382	-0.1049733	0.1410955	-0.1408443	0.2244599	0.4895564	0.5740712	-0.1772685	-0.1391538	-0.1093767	0.4787309	0.6786892	0.6796325	0.1276695	0.0406176	0.1145059	0.5734737	0.6570466	0.1462133	0.2450322	0.0811899	0.5568700	0.6086104	-0.3760151	NA	NA	-0.2348512	-0.6184543	0.5209731	-0.1185563	-0.1004231	-0.2022438	0.1409141	0.4339529	NA	-0.1607987	-0.2895383	-0.2825534	-0.1507291	-0.0166471	0.5555595	-0.6303087	-0.6278253	-0.7219680	-0.3096243	-0.1700625	0.3144783	0.5673956	0.6753937	0.1531388	0.0157325	0.3363197	0.6936409	0.8460878	-0.0325116	NA	-0.2351267	0.1073231	0.4599506	0.0582013	-0.1737918	0.0367322	0.6327440	0.6393356	-0.2108152	-0.3403661	-0.3331195	0.5817243	0.5864793	-0.7424809	-0.8062928	-0.5697895	0.0335282	-0.0094099	-0.4815431	-0.4465675	-0.4465675	0.5535922	0.5424592	-0.2384638	0.3713033	-0.3024735	-0.2541922	0.4517987	0.5686334	0.2974615	-0.3834999	-0.5142691	-0.4746596	0.1256799	0.3445276	0.3438635	-0.8068604	-0.8964433	-0.7249879	0.2036747	0.6138179	0.5418054	0.5590698	-0.9110950	-0.8592373	-0.8527959	-0.1408625	0.2665067	0.6261249	-0.3481316	NA	-0.3695715	-0.4722865	0.6550186	0.7237206	-0.7017161	-0.7489781	-0.7974073	-0.0931667	0.2591966	0.1406041	NA	-0.0555291	0.5584059	0.6779388	-0.9403241	-0.8991930	-0.7997551	0.7588570	0.6573634
IgG1_DT	0.9238473	-0.1004493	0.5475386	0.6021978	0.0287017	0.7705725	-1.3194927	-1.3154684	-1.3062688	-1.3060930	-0.5831041	0.7138096	0.5963014	0.5589635	-0.0216279	0.7997619	0.3292576	0.2141918	0.1800517	-0.0521563	0.5817212	-0.6289031	-0.3836710	-0.6328250	-0.5501323	0.0807199	-0.5303599	-0.4256136	-0.4085177	0.2982107	0.3185734	0.5646561	0.6975759	0.6246573	1.0848523	0.8876539	-0.6647731	-0.6620713	-0.6269207	0.3916889	0.4697015	-1.0517682	-1.0098913	-1.0719749	-0.0811424	-0.0191152	-0.3853407	NA	-0.4508859	-0.4196471	0.3525643	0.1061282	-0.6154946	NA	-0.6940418	-0.7371570	-0.1946393	NA	0.2334658	-0.6964340	-0.6837978	-0.7235358	0.2391977	0.8551205	-1.0633912	-1.0725940	0.0037209	-1.0951085	-0.4880080	0.2397447	0.7972039	0.2491913	0.3084038	0.3536770	0.7136286	0.7921122	1.0536298	-0.5723981	-0.6679782	-0.5880650	0.7101446	0.7590357	0.3194541	0.5040615	0.2119116	0.9572059	0.9946920	-0.3927648	NA	NA	-0.2287388	-0.8358904	0.5777210	-0.0295367	-0.0340044	-0.1746446	0.0363489	0.1238842	NA	-0.6030766	-0.7215018	-0.7357213	0.0138283	0.2460977	0.5822784	0.1196001	0.1371998	0.0781481	0.1486048	0.2868838	0.9656795	0.6597556	0.7702214	0.7210218	0.5578095	0.7538575	0.8431896	0.9167858	-0.1424469	NA	-0.5603256	0.0759554	0.5223607	0.3762479	-0.2430061	0.2641069	0.4843554	0.4186842	-1.0578675	-1.1377133	-1.1295321	-0.2185426	-0.0791333	-0.9145951	-1.0451295	-0.7124402	-0.1855081	-0.3431247	0.3252933	0.3201777	0.3352144	0.6301349	0.5422659	0.5769382	0.7925559	0.4054631	0.4478345	0.7893411	0.8863798	0.6973320	-0.0623018	-0.2503636	-0.1715631	0.5821213	0.7023851	0.7681388	-0.6164371	-0.7211772	-0.5199646	0.8958687	1.2449228	0.6950999	0.6761001	-1.2417512	-1.2060714	-1.2005424	-0.1276014	0.6043848	1.2309788	-0.9850695	NA	-1.0160060	-1.0834626	0.9475704	1.1492764	-0.5095229	-0.5954508	-0.6174837	-0.2329658	-0.0736395	-0.5400368	NA	-0.7439460	1.0397159	1.0668339	-1.3075587	-1.3013974	-1.2833576	0.8999799	0.8813573
IgG1_OVA	-3.7513483	-3.9922626	25.7987843	34.6574135	14.9435234	41.8257294	-1.5065289	-0.9464521	0.3964386	-3.5744393	0.8348107	-4.2188106	-4.2288098	-4.0366812	-4.2288098	-4.1910377	-4.2288098	-4.2288098	-4.1601663	-4.2288098	-4.1354694	-3.6272688	-2.9808826	-3.3575125	-4.0854650	-3.2093301	9.9850655	11.2013950	11.9855270	8.2500992	7.0339141	-4.1837301	-4.1182833	-4.1575513	-3.9481206	-4.0397468	-4.1182833	-4.1051936	-4.1117387	-4.0004783	-3.8957629	-2.5999088	-1.8014534	-2.9533236	-1.2909656	-1.3105996	-3.0253155	NA	-3.3198276	-3.2478359	-3.7806427	23.6990643	-3.4965351	NA	-3.7779579	-3.8695841	-3.7806427	NA	28.5172234	-2.7438927	-2.7308033	-2.9991364	-3.4982338	-2.0108843	-4.1051936	-4.1313725	16.1632900	-4.1706409	-4.2288098	-3.8237710	11.1581402	-4.1708860	-4.1054392	-4.0661707	-4.1185284	-4.0923495	16.7678967	-3.8960080	-4.0269022	-3.9614551	-3.9128120	-4.0054259	-4.1316180	-4.1054392	-4.1968279	-4.0733428	-4.1227369	4.9524493	NA	NA	10.3518410	0.0699821	0.4871349	-2.6263328	-2.6394224	-2.8137937	-2.5791717	-0.3070436	NA	-3.4509673	-3.7520242	-3.7028871	-3.8881149	-3.8510695	0.7613897	-4.2288098	-4.2288098	-4.2288098	-4.2288098	-4.2288098	-3.6516192	1.0730429	-0.4353585	-4.2288098	-4.2288098	-4.2288098	-4.1418476	-4.1803460	14.8121643	NA	8.2239819	24.9115620	5.9511323	-4.0776839	-4.2288098	-4.0905166	-3.8466940	-3.9365234	-4.0648513	-4.2109804	-4.1354313	-4.0776839	-4.0391855	5.9960465	3.2302732	13.6058846	8.6716805	5.2902446	0.1151385	0.0079408	0.4198065	0.2392626	-1.5323246	15.9409409	-0.8779058	13.9605999	17.0354881	14.5036469	18.6988106	-2.0247896	-1.8087826	-2.8751202	-2.5027483	-1.9235923	-2.2050152	-2.0372558	0.7019062	-1.4589787	1.0573521	-3.9071748	-1.9811580	1.8919778	-0.6931856	-2.4237602	-1.8031404	-1.1261008	-1.8057873	-3.4681454	-1.8440306	4.3641009	NA	3.3730435	0.7052922	-1.4077163	-3.9383402	-3.9134078	-3.9882045	-4.0006709	-4.0380692	-3.7783008	-4.2288098	NA	-4.2288098	-4.2288098	-4.1684666	-4.2188106	-4.1558805	-4.1181226	-4.0174346	-4.0551925
IgG2_PT	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	0.9183917	0.0770750	-0.3495622	-0.1311436	0.1600814	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.2810969	-3.7637157	-3.6258411	-4.3539028	-3.1161976	-3.4074225	-4.4503980	-4.4503980	-4.4503980	-2.6429572	-2.0908136	-4.1795988	-4.1422987	-4.3287973	-4.0303998	-4.0303998	-4.2541981	-4.2541981	-4.2541981	-3.8066013	-3.8812008	-4.0303998	-2.9114079	-3.4336040	-3.1352062	-0.5242252	-4.4503980	NA	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	NA	-4.4503980	-4.4503980	-4.4503980	NA	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.1795988	-3.4336040	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-3.9558003	-4.4503980	-4.3801613	-4.4503980	-4.4503980	-3.9829495	1.8759208	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-1.9968920	-2.3941035	-2.0988789	1.0935750	18.8976421	-4.1815553	NA	NA	-4.1815553	-4.4503980	-1.4329824	26.4037342	24.8148861	23.4407501	22.0491676	25.2416210	NA	-2.0465431	-2.1954975	-3.4086032	-2.1807365	-0.7891541	-1.3855100	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.2101164	-1.3380375	0.7982197	-4.2259407	-4.0729742	-4.4503980	-1.6255093	0.8984389	-2.6962752	NA	-1.4343009	-2.0844088	-2.8492417	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.3789072	-4.1494575	-3.9964910	-4.4503980	-4.1494575	-4.2259407	-2.9257250	-2.0461674	-2.5050669	-3.3846245	-2.3903418	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	0.2285509	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-1.3380375	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-1.4689574	-1.6703444	75.3931503	70.1010056	64.3203506	-4.4503980	0.1098700	105.2779388	127.9228287	1.0588069	3.0942492	0.6924276	1.1338639	2.0014710	0.3234959	-4.4503980	NA	-4.4503980	-4.4503980	-4.4503980	-4.3762698	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	NA	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-4.4503980	-3.9100316	-4.0563474

# abtiter <- head(results$abtiter$group1)
knitr::kable(results$abtiter$group1[1:10,], "html", align = "lccrr", booktabs=TRUE, border_left = T, 
             border_right = T, caption = "Ab-titer After Imputation")  %>% 
  kable_styling("striped", full_width = T) %>% 
  scroll_box(width = "100%", height = "400px")

Ab-titer After Imputation
	1	102	103	104	105	106	114	115	116	117	118	131	132	133	134	135	138	139	140	141	142	146	147	148	149	150	153	154	155	156	157	160	161	162	163	164	167	168	169	170	171	174	175	176	177	178	181	182	183	184	185	19	191	192	193	194	195	2	20	201	202	203	204	205	208	209	21	210	211	212	22	223	224	225	226	227	23	241	242	243	244	245	248	249	250	251	252	255	256	257	258	259	27	274	275	276	277	278	28	281	282	283	284	285	29	293	294	295	296	297	3	30	31	324	325	326	327	328	332	333	334	335	336	342	343	344	345	346	349	350	351	352	353	355	356	357	358	359	360	361	362	363	364	369	37	370	371	372	373	38	385	386	387	388	389	39	397	398	399	4	40	400	401	405	406	407	408	409	41	45	46	47	48	49	5	70	71	72	73	74	77	78	79	80	81	87	88	89	90	91
IgG_PT	3.7817945	1.6860422	2.103009	2.3629913	2.283470	3.225230	0.4426584	0.3350487	1.2160287	1.0061269	5.473249	9.8416176	7.9445214	7.7529440	8.7641220	9.0980244	2.3076410	1.6299914	1.2789154	10.2521076	9.8400888	3.5303822	3.6955481	4.2190871	9.0965443	9.1659966	4.8708744	5.1196594	1.4647713	6.0650535	7.2101030	5.8285050	0.6608362	0.3102498	1.5062919	2.0228386	3.5332811	0.4564505	0.2530222	7.4170589	4.9169183	0.4611707	0.4843881	0.4297090	4.3838263	7.154469	0.3488405	2.589788	0.3075566	0.3007460	1.4009500	1.2146709	0.8112657	3.915878	0.4590759	0.6353095	1.3727441	3.721119	0.8416696	0.7856195	0.3500762	0.7559159	1.152296	2.5728278	0.8353906	0.3500762	0.6507697	0.6384156	0.1772223	2.4780235	6.394066	1.1167917	0.9102640	1.1234367	2.0109477	4.1275015	6.994367	0.2669566	0.3062036	0.2340856	1.1160913	1.8974881	1.7487859	1.6040677	1.6954818	7.8800077	14.5987258	0.6897650	2.668232	2.195160	0.7591958	0.8572812	2.138524	1.399334	1.878897	2.352767	4.0408168	4.246703	3.038902	1.1767716	0.6573429	0.7252710	1.5668083	2.3424132	1.730970	0.8361764	0.6751561	0.6169691	4.9305973	6.5686545	2.3415732	1.530526	7.825563	1.2845778	1.2037895	1.2014043	7.8977356	8.7658300	1.125183	3.306581	0.9276438	0.9003808	1.553390	1.0271759	0.9283962	1.0148575	12.3787055	15.7200809	0.2490253	0.2795596	0.1772223	0.5602741	2.1886930	9.7174549	10.5061274	9.3232937	12.8292747	10.8114634	5.3144908	5.1541176	5.6544476	12.0771079	15.0319018	0.1772223	3.841112	0.1772223	0.1772223	0.3382163	0.1772223	3.217442	0.5588565	0.5193696	0.3331380	1.026453	2.950775	2.324480	2.9906142	2.7654841	0.1772223	3.3087175	5.978846	3.5859351	5.9770579	16.7630401	8.7676096	6.1179652	6.6955490	11.7673221	5.327742	0.3562124	2.852654	0.3426178	0.3188872	9.0236053	10.7202520	0.3634861	0.3369517	0.4889593	1.0315099	1.0712738	0.1772223	2.2900039	0.1772223	0.3945773	0.3513091	2.5083511	2.0635974	2.0158803	28.4306922	22.1118159
IgG_PRN	2.4563730	1.3143671	1.488713	0.6877553	11.363958	12.674273	1.1993687	1.0162356	2.1009486	4.8634152	15.142299	0.6824464	0.6642075	0.6654364	0.6936933	0.7124650	1.9433068	1.3728650	1.0861454	0.9103167	0.8123631	2.4422848	0.6981642	0.7058401	0.7744945	0.8018489	0.7669361	0.7726377	2.2716663	0.7040249	0.7154946	2.1365395	11.9797461	5.6134753	10.1622813	11.7060959	1.5421555	1.9461530	1.0053989	0.7862360	0.7667816	0.6427991	0.6704371	0.5988667	0.8223846	28.949810	1.2390828	3.055147	1.1486777	1.1104653	3.9100754	6.5270786	0.9561675	3.112043	0.6810526	0.8206242	5.4117751	2.443802	4.6238742	1.3065494	0.6631937	1.2361728	4.638808	0.7016927	1.0028285	0.5801947	3.3215866	0.8468145	0.7833135	0.7498281	8.803439	5.4776812	4.4513011	5.6525121	6.7383378	0.7723655	6.869021	2.8393793	3.0887547	2.3739302	4.0072150	4.5451312	1.5506982	1.4796723	1.4410279	0.8486619	0.9812939	0.5059781	2.271767	2.419713	0.5221031	0.5335088	4.929331	1.450982	2.003457	2.837614	0.7257859	6.568772	3.507109	3.6192911	1.9613590	2.3261130	3.8745797	4.0546460	3.644285	0.7450879	0.6658416	0.6205242	0.7466880	0.8189168	1.4633727	2.741334	6.622748	4.3067517	3.8624413	3.8597996	0.7989112	0.8257377	1.550747	2.324225	1.3474363	1.3084912	8.469993	0.8884401	0.8345668	0.8656399	0.8706045	0.9416175	0.4715006	0.4830902	0.4141386	1.4891998	10.2251236	0.6216872	0.6326122	0.6174924	0.8074864	0.7918551	0.7284141	0.7341390	0.7344975	0.8121037	0.8855964	1.2003033	4.605200	0.8018265	0.3979826	4.4716139	0.8319960	4.054484	0.5594718	0.5447462	0.4640925	2.286180	0.863157	3.103709	1.9318845	1.8594500	0.6836020	2.1603868	4.622971	0.7236058	0.7954054	0.6696582	0.5475452	0.5037024	0.6691141	0.7412126	4.439257	0.4314730	2.241844	0.4309366	0.4275446	2.1773949	6.5329795	0.4840462	0.4796619	2.1727657	3.5920687	3.6241021	0.4125814	2.7963207	0.4182274	9.0745928	8.2933095	6.8784096	5.5793695	5.2823367	8.1830266	6.6240034
IgG_FHA	33.2427640	2.6021037	6.290376	3.7472699	71.597443	22.154032	2.7001374	2.4102731	2.1237323	2.6128633	1.647934	3.8477669	3.7336876	3.7330723	3.8216410	3.9211781	11.2967734	6.6641803	2.3148272	4.5008063	4.4656348	2.5557482	3.2848248	3.3298173	3.7185490	3.6566536	3.3440585	3.3399193	12.8247838	3.8133039	3.9275377	14.8183389	2.3968799	1.8895335	17.6720986	1.6479340	4.7423182	2.0528870	1.8210402	3.8378711	3.7373381	3.6393859	3.5191686	3.3291328	4.4656348	64.099610	2.0570958	5.287606	2.0374501	2.0285857	3.5284929	2.5892906	1.8211312	5.350083	1.7159121	1.7638042	2.8182952	5.238756	2.2674596	2.4774034	1.9243085	2.4568861	3.786901	3.5351250	3.6200447	2.2961826	2.1328478	3.2027004	3.6781464	3.6506958	1.647934	6.2038097	5.4019918	7.2362099	12.8583045	3.9618828	12.326140	1.8731365	1.9119797	1.8345156	3.8992782	7.2961912	2.2626197	2.1896958	2.2168350	3.6905785	4.6780338	2.1187360	4.900160	4.698663	2.1964905	2.2192955	2.544473	3.788144	4.786702	8.326727	3.7217846	1.647934	5.425478	4.3686361	2.8925645	3.0568249	3.8186479	4.7423182	2.331974	2.2801855	2.1665599	2.1170495	3.7435527	4.3191252	5.6984053	2.226064	4.295874	2.3378980	2.2825763	2.3184826	3.5804389	4.0040550	2.521733	4.976024	2.3519263	2.3171110	5.598934	1.9814110	1.9462051	1.9779139	3.7950523	4.2546906	1.8171678	1.8294663	1.7027006	5.4705729	1.6479340	3.4970760	3.5334260	3.4901164	3.8746572	3.8871069	3.3927724	3.4236529	3.4089577	3.9090054	4.3548117	1.9383211	1.647934	1.7629981	1.6479340	3.5491126	3.9324796	11.365495	2.0613322	2.0462441	1.8540306	2.867683	4.061724	5.910462	1.6479340	56.5415349	3.7532156	11.1851420	1.647934	3.8771820	4.3867497	4.1209731	4.3602333	3.6444075	3.5722697	4.3750887	1.647934	1.9221988	5.248056	1.9258409	1.9272399	10.9500403	1.6479340	1.9190891	1.8813748	2.1690822	6.9963627	7.1423326	1.6667757	5.6541097	1.6687031	3.8751106	3.6501660	5.8062510	4.3940797	4.2261128	19.7153001	35.0457616
IgG1_PT	14.1694136	4.3421988	3.264131	5.1102428	7.935424	37.077320	-3.9551163	-3.9178076	-3.7774277	-3.4758930	4.677660	45.9702377	39.7062492	33.5415306	13.6924877	51.3639221	3.6442137	2.5373869	1.8749819	13.2317400	44.9085808	9.7776203	17.1140242	9.9969053	12.2005787	38.5799751	-2.0539284	-2.0668297	-2.0137053	20.3454905	23.6957235	-3.7083139	-3.6658726	-3.6470089	1.8539186	2.2712631	-3.8379974	-3.8387833	-3.7821941	27.9854889	32.1447830	-3.8529310	-3.7994852	-3.8812256	11.3640242	28.805244	-3.8945866	7.593361	-3.9228811	-3.9252396	-0.2936859	-0.5338783	-2.3816147	8.656209	-2.8256817	-3.0394630	-2.5033722	9.494364	0.4949303	-1.8801737	-1.9949236	-2.2338552	9.829060	28.4924316	-3.5094662	-3.5354033	-1.4362984	-3.6014233	2.8477764	14.7762661	22.158904	-3.2028704	-3.0564518	-2.8451424	-0.6987772	7.8459220	38.506943	-4.0065098	-4.0248117	-4.0081730	-0.1117229	1.9588876	0.0274935	1.4542446	0.4574060	33.8589821	48.5303383	-2.1047297	8.302924	7.707403	-1.0631599	-3.5014057	5.596846	3.252034	3.292798	2.136792	9.4209938	19.017955	10.087780	-1.2312088	-2.3642902	-2.1024418	0.8016844	5.2501211	6.886860	-2.4063625	-2.2877588	-2.6901035	16.9901724	23.9712782	16.5320520	7.086555	31.811680	-0.9048357	-1.6678562	1.1603622	28.9207268	44.5618477	-3.666841	7.786171	-3.9046555	-3.2719316	-2.234603	-0.7787170	-2.4454937	-0.4854898	51.8917236	55.4687729	-4.0042095	-4.0649376	-4.0467749	-3.9379978	-3.9001617	34.5519409	16.4885798	44.6367302	47.7912827	42.4162483	26.6598434	27.7005157	28.6850319	53.3562202	50.1837311	-4.0634480	14.471905	-4.0648689	-4.0634480	-4.0069294	-3.7976208	10.596808	-3.8224716	-3.9880981	-3.8971100	-3.059704	5.256839	11.384635	-1.1774302	-1.9444284	-0.1822510	12.2364988	29.946171	3.8975616	2.1057129	17.2945051	19.8037748	20.2629786	30.1760979	37.8737450	28.156498	-3.8671865	8.562692	-3.9076309	-3.9750385	-1.9258471	44.1506500	-4.0649376	-4.0649376	-4.0649376	-3.9177427	-2.8327446	-4.0649376	7.9406604	-4.0649376	-4.0649376	-4.0064163	0.0244856	0.9743052	2.6664133	65.8394890	61.7238655
IgG1_PRN	2.3302751	1.5284061	1.312762	1.2526708	2.527934	3.265095	0.0390973	0.0590874	0.0821339	0.2282989	1.317252	1.5933369	1.3866634	1.1822584	0.9813663	2.6184087	1.5628617	1.4597625	1.2189078	1.9637831	3.0978546	1.5634854	1.9696234	1.4077821	1.6176035	2.6763713	0.9227967	1.0455737	1.1016996	1.9540832	1.9487071	2.8577774	3.2810180	2.9498639	3.3882244	3.0529113	1.5253774	1.5015538	1.6049281	2.6392655	2.6572075	0.2182268	0.2564871	0.2068794	2.4799263	2.494334	1.5344672	1.566151	1.4303502	1.4227457	2.0974636	3.4107304	0.5112989	1.843486	0.4193611	0.3869230	2.0340388	1.647277	3.5069757	1.2563962	1.2282653	0.9932818	1.216798	1.8467289	0.4487396	0.4134498	3.3707349	0.3858833	2.1754553	2.6102285	3.572792	2.6664202	2.8220983	2.8472536	2.9649038	3.2045157	3.831100	2.1541936	1.9555870	2.1198878	2.7180583	2.6545367	0.1403989	0.1881661	0.1485130	3.0984559	3.0723395	0.0238652	1.660880	1.460535	0.0342562	-0.0141606	2.786160	2.382360	2.349357	2.073079	2.5663631	2.995394	2.065294	2.4784529	2.2797222	2.1578963	2.2026849	2.4202814	2.839402	0.3122902	0.3543024	0.3091781	2.3934939	2.7089055	2.4153535	2.852041	3.173893	2.5625565	2.3627985	2.8233757	3.1601458	3.5226338	1.288268	1.657744	0.9038076	1.6093972	2.937497	0.8032365	0.5019591	0.8197802	3.1149364	3.1358116	-0.0158885	-0.0234716	-0.0282210	1.4140309	2.2271700	0.2206868	0.1505827	0.3618801	2.9305792	2.8109229	1.9338895	1.9715563	1.9741386	3.0881450	3.0998774	0.5012586	2.971100	0.4432147	0.5231233	2.6921661	3.0793610	2.771314	0.0864463	0.0155753	0.0531579	1.556530	2.845892	2.844586	1.2621175	1.0889679	1.4683589	2.1933625	3.179812	2.6489723	2.9351914	-0.0074402	0.0104951	0.0202065	0.9641240	1.8341732	3.209409	-0.0229982	1.884009	-0.0245340	-0.0308373	0.2108318	3.1672697	0.0080703	-0.0081838	-0.0113835	1.1235619	2.1912584	-0.0151271	1.1791268	-0.0358608	2.4212730	2.8397939	2.9442298	3.0789032	3.2451212	3.7102406	3.6079137
IgG1_FHA	3.9798987	1.3074943	2.775139	2.7162172	2.610007	4.466119	1.1000255	1.2964046	1.0654219	1.0155632	3.462704	3.0779868	2.8695170	2.6667017	1.6127404	3.6789318	2.8410999	2.6735998	2.3668498	2.5163182	4.2649152	0.5706489	1.1136343	0.5586936	1.2581201	2.5762557	-0.5095670	-0.4622746	-0.4739254	2.6338192	2.7331773	0.5687256	0.6825459	0.7097571	3.9488933	3.7824776	0.1221907	0.1164764	0.2264094	3.3014237	3.6377145	2.0085059	2.0714802	1.8988061	3.7266949	3.673672	0.4374901	1.335753	0.3717170	0.3818239	1.9495913	1.1822246	-0.4264247	1.726639	-0.4754825	-0.5280387	0.6391023	1.321251	1.3707460	0.8531209	0.8179796	0.5042351	1.891331	3.2942711	1.4763337	1.5068491	0.9277207	1.4310077	2.0294167	3.2295085	3.498641	2.4927596	2.6855317	2.7005035	2.8877724	3.5803598	4.011833	-0.2549298	-0.3366675	-0.2425478	2.4185292	2.6039118	0.0670854	0.2438335	0.0192903	2.5890876	3.6825536	0.5337200	1.585573	1.486237	0.9059108	-0.0810312	1.153540	2.665057	2.593840	2.381469	2.9708313	3.575980	2.106504	2.4290689	1.9784582	1.9055712	1.8701534	2.3277007	1.287699	-0.0170090	-0.0163279	-0.0732609	2.5352398	3.7047499	4.1133258	1.394961	2.350285	0.5799799	0.4024148	1.0056915	2.1257225	4.1480911	0.785381	1.637632	0.2076824	1.1652541	2.349523	-0.0869792	-0.4098225	-0.1122776	3.3069776	3.7830484	-0.5757387	-0.6567805	-0.6812942	2.3128041	2.4705428	1.2637515	0.6275494	1.8255118	3.0979284	2.9566852	1.7136362	1.7227243	1.7709733	3.7983873	3.9829595	-0.2913897	3.739290	-0.3788364	-0.3335061	2.1542267	3.7612966	3.447976	-0.1668885	-0.4147089	-0.2878432	0.858427	3.200371	3.664044	2.5303208	2.1850418	2.6772841	3.7956841	4.118933	3.5888239	3.6779689	1.4713572	1.5241872	1.6175817	2.0036303	3.4136063	4.128278	0.1555142	1.115403	0.1355245	-0.0785936	1.6136298	4.8011448	-0.2238851	-0.3941231	-0.3800652	1.3615637	3.0414835	-0.8278036	0.9747817	-0.8607137	-0.4145193	2.2407957	1.9300547	2.1766452	2.6932379	4.2304628	5.4043481
IgG1_TT	1.4942536	0.9973521	1.379331	1.4170711	1.796846	1.928070	-0.0360039	-0.0288292	-0.0140253	0.8696622	1.682223	1.3199177	1.1930063	1.1088042	1.0161684	1.6040348	1.5521569	1.5000563	1.3901588	1.5980810	1.9856684	1.1547807	1.4038718	1.1013944	1.5671514	1.8910602	0.5880247	0.6965237	0.7088141	1.2108815	1.1766360	1.4034187	1.4765202	1.4700419	2.1600475	1.9214078	0.5930234	0.5758677	0.6565273	1.7216183	1.7512509	0.4642359	0.5210015	0.4467803	1.7937601	1.714260	1.0216351	1.124673	0.9688684	0.9824650	1.5203966	1.4383706	0.8694136	1.336630	0.8058096	0.7870544	1.6150366	1.179712	1.5098779	1.1033545	1.1304276	0.9982610	1.699896	1.8525053	1.1550214	1.1358863	1.3819551	1.1000153	1.4653195	1.7304161	1.814931	1.0635911	1.1017058	1.1314830	1.7195905	1.9195489	1.920492	1.3685291	1.2814772	1.3553655	1.8143333	1.8979062	1.3870729	1.4858918	1.3220495	1.7977296	1.8494700	0.8648446	1.337599	1.228016	1.0060084	0.6224054	1.761833	1.122303	1.140437	1.038616	1.3817737	1.674813	1.308888	1.0800610	0.9513213	0.9583062	1.0901306	1.2242125	1.796419	0.6105509	0.6130343	0.5188916	0.9312353	1.0707971	1.5553379	1.808255	1.916253	1.3939984	1.2565922	1.5771793	1.9345006	2.0869474	1.208348	1.467166	1.0057329	1.3481827	1.700810	1.2990609	1.0670679	1.2775918	1.8736036	1.8801953	1.0300444	0.9004935	0.9077401	1.8225839	1.8273389	0.4983788	0.4345669	0.6710701	1.2743878	1.2314497	0.7593165	0.7942921	0.7942921	1.7944518	1.7833189	1.0023959	1.612163	0.9383861	0.9866675	1.6926583	1.8094931	1.538321	0.8573597	0.7265906	0.7662001	1.366540	1.585387	1.584723	0.4339992	0.3444163	0.5158718	1.4445343	1.854678	1.7826650	1.7999294	0.3297647	0.3816224	0.3880637	1.0999972	1.5073663	1.866985	0.8927280	1.348850	0.8712881	0.7685731	1.8958782	1.9645802	0.5391436	0.4918815	0.4434524	1.1476929	1.5000563	1.3814638	1.3765701	1.1853305	1.7992655	1.9187984	0.3005355	0.3416666	0.4411045	1.9997166	1.8982230
IgG1_DT	2.3434474	1.3191508	1.967139	2.0217979	1.448302	2.190173	0.1001074	0.1041317	0.1133313	0.1135072	0.836496	2.1334097	2.0159016	1.9785637	1.3979722	2.2193620	1.7488577	1.6337919	1.5996518	1.3674438	2.0013213	0.7906970	1.0359291	0.7867752	0.8694679	1.5003201	0.8892402	0.9939865	1.0110824	1.7178109	1.7381735	1.9842563	2.1171761	2.0442574	2.5044525	2.3072541	0.7548270	0.7575288	0.7926794	1.8112891	1.8893017	0.3678319	0.4097089	0.3476253	1.3384577	1.400485	1.0342594	1.255694	0.9687142	0.9999530	1.7721645	1.5257283	0.8041055	1.406089	0.7255583	0.6824431	1.2249608	1.484724	1.6530659	0.7231661	0.7358024	0.6960644	1.658798	2.2747207	0.3562089	0.3470061	1.4233210	0.3244916	0.9315922	1.6593448	2.216804	1.6687914	1.7280040	1.7732772	2.1332288	2.2117124	2.473230	0.8472020	0.7516220	0.8315351	2.1297448	2.1786358	1.7390542	1.9236616	1.6315117	2.3768060	2.4142921	1.0268353	1.514755	1.434969	1.1908613	0.5837098	1.997321	1.390063	1.385596	1.244956	1.4559491	1.543484	1.421563	0.8165235	0.6980984	0.6838788	1.4334284	1.6656978	2.001879	1.5392002	1.5567999	1.4977483	1.5682049	1.7064840	2.3852797	2.079356	2.189821	2.1406219	1.9774096	2.1734576	2.2627897	2.3363860	1.277153	1.609822	0.8592745	1.4955555	1.941961	1.7958480	1.1765940	1.6837070	1.9039556	1.8382844	0.3617326	0.2818868	0.2900680	1.2010576	1.3404669	0.5050050	0.3744706	0.7071599	1.2340920	1.0764754	1.7448934	1.7397778	1.7548145	2.0497351	1.9618660	1.9965383	2.212156	1.8250632	1.8674346	2.2089412	2.3059800	2.116932	1.3572984	1.1692365	1.2480370	2.001721	2.121985	2.187739	0.8031631	0.6984230	0.8996355	2.3154688	2.664523	2.1147001	2.0957003	0.1778489	0.2135288	0.2190577	1.2919987	2.0239849	2.650579	0.4345307	1.396243	0.4035941	0.3361375	2.3671706	2.5688765	0.9100773	0.8241493	0.8021165	1.1866343	1.3459606	0.8795633	1.5421561	0.6756542	2.4593160	2.4864340	0.1120415	0.1182027	0.1362425	2.3195801	2.3009574
IgG1_OVA	0.8001978	0.5592835	30.350330	39.2089596	19.495069	46.377276	3.0450172	3.6050940	4.9479847	0.9771068	5.386357	0.3327355	0.3227363	0.5148649	0.3227363	0.3605084	0.3227363	0.3227363	0.3913798	0.3227363	0.4160767	0.9242773	1.5706635	1.1940336	0.4660811	1.3422160	14.5366116	15.7529411	16.5370731	12.8016453	11.5854602	0.3678160	0.4332628	0.3939948	0.6034255	0.5117993	0.4332628	0.4463525	0.4398074	0.5510678	0.6557832	1.9516373	2.7500927	1.5982225	3.2605805	3.240947	1.5262306	3.520260	1.2317185	1.3037102	0.7709033	28.2506104	1.0550110	2.061579	0.7735882	0.6819620	0.7709033	5.414790	33.0687695	1.8076534	1.8207428	1.5524096	1.053312	2.5406618	0.4463525	0.4201736	20.7148361	0.3809052	0.3227363	0.7277751	15.709686	0.3806601	0.4461069	0.4853754	0.4330177	0.4591966	21.319443	0.6555381	0.5246439	0.5900910	0.6387341	0.5461202	0.4199281	0.4461069	0.3547182	0.4782033	0.4288092	9.5039954	5.019321	4.534534	14.9033871	4.6215281	5.038681	1.925213	1.912124	1.737752	1.9723744	4.244503	4.692609	1.1005788	0.7995219	0.8486590	0.6634312	0.7004766	5.312936	0.3227363	0.3227363	0.3227363	0.3227363	0.3227363	0.8999269	5.624589	4.116188	0.3227363	0.3227363	0.3227363	0.4096985	0.3712001	19.363710	3.379360	12.7755280	29.4631081	10.502678	0.4738622	0.3227363	0.4610295	0.7048521	0.6150227	0.4866948	0.3405657	0.4161148	0.4738622	0.5123606	10.5475926	7.7818193	18.1574306	13.2232265	9.8417907	4.6666846	4.5594869	4.9713526	4.7908087	3.0192215	20.4924870	3.673640	18.5121460	21.5870342	19.0551929	23.2503567	2.526756	2.7427635	1.6764259	2.0487978	2.627954	2.346531	2.514290	5.2534523	3.0925674	5.6088982	0.6443713	2.570388	6.4435239	3.8583605	2.1277859	2.7484057	3.4254453	2.7457588	1.0834007	2.707515	8.9156470	7.507787	7.9245896	5.2568383	3.1438298	0.6132059	0.6381383	0.5633416	0.5508752	0.5134768	0.7732453	0.3227363	3.7929403	0.3227363	0.3227363	0.3830795	0.3327355	0.3956656	0.4334235	0.5341115	0.4963536
IgG2_PT	2.7249775	2.7249775	2.724978	2.7249775	2.724978	2.724978	2.7249775	2.7249775	2.7249775	2.7249775	2.724978	8.0937672	7.2524505	6.8258133	7.0442319	7.3354568	2.7249775	2.7249775	2.7249775	2.7249775	2.8942785	3.4116597	3.5495343	2.8214726	4.0591779	3.7679529	2.7249775	2.7249775	2.7249775	4.5324183	5.0845618	2.9957767	3.0330768	2.8465781	3.1449757	3.1449757	2.9211774	2.9211774	2.9211774	3.3687742	3.2941747	3.1449757	4.2639675	3.7417715	4.0401692	6.651150	2.7249775	8.015645	2.7249775	2.7249775	2.7249775	2.7249775	2.7249775	7.519328	2.7249775	2.7249775	2.7249775	6.317613	2.7249775	2.7249775	2.7249775	2.7249775	2.995777	3.7417715	2.7249775	2.7249775	2.7249775	2.7249775	2.7249775	3.2195752	2.724978	2.7952142	2.7249775	2.7249775	3.1924260	9.0512962	2.724978	2.7249775	2.7249775	2.7249775	2.7249775	2.7249775	5.1784835	4.7812719	5.0764966	8.2689505	26.0730176	2.9938202	8.233890	8.801501	2.9938202	2.7249775	5.742393	33.579110	31.990262	30.616126	29.2245431	32.416997	6.199564	5.1288323	4.9798779	3.7667723	4.9946389	6.3862214	5.789866	2.7249775	2.7249775	2.7249775	2.7249775	2.7249775	2.9652591	5.837338	7.973595	2.9494348	3.1024013	2.7249775	5.5498662	8.0738144	4.479100	8.999968	5.7410746	5.0909667	4.326134	2.7249775	2.7249775	2.7249775	2.7249775	2.7964683	3.0259180	3.1788845	2.7249775	3.0259180	2.9494348	4.2496505	5.1292081	4.6703086	3.7907510	4.7850337	2.7249775	2.7249775	2.7249775	2.7249775	2.7249775	2.7249775	7.403926	2.7249775	2.7249775	2.7249775	2.7249775	5.837338	2.7249775	2.7249775	2.7249775	2.724978	5.706418	5.505031	82.5685258	77.2763810	71.4957261	2.7249775	7.285245	112.4533143	135.0982041	8.2341824	10.2696247	7.8678031	8.3092394	9.1768465	7.498871	2.7249775	7.044437	2.7249775	2.7249775	2.7249775	2.7991056	2.7249775	2.7249775	2.7249775	2.7249775	2.7249775	2.7249775	7.1914103	2.7249775	2.7249775	2.7249775	2.7249775	2.7249775	2.7249775	3.2653439	3.1190281

# knitr::kable(head(results$rnaseq), "html", align = "lccrr", booktabs=TRUE, border_left = T, 
#              border_right = T, caption = "RNA seq")  %>% 
#   kable_styling("striped", full_width = T) %>% 
#   scroll_box(width = "100%", height = "400px")
# 
# knitr::kable(head(results$cytof), "html", align = "lccrr", booktabs=TRUE, border_left = T, 
#              border_right = T, caption = "Cell Frequency")  %>% 
#   kable_styling("striped", full_width = T) %>% 
#   scroll_box(width = "100%", height = "400px")
# 
# olink <- head(results$olink)
# knitr::kable(, "html", align = "lccrr", booktabs=TRUE, border_left = T, 
#              border_right = T, caption = "Olink")  %>% 
#   kable_styling("striped", full_width = T) %>% 
#   scroll_box(width = "100%", height = "400px")

Imputation using MOFA for 2020 Data set

2023-09-07

Load libraries

Load data and Generate Mofa object

Plot multiomic missing values

Setting data Options

Setting model Options

Setting training Options

Training Model

Impute Data

Add meta data to Mofa and Imputed objects

Mofa object

Imputed data

Results for Actual Data

Results for Imputed Data