Last updated: 2021-03-03

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The following document outlines and summarizes the GWAS results performed in PSYMETAB, for an overview of the method see GWAS Method.

Model counts and distributions.

Parsed with column specification:
cols(
  COUNT = col_double(),
  GPCR = col_character(),
  eth = col_character()
)
Joining, by = "FID"
Joining, by = "FID"
Drug_class Interaction_outcome Sensitivity_Model N Drug_CEU NoDrug_CEU Drug_MIXED NoDrug_MIXED Drug_YRI NoDrug_YRI
all BMI_slope No 1317 273 770 62 176 9 27
all BMI_slope Yes 1317 273 770 62 176 9 27
all LDL_slope No 759 153 453 39 92 8 14
all LDL_slope Yes 759 153 453 39 92 8 14
all BMI_slope_6mo No 1130 228 672 54 147 8 21
all BMI_slope_6mo Yes 1130 228 672 54 147 8 21
all LDL_slope_6mo No 673 138 400 33 81 8 13
all LDL_slope_6mo Yes 673 138 400 33 81 8 13
all BMI_slope_weight No 864 188 499 45 109 3 20
all BMI_slope_weight Yes 864 188 499 45 109 3 20
all LDL_slope_weight No 303 78 173 18 27 3 4
all LDL_slope_weight Yes 303 78 173 18 27 3 4
all BMI_slope_weight_6mo No 687 140 408 37 87 2 13
all BMI_slope_weight_6mo Yes 687 140 408 37 87 2 13
all LDL_slope_weight_6mo No 212 60 122 14 14 1 1
all LDL_slope_weight_6mo Yes 212 60 122 14 14 1 1
all BMI_change No 1317 273 770 62 176 9 27
all BMI_change Yes 1317 273 770 62 176 9 27
all LDL_change No 493 97 296 28 55 8 9
all LDL_change Yes 493 97 296 28 55 8 9
all BMI_change_1mo No 372 71 217 26 45 3 10
all BMI_change_1mo Yes 372 71 217 26 45 3 10
all LDL_change_1mo No 176 39 100 10 19 3 5
all LDL_change_1mo Yes 176 39 100 10 19 3 5
all BMI_change_3mo No 1002 203 592 51 131 7 18
all BMI_change_3mo Yes 1002 203 592 51 131 7 18
all LDL_change_3mo No 441 89 262 20 53 6 11
all LDL_change_3mo Yes 441 89 262 20 53 6 11
all BMI_change_6mo No 1132 228 673 55 147 8 21
all BMI_change_6mo Yes 1132 228 673 55 147 8 21
all LDL_change_6mo No 503 103 303 27 53 7 10
all LDL_change_6mo Yes 503 103 303 27 53 7 10
olanz_cloz BMI_slope No 1361 201 882 47 193 8 30
olanz_cloz BMI_slope Yes 1361 201 882 47 193 8 30
olanz_cloz LDL_slope No 784 111 518 31 100 7 17
olanz_cloz LDL_slope Yes 784 111 518 31 100 7 17
olanz_cloz BMI_slope_6mo No 1168 168 767 40 162 7 24
olanz_cloz BMI_slope_6mo Yes 1168 168 767 40 162 7 24
olanz_cloz LDL_slope_6mo No 693 100 456 26 88 7 16
olanz_cloz LDL_slope_6mo Yes 693 100 456 26 88 7 16
olanz_cloz BMI_slope_weight No 887 133 573 35 121 2 23
olanz_cloz BMI_slope_weight Yes 887 133 573 35 121 2 23
olanz_cloz LDL_slope_weight No 301 56 193 14 30 2 6
olanz_cloz LDL_slope_weight Yes 301 56 193 14 30 2 6
olanz_cloz BMI_slope_weight_6mo No 707 96 468 27 99 1 16
olanz_cloz BMI_slope_weight_6mo Yes 707 96 468 27 99 1 16
olanz_cloz LDL_slope_weight_6mo No 209 41 137 11 17 1 2
olanz_cloz LDL_slope_weight_6mo Yes 209 41 137 11 17 1 2
olanz_cloz BMI_change No 1361 201 882 47 193 8 30
olanz_cloz BMI_change Yes 1361 201 882 47 193 8 30
olanz_cloz LDL_change No 501 69 333 24 59 7 9
olanz_cloz LDL_change Yes 501 69 333 24 59 7 9
olanz_cloz BMI_change_1mo No 391 58 250 18 51 3 11
olanz_cloz BMI_change_1mo Yes 391 58 250 18 51 3 11
olanz_cloz LDL_change_1mo No 188 33 116 8 22 3 6
olanz_cloz LDL_change_1mo Yes 188 33 116 8 22 3 6
olanz_cloz BMI_change_3mo No 1033 153 671 38 145 6 20
olanz_cloz BMI_change_3mo Yes 1033 153 671 38 145 6 20
olanz_cloz LDL_change_3mo No 449 66 292 17 57 5 12
olanz_cloz LDL_change_3mo Yes 449 66 292 17 57 5 12
olanz_cloz BMI_change_6mo No 1170 168 768 41 162 7 24
olanz_cloz BMI_change_6mo Yes 1170 168 768 41 162 7 24
olanz_cloz LDL_change_6mo No 515 76 341 22 58 7 11
olanz_cloz LDL_change_6mo Yes 515 76 341 22 58 7 11
valproate BMI_slope No 1386 83 1006 17 235 1 44
valproate BMI_slope Yes 1386 83 1006 17 235 1 44
valproate LDL_slope No 802 48 594 9 126 1 24
valproate LDL_slope Yes 802 48 594 9 126 1 24
valproate BMI_slope_6mo No 1196 71 872 16 200 1 36
valproate BMI_slope_6mo Yes 1196 71 872 16 200 1 36
valproate LDL_slope_6mo No 708 44 523 8 109 1 23
valproate LDL_slope_6mo Yes 708 44 523 8 109 1 23
valproate BMI_slope_weight No 924 61 663 12 154 1 33
valproate BMI_slope_weight Yes 924 61 663 12 154 1 33
valproate LDL_slope_weight No 322 24 234 4 48 1 11
valproate LDL_slope_weight Yes 322 24 234 4 48 1 11
valproate BMI_slope_weight_6mo No 740 50 528 11 125 1 25
valproate BMI_slope_weight_6mo Yes 740 50 528 11 125 1 25
valproate LDL_slope_weight_6mo No 217 19 164 3 25 0 6
valproate LDL_slope_weight_6mo Yes 217 19 164 3 25 0 6
valproate BMI_change No 1386 83 1006 17 235 1 44
valproate BMI_change Yes 1386 83 1006 17 235 1 44
valproate LDL_change No 514 32 384 4 75 1 18
valproate LDL_change Yes 514 32 384 4 75 1 18
valproate BMI_change_1mo No 380 18 275 8 66 0 13
valproate BMI_change_1mo Yes 380 18 275 8 66 0 13
valproate LDL_change_1mo No 177 8 133 2 28 0 6
valproate LDL_change_1mo Yes 177 8 133 2 28 0 6
valproate BMI_change_3mo No 1054 59 769 15 178 1 32
valproate BMI_change_3mo Yes 1054 59 769 15 178 1 32
valproate LDL_change_3mo No 463 27 345 4 67 1 19
valproate LDL_change_3mo Yes 463 27 345 4 67 1 19
valproate BMI_change_6mo No 1197 71 873 16 200 1 36
valproate BMI_change_6mo Yes 1197 71 873 16 200 1 36
valproate LDL_change_6mo No 523 32 396 6 71 0 18
valproate LDL_change_6mo Yes 523 32 396 6 71 0 18
olanz BMI_slope No 1369 125 967 42 199 6 30
olanz BMI_slope Yes 1369 125 967 42 199 6 30
olanz LDL_slope No 785 72 560 29 102 5 17
olanz LDL_slope Yes 785 72 560 29 102 5 17
olanz BMI_slope_6mo No 1171 107 832 35 168 5 24
olanz BMI_slope_6mo Yes 1171 107 832 35 168 5 24
olanz LDL_slope_6mo No 692 64 493 24 90 5 16
olanz LDL_slope_6mo Yes 692 64 493 24 90 5 16
olanz BMI_slope_weight No 892 75 636 31 125 2 23
olanz BMI_slope_weight Yes 892 75 636 31 125 2 23
olanz LDL_slope_weight No 298 32 214 13 31 2 6
olanz LDL_slope_weight Yes 298 32 214 13 31 2 6
olanz BMI_slope_weight_6mo No 706 56 507 24 102 1 16
olanz BMI_slope_weight_6mo Yes 706 56 507 24 102 1 16
olanz LDL_slope_weight_6mo No 208 26 151 10 18 1 2
olanz LDL_slope_weight_6mo Yes 208 26 151 10 18 1 2
olanz BMI_change No 1369 125 967 42 199 6 30
olanz BMI_change Yes 1369 125 967 42 199 6 30
olanz LDL_change No 504 50 357 22 61 5 9
olanz LDL_change Yes 504 50 357 22 61 5 9
olanz BMI_change_1mo No 392 41 269 16 53 2 11
olanz BMI_change_1mo Yes 392 41 269 16 53 2 11
olanz LDL_change_1mo No 189 24 126 7 24 2 6
olanz LDL_change_1mo Yes 189 24 126 7 24 2 6
olanz BMI_change_3mo No 1035 99 728 34 150 4 20
olanz BMI_change_3mo Yes 1035 99 728 34 150 4 20
olanz LDL_change_3mo No 453 46 317 16 59 3 12
olanz LDL_change_3mo Yes 453 46 317 16 59 3 12
olanz BMI_change_6mo No 1173 107 833 36 168 5 24
olanz BMI_change_6mo Yes 1173 107 833 36 168 5 24
olanz LDL_change_6mo No 516 54 366 20 60 5 11
olanz LDL_change_6mo Yes 516 54 366 20 60 5 11
cloza BMI_slope No 1452 84 1057 7 256 2 46
cloza BMI_slope Yes 1452 84 1057 7 256 2 46
cloza LDL_slope No 845 42 632 4 138 2 27
cloza LDL_slope Yes 845 42 632 4 138 2 27
cloza BMI_slope_6mo No 1257 69 922 7 219 2 38
cloza BMI_slope_6mo Yes 1257 69 922 7 219 2 38
cloza LDL_slope_6mo No 744 39 554 3 120 2 26
cloza LDL_slope_6mo Yes 744 39 554 3 120 2 26
cloza BMI_slope_weight No 966 63 694 5 169 0 35
cloza BMI_slope_weight Yes 966 63 694 5 169 0 35
cloza LDL_slope_weight No 332 26 241 1 51 0 13
cloza LDL_slope_weight Yes 332 26 241 1 51 0 13
cloza BMI_slope_weight_6mo No 778 44 563 3 141 0 27
cloza BMI_slope_weight_6mo Yes 778 44 563 3 141 0 27
cloza LDL_slope_weight_6mo No 222 17 170 1 27 0 7
cloza LDL_slope_weight_6mo Yes 222 17 170 1 27 0 7
cloza BMI_change No 1452 84 1057 7 256 2 46
cloza BMI_change Yes 1452 84 1057 7 256 2 46
cloza LDL_change No 528 20 404 3 81 2 18
cloza LDL_change Yes 528 20 404 3 81 2 18
cloza BMI_change_1mo No 409 23 298 2 71 1 14
cloza BMI_change_1mo Yes 409 23 298 2 71 1 14
cloza LDL_change_1mo No 195 12 144 1 30 1 7
cloza LDL_change_1mo Yes 195 12 144 1 30 1 7
cloza BMI_change_3mo No 1106 61 808 6 196 2 33
cloza BMI_change_3mo Yes 1106 61 808 6 196 2 33
cloza LDL_change_3mo No 474 23 354 2 73 2 20
cloza LDL_change_3mo Yes 474 23 354 2 73 2 20
cloza BMI_change_6mo No 1258 69 923 7 219 2 38
cloza BMI_change_6mo Yes 1258 69 923 7 219 2 38
cloza LDL_change_6mo No 541 24 415 3 78 2 19
cloza LDL_change_6mo Yes 541 24 415 3 78 2 19
risp BMI_slope No 1367 223 855 59 185 17 28
risp BMI_slope Yes 1211 223 724 59 162 17 26
risp LDL_slope No 798 127 507 34 101 13 16
risp LDL_slope Yes 714 127 437 34 88 13 15
risp BMI_slope_6mo No 1178 199 733 53 156 14 23
risp BMI_slope_6mo Yes 1058 199 634 53 136 14 22
risp LDL_slope_6mo No 704 110 448 30 88 13 15
risp LDL_slope_6mo Yes 631 110 386 30 78 13 14
risp BMI_slope_weight No 903 142 570 39 120 11 21
risp BMI_slope_weight Yes 795 142 479 39 104 11 20
risp LDL_slope_weight No 304 44 199 8 39 8 6
risp LDL_slope_weight Yes 268 44 169 8 34 8 5
risp BMI_slope_weight_6mo No 723 115 452 34 98 8 16
risp BMI_slope_weight_6mo Yes 649 115 390 34 86 8 16
risp LDL_slope_weight_6mo No 201 33 136 4 21 4 3
risp LDL_slope_weight_6mo Yes 175 33 114 4 17 4 3
risp BMI_change No 1367 223 855 59 185 17 28
risp BMI_change Yes 1211 223 724 59 162 17 26
risp LDL_change No 503 74 324 21 61 12 11
risp LDL_change Yes 451 74 282 21 52 12 10
risp BMI_change_1mo No 386 64 238 22 46 7 9
risp BMI_change_1mo Yes 352 64 209 22 41 7 9
risp LDL_change_1mo No 183 22 120 13 19 4 5
risp LDL_change_1mo Yes 165 22 104 13 17 4 5
risp BMI_change_3mo No 1043 177 641 51 139 14 21
risp BMI_change_3mo Yes 937 177 553 51 122 14 20
risp LDL_change_3mo No 447 68 285 22 48 13 11
risp LDL_change_3mo Yes 402 68 247 22 42 13 10
risp BMI_change_6mo No 1179 199 734 53 156 14 23
risp BMI_change_6mo Yes 1059 199 635 53 136 14 22
risp LDL_change_6mo No 513 77 337 18 58 12 11
risp LDL_change_6mo Yes 458 77 291 18 50 12 10
quet BMI_slope No 1286 414 596 84 150 13 29
quet BMI_slope Yes 1153 414 484 84 131 13 27
quet LDL_slope No 763 264 346 44 82 10 17
quet LDL_slope Yes 688 264 283 44 71 10 16
quet BMI_slope_6mo No 1100 358 509 66 132 12 23
quet BMI_slope_6mo Yes 998 358 425 66 115 12 22
quet LDL_slope_6mo No 671 232 304 40 69 10 16
quet LDL_slope_6mo Yes 607 232 249 40 61 10 15
quet BMI_slope_weight No 862 285 395 51 101 11 19
quet BMI_slope_weight Yes 771 285 318 51 88 11 18
quet LDL_slope_weight No 312 118 130 21 31 5 7
quet LDL_slope_weight Yes 281 118 105 21 26 5 6
quet BMI_slope_weight_6mo No 698 233 315 47 79 10 14
quet BMI_slope_weight_6mo Yes 636 233 263 47 69 10 14
quet LDL_slope_weight_6mo No 215 77 102 13 14 5 4
quet LDL_slope_weight_6mo Yes 190 77 82 13 9 5 4
quet BMI_change No 1286 414 596 84 150 13 29
quet BMI_change Yes 1153 414 484 84 131 13 27
quet LDL_change No 486 173 220 28 46 7 12
quet LDL_change Yes 438 173 180 28 39 7 11
quet BMI_change_1mo No 352 116 165 18 42 4 7
quet BMI_change_1mo Yes 319 116 137 18 37 4 7
quet LDL_change_1mo No 184 69 81 10 18 3 3
quet LDL_change_1mo Yes 163 69 63 10 15 3 3
quet BMI_change_3mo No 972 316 448 63 116 10 19
quet BMI_change_3mo Yes 882 316 374 63 101 10 18
quet LDL_change_3mo No 433 147 201 25 42 6 12
quet LDL_change_3mo Yes 392 147 166 25 37 6 11
quet BMI_change_6mo No 1101 358 510 66 132 12 23
quet BMI_change_6mo Yes 999 358 426 66 115 12 22
quet LDL_change_6mo No 489 172 228 25 43 9 12
quet LDL_change_6mo Yes 438 172 184 25 37 9 11
ocq BMI_slope No 1263 586 412 120 108 19 18
ocq BMI_slope Yes 1263 586 412 120 108 19 18
ocq LDL_slope No 737 351 237 66 57 15 11
ocq LDL_slope Yes 737 351 237 66 57 15 11
ocq BMI_slope_6mo No 1077 499 354 98 95 17 14
ocq BMI_slope_6mo Yes 1077 499 354 98 95 17 14
ocq LDL_slope_6mo No 650 312 206 58 49 15 10
ocq LDL_slope_6mo Yes 650 312 206 58 49 15 10
ocq BMI_slope_weight No 832 394 265 77 72 12 12
ocq BMI_slope_weight Yes 832 394 265 77 72 12 12
ocq LDL_slope_weight No 295 157 84 27 17 7 3
ocq LDL_slope_weight Yes 295 157 84 27 17 7 3
ocq BMI_slope_weight_6mo No 667 308 219 68 54 10 8
ocq BMI_slope_weight_6mo Yes 667 308 219 68 54 10 8
ocq LDL_slope_weight_6mo No 208 108 65 19 9 6 1
ocq LDL_slope_weight_6mo Yes 208 108 65 19 9 6 1
ocq BMI_change No 1263 586 412 120 108 19 18
ocq BMI_change Yes 1263 586 412 120 108 19 18
ocq LDL_change No 478 227 154 44 34 12 7
ocq LDL_change Yes 478 227 154 44 34 12 7
ocq BMI_change_1mo No 355 164 114 33 30 7 7
ocq BMI_change_1mo Yes 355 164 114 33 30 7 7
ocq LDL_change_1mo No 182 94 51 16 12 6 3
ocq LDL_change_1mo Yes 182 94 51 16 12 6 3
ocq BMI_change_3mo No 957 444 311 93 83 15 11
ocq BMI_change_3mo Yes 957 444 311 93 83 15 11
ocq LDL_change_3mo No 424 201 136 35 34 10 8
ocq LDL_change_3mo Yes 424 201 136 35 34 10 8
ocq BMI_change_6mo No 1078 499 355 98 95 17 14
ocq BMI_change_6mo Yes 1078 499 355 98 95 17 14
ocq LDL_change_6mo No 485 235 155 40 34 14 7
ocq LDL_change_6mo Yes 485 235 155 40 34 14 7
ami BMI_slope No 1403 119 989 45 205 11 34
ami BMI_slope Yes 462 119 209 45 67 11 11
ami LDL_slope No 819 79 583 23 108 7 19
ami LDL_slope Yes 268 79 119 23 37 7 3
ami BMI_slope_6mo No 1205 110 844 42 171 11 27
ami BMI_slope_6mo Yes 417 110 187 42 59 11 8
ami LDL_slope_6mo No 719 66 515 20 93 7 18
ami LDL_slope_6mo Yes 232 66 104 20 32 7 3
ami BMI_slope_weight No 933 86 650 39 124 8 26
ami BMI_slope_weight Yes 321 86 140 39 41 8 7
ami LDL_slope_weight No 315 26 228 11 38 2 10
ami LDL_slope_weight Yes 98 26 44 11 14 2 1
ami BMI_slope_weight_6mo No 746 72 515 31 104 6 18
ami BMI_slope_weight_6mo Yes 257 72 111 31 33 6 4
ami LDL_slope_weight_6mo No 207 21 157 2 22 1 4
ami LDL_slope_weight_6mo Yes 59 21 29 2 6 1 0
ami BMI_change No 1403 119 989 45 205 11 34
ami BMI_change Yes 462 119 209 45 67 11 11
ami LDL_change No 517 51 372 10 66 5 13
ami LDL_change Yes 166 51 78 10 21 5 1
ami BMI_change_1mo No 386 31 277 13 54 1 10
ami BMI_change_1mo Yes 118 31 53 13 17 1 3
ami LDL_change_1mo No 186 12 140 3 25 1 5
ami LDL_change_1mo Yes 50 12 28 3 5 1 1
ami BMI_change_3mo No 1055 97 737 40 150 9 22
ami BMI_change_3mo Yes 362 97 164 40 47 9 5
ami LDL_change_3mo No 459 39 331 13 56 5 15
ami LDL_change_3mo Yes 146 39 71 13 17 5 1
ami BMI_change_6mo No 1206 110 845 42 171 11 27
ami BMI_change_6mo Yes 417 110 187 42 59 11 8
ami LDL_change_6mo No 525 49 388 11 59 5 13
ami LDL_change_6mo Yes 166 49 81 11 19 5 1

GWAS results.

Baseline

Interaction

Subgroup

het_out <-
  fread(
    paste0("analysis/GWAS/subgroup/", eth, "/", output, "_", suffix,
      "_", eth, ".", outcome_var, ".het"),
    header = F,
    data.table = F
  )

sig_list <- which(as.numeric(het_out[, 2]) < 5e-08)
length(sig_list)
colnames(het_out) <- c("ID", "P_HET")
result <- cbind(filter, "P_HET" = het_out$P_HET)
png(
  paste0("analysis/GWAS/subgroup/", eth, "/", output, "_", suffix, "_", eth, ".", outcome_var, ".het.manhattan.png"),
  width = 2000,
  height = 1000,
  pointsize = 18
)
manhattan(result, p = "P_HET", chr = "CHROM")
dev.off()

png(
  paste0(
    "analysis/GWAS/subgroup/", eth, "/", output, "_", suffix, "_", eth, ".", outcome_var, ".het.qq.png"),
  width = 2000,
  height = 1000, 
  pointsize = 18
)
qq(result$P_HET)
dev.off()


#### GWAS
    sig_nodrug <-nodrug[ which(nodrug$P < 5e-08),]
    sig_drug <- drug[which(drug$P < 5e-08),]
    for(data in c("nodrug", "drug"))
    {
      gwas_result <- get(data)
      joint <- reduce(list(gwas_result,freq,info), full_join, by = "ID")
      sig <- joint %>%
              mutate_at("P", as.numeric) %>%
              filter(P < 5e-06) %>%
              filter(ALT_FREQS > maf_threshold & ALT_FREQS < (1 - maf_threshold)) %>%
              filter(R2 > info_threshold)

      joint_maf <- joint %>% filter(ALT_FREQS > maf_threshold & ALT_FREQS < (1- maf_threshold))%>% mutate_at("P", as.numeric)
      sig <- joint_maf  %>% filter(P < gw_sig)
      png("man_interaction.png", width=2000, height=1000, pointsize=18)
      manhattan(joint_maf)
      dev.off()

      png("interaction_qq2.png", width=2000, height=1000, pointsize=18)
      qq(joint_maf$P)
      dev.off()

            qq(gwas_result2$P)
    # sig_nodrug <- sig
    }
    
    gwas_result <- fread(result, data.table=F, stringsAsFactors=F)
  gwas_result2 <- gwas_result %>% rename(CHR = "#CHROM") %>% rename(BP = POS) %>% filter(!is.na(P))


  #### GWAS
  sig_nodrug <-nodrug[ which(nodrug$P < 5e-08),]
  sig_drug <- drug[which(drug$P < 5e-08),]

  for(data in c("nodrug", "drug"))
  {
  gwas_result <- get(data)
  gwas_munge <- gwas_result %>% rename(CHR = "#CHROM") %>% rename(BP = POS) %>% filter(!is.na(P))
  joint <- reduce(list(gwas_munge,freq,info), full_join, by = "ID")
  sig <- joint %>%
          mutate_at("P", as.numeric) %>%
          filter(P < 5e-06) %>%
          filter(ALT_FREQS > maf_threshold & ALT_FREQS < (1 - maf_threshold)) %>%
          filter(R2 > info_threshold)
  # sig_nodrug <- sig
  }

sessionInfo()
R version 3.5.3 (2019-03-11)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS: /data/sgg2/jenny/bin/R-3.5.3/lib64/R/lib/libRblas.so
LAPACK: /data/sgg2/jenny/bin/R-3.5.3/lib64/R/lib/libRlapack.so

locale:
[1] en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] tidyselect_0.2.5        rbgen_0.1               ukbtools_0.11.3        
 [4] hrbrthemes_0.8.0        OpenImageR_1.1.6        fuzzyjoin_0.1.5        
 [7] kableExtra_1.1.0        R.utils_2.9.2           R.oo_1.23.0            
[10] R.methodsS3_1.7.1       TwoSampleMR_0.4.25      reader_1.0.6           
[13] NCmisc_1.1.6            optparse_1.6.4          readxl_1.3.1           
[16] ggthemes_4.2.0          tryCatchLog_1.1.6       futile.logger_1.4.3    
[19] DataExplorer_0.8.0      taRifx_1.0.6.1          qqman_0.1.4            
[22] MASS_7.3-51.5           bit64_0.9-7             bit_1.1-14             
[25] rslurm_0.5.0            rmeta_3.0               devtools_2.2.1         
[28] usethis_1.5.1           data.table_1.12.8       clustermq_0.8.8.1      
[31] future.batchtools_0.8.1 future_1.15.1           rlang_0.4.5            
[34] knitr_1.26              drake_7.12.0.9000       forcats_0.4.0          
[37] stringr_1.4.0           dplyr_0.8.3             purrr_0.3.3            
[40] readr_1.3.1             tidyr_1.0.3             tibble_2.1.3           
[43] ggplot2_3.3.2           tidyverse_1.3.0         pacman_0.5.1           
[46] processx_3.4.1          workflowr_1.6.0        

loaded via a namespace (and not attached):
  [1] backports_1.1.6      systemfonts_0.2.3    plyr_1.8.5          
  [4] igraph_1.2.5         storr_1.2.1          listenv_0.8.0       
  [7] digest_0.6.25        foreach_1.4.7        htmltools_0.4.0     
 [10] tiff_0.1-5           fansi_0.4.1          magrittr_1.5        
 [13] checkmate_1.9.4      memoise_1.1.0        base64url_1.4       
 [16] doParallel_1.0.15    remotes_2.1.0        globals_0.12.5      
 [19] extrafont_0.17       modelr_0.1.5         extrafontdb_1.0     
 [22] prettyunits_1.1.0    jpeg_0.1-8.1         colorspace_1.4-1    
 [25] rvest_0.3.5          rappdirs_0.3.1       haven_2.2.0         
 [28] xfun_0.11            callr_3.4.0          crayon_1.3.4        
 [31] jsonlite_1.6         iterators_1.0.12     brew_1.0-6          
 [34] glue_1.4.0           gtable_0.3.0         webshot_0.5.2       
 [37] pkgbuild_1.0.6       Rttf2pt1_1.3.8       scales_1.1.0        
 [40] futile.options_1.0.1 DBI_1.1.0            Rcpp_1.0.3          
 [43] xtable_1.8-4         viridisLite_0.3.0    progress_1.2.2      
 [46] txtq_0.2.0           htmlwidgets_1.5.1    httr_1.4.1          
 [49] getopt_1.20.3        calibrate_1.7.5      ellipsis_0.3.0      
 [52] XML_3.98-1.20        pkgconfig_2.0.3      dbplyr_1.4.2        
 [55] reshape2_1.4.3       later_1.0.0          munsell_0.5.0       
 [58] cellranger_1.1.0     tools_3.5.3          cli_2.0.1           
 [61] generics_0.0.2       broom_0.5.3          fastmap_1.0.1       
 [64] evaluate_0.14        yaml_2.2.0           fs_1.3.1            
 [67] packrat_0.5.0        nlme_3.1-143         mime_0.8            
 [70] whisker_0.4          formatR_1.7          proftools_0.99-2    
 [73] xml2_1.2.2           compiler_3.5.3       rstudioapi_0.10     
 [76] png_0.1-7            filelock_1.0.2       testthat_2.3.1      
 [79] reprex_0.3.0         stringi_1.4.5        highr_0.8           
 [82] ps_1.3.0             desc_1.2.0           gdtools_0.2.2       
 [85] lattice_0.20-38      vctrs_0.2.4          pillar_1.4.3        
 [88] lifecycle_0.1.0      networkD3_0.4        httpuv_1.5.2        
 [91] R6_2.4.1             promises_1.1.0       gridExtra_2.3       
 [94] sessioninfo_1.1.1    codetools_0.2-16     lambda.r_1.2.4      
 [97] assertthat_0.2.1     pkgload_1.0.2        rprojroot_1.3-2     
[100] withr_2.1.2          batchtools_0.9.12    parallel_3.5.3      
[103] hms_0.5.3            grid_3.5.3           rmarkdown_1.18      
[106] git2r_0.26.1         shiny_1.4.0          lubridate_1.7.4