EDA_2
540325674
2026-04-17
Data Acquisition
Downloaded three GEO files: 1. Expression matrix (series_matrix) 2. Metadata (SOFT via GEOquery)
32,049 genes measured across 388 samples
data <- read.table("GSE63061_series_matrix.txt",
header = TRUE,
sep = "\t",
comment.char = "!",
check.names = FALSE)
dim(data)## [1] 32049 389head(data[,1:5])## ID_REF GSM1539409 GSM1539410 GSM1539411 GSM1539412
## 1 ILMN_1343291 12.552807 12.711459 13.088393 12.643831
## 2 ILMN_1343295 10.101556 9.776015 9.594397 10.126782
## 3 ILMN_1651209 6.084671 6.255012 6.160485 6.109219
## 4 ILMN_1651210 6.068805 6.016468 6.024322 6.016118
## 5 ILMN_1651221 6.121060 6.173167 6.039552 6.111306
## 6 ILMN_1651228 10.833984 10.270673 10.430594 10.765207data <- as.matrix(data)
mode(data) <- "numeric"## Warning in mde(x): NAs introduced by coerciondata <- na.omit(data)
summary(data)## ID_REF GSM1539409 GSM1539410 GSM1539411 GSM1539412
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539413 GSM1539414 GSM1539415 GSM1539416 GSM1539417
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539418 GSM1539419 GSM1539420 GSM1539421 GSM1539422
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539423 GSM1539424 GSM1539425 GSM1539426 GSM1539427
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539428 GSM1539429 GSM1539430 GSM1539431 GSM1539432
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539433 GSM1539434 GSM1539435 GSM1539436 GSM1539437
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539438 GSM1539439 GSM1539440 GSM1539441 GSM1539442
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539443 GSM1539444 GSM1539445 GSM1539446 GSM1539447
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539448 GSM1539449 GSM1539450 GSM1539451 GSM1539452
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539453 GSM1539454 GSM1539455 GSM1539456 GSM1539457
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539458 GSM1539459 GSM1539460 GSM1539461 GSM1539462
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539463 GSM1539464 GSM1539465 GSM1539466 GSM1539467
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539468 GSM1539469 GSM1539470 GSM1539471 GSM1539472
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539473 GSM1539474 GSM1539475 GSM1539476 GSM1539477
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539478 GSM1539479 GSM1539480 GSM1539481 GSM1539482
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539483 GSM1539484 GSM1539485 GSM1539486 GSM1539487
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539488 GSM1539489 GSM1539490 GSM1539491 GSM1539492
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539493 GSM1539494 GSM1539495 GSM1539496 GSM1539497
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539498 GSM1539499 GSM1539500 GSM1539501 GSM1539502
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539503 GSM1539504 GSM1539505 GSM1539506 GSM1539507
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539508 GSM1539509 GSM1539510 GSM1539511 GSM1539512
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539513 GSM1539514 GSM1539515 GSM1539516 GSM1539517
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539518 GSM1539519 GSM1539520 GSM1539521 GSM1539522
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539523 GSM1539524 GSM1539525 GSM1539526 GSM1539527
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539528 GSM1539529 GSM1539530 GSM1539531 GSM1539532
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539533 GSM1539534 GSM1539535 GSM1539536 GSM1539537
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539538 GSM1539539 GSM1539540 GSM1539541 GSM1539542
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539543 GSM1539544 GSM1539545 GSM1539546 GSM1539547
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539548 GSM1539549 GSM1539550 GSM1539551 GSM1539552
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539553 GSM1539554 GSM1539555 GSM1539556 GSM1539557
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539558 GSM1539559 GSM1539560 GSM1539561 GSM1539562
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539563 GSM1539564 GSM1539565 GSM1539566 GSM1539567
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539568 GSM1539569 GSM1539570 GSM1539571 GSM1539572
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539573 GSM1539574 GSM1539575 GSM1539576 GSM1539577
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539578 GSM1539579 GSM1539580 GSM1539581 GSM1539582
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539583 GSM1539584 GSM1539585 GSM1539586 GSM1539587
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539588 GSM1539589 GSM1539590 GSM1539591 GSM1539592
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539593 GSM1539594 GSM1539595 GSM1539596 GSM1539597
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539598 GSM1539599 GSM1539600 GSM1539601 GSM1539602
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
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## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539603 GSM1539604 GSM1539605 GSM1539606 GSM1539607
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
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## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539608 GSM1539609 GSM1539610 GSM1539611 GSM1539612
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
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## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539613 GSM1539614 GSM1539615 GSM1539616 GSM1539617
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
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## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
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## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539618 GSM1539619 GSM1539620 GSM1539621 GSM1539622
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
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## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
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## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539623 GSM1539624 GSM1539625 GSM1539626 GSM1539627
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
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## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539628 GSM1539629 GSM1539630 GSM1539631 GSM1539632
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
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## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
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## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539633 GSM1539634 GSM1539635 GSM1539636 GSM1539637
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
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## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539638 GSM1539639 GSM1539640 GSM1539641 GSM1539642
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## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539643 GSM1539644 GSM1539645 GSM1539646 GSM1539647
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539648 GSM1539649 GSM1539650 GSM1539651 GSM1539652
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539653 GSM1539654 GSM1539655 GSM1539656 GSM1539657
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539658 GSM1539659 GSM1539660 GSM1539661 GSM1539662
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539663 GSM1539664 GSM1539665 GSM1539666 GSM1539667
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539668 GSM1539669 GSM1539670 GSM1539671 GSM1539672
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539673 GSM1539674 GSM1539675 GSM1539676 GSM1539677
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539678 GSM1539679 GSM1539680 GSM1539681 GSM1539682
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539683 GSM1539684 GSM1539685 GSM1539686 GSM1539687
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539688 GSM1539689 GSM1539690 GSM1539691 GSM1539692
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539693 GSM1539694 GSM1539695 GSM1539696 GSM1539697
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539698 GSM1539699 GSM1539700 GSM1539701 GSM1539702
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539703 GSM1539704 GSM1539705 GSM1539706 GSM1539707
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539708 GSM1539709 GSM1539710 GSM1539711 GSM1539712
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539713 GSM1539714 GSM1539715 GSM1539716 GSM1539717
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539718 GSM1539719 GSM1539720 GSM1539721 GSM1539722
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539723 GSM1539724 GSM1539725 GSM1539726 GSM1539727
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539728 GSM1539729 GSM1539730 GSM1539731 GSM1539732
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539733 GSM1539734 GSM1539735 GSM1539736 GSM1539737
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539738 GSM1539739 GSM1539740 GSM1539741 GSM1539742
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539743 GSM1539744 GSM1539745 GSM1539746 GSM1539747
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539748 GSM1539749 GSM1539750 GSM1539751 GSM1539752
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539753 GSM1539754 GSM1539755 GSM1539756 GSM1539757
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539758 GSM1539759 GSM1539760 GSM1539761 GSM1539762
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539763 GSM1539764 GSM1539765 GSM1539766 GSM1539767
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539768 GSM1539769 GSM1539770 GSM1539771 GSM1539772
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539773 GSM1539774 GSM1539775 GSM1539776 GSM1539777
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539778 GSM1539779 GSM1539780 GSM1539781 GSM1539782
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539783 GSM1539784 GSM1539785 GSM1539786 GSM1539787
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539788 GSM1539789 GSM1539790 GSM1539791 GSM1539792
## Min. : NA Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NA Max. : NA
## GSM1539793 GSM1539794 GSM1539795 GSM1539796
## Min. : NA Min. : NA Min. : NA Min. : NA
## 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA 1st Qu.: NA
## Median : NA Median : NA Median : NA Median : NA
## Mean :NaN Mean :NaN Mean :NaN Mean :NaN
## 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA 3rd Qu.: NA
## Max. : NA Max. : NA Max. : NA Max. : NAlibrary(GEOquery)## Loading required package: Biobase## Warning: package 'Biobase' was built under R version 4.5.2## Loading required package: BiocGenerics## Warning: package 'BiocGenerics' was built under R version 4.5.2## Loading required package: generics##
## Attaching package: 'generics'## The following objects are masked from 'package:base':
##
## as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,
## setequal, union##
## Attaching package: 'BiocGenerics'## The following objects are masked from 'package:stats':
##
## IQR, mad, sd, var, xtabs## The following objects are masked from 'package:base':
##
## anyDuplicated, aperm, append, as.data.frame, basename, cbind,
## colnames, dirname, do.call, duplicated, eval, evalq, Filter, Find,
## get, grep, grepl, is.unsorted, lapply, Map, mapply, match, mget,
## order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
## rbind, Reduce, rownames, sapply, saveRDS, table, tapply, unique,
## unsplit, which.max, which.min## Welcome to Bioconductor
##
## Vignettes contain introductory material; view with
## 'browseVignettes()'. To cite Bioconductor, see
## 'citation("Biobase")', and for packages 'citation("pkgname")'.## Setting options('download.file.method.GEOquery'='auto')## Setting options('GEOquery.inmemory.gpl'=FALSE)library(pheatmap)
expr <- read.table("GSE63061_series_matrix.txt",
header = TRUE,
sep = "\t",
comment.char = "!",
check.names = FALSE,
stringsAsFactors = FALSE)
rownames(expr) <- expr[,1]
expr <- expr[,-1]
expr <- as.matrix(expr)
mode(expr) <- "numeric"
expr <- na.omit(expr)
dim(expr)## [1] 32049 388expr[1:5, 1:5]## GSM1539409 GSM1539410 GSM1539411 GSM1539412 GSM1539413
## ILMN_1343291 12.552807 12.711459 13.088393 12.643831 13.098389
## ILMN_1343295 10.101556 9.776015 9.594397 10.126782 10.223301
## ILMN_1651209 6.084671 6.255012 6.160485 6.109219 6.069960
## ILMN_1651210 6.068805 6.016468 6.024322 6.016118 6.056163
## ILMN_1651221 6.121060 6.173167 6.039552 6.111306 6.089542gset <- getGEO("GSE63061", GSEMatrix = TRUE)## Found 1 file(s)## GSE63061_series_matrix.txt.gzlength(gset)## [1] 1gset <- gset[[1]]
pheno <- pData(gset)
dim(pheno)## [1] 388 40colnames(pheno)## [1] "title" "geo_accession"
## [3] "status" "submission_date"
## [5] "last_update_date" "type"
## [7] "channel_count" "source_name_ch1"
## [9] "organism_ch1" "characteristics_ch1"
## [11] "characteristics_ch1.1" "characteristics_ch1.2"
## [13] "characteristics_ch1.3" "characteristics_ch1.4"
## [15] "characteristics_ch1.5" "molecule_ch1"
## [17] "extract_protocol_ch1" "label_ch1"
## [19] "label_protocol_ch1" "taxid_ch1"
## [21] "hyb_protocol" "scan_protocol"
## [23] "description" "data_processing"
## [25] "platform_id" "contact_name"
## [27] "contact_email" "contact_institute"
## [29] "contact_address" "contact_city"
## [31] "contact_zip/postal_code" "contact_country"
## [33] "supplementary_file" "data_row_count"
## [35] "age:ch1" "ethnicity:ch1"
## [37] "gender:ch1" "included in case -control study:ch1"
## [39] "status:ch1" "tissue:ch1"head(pheno[, 1:10])## title geo_accession status submission_date
## GSM1539409 7196843065_F GSM1539409 Public on Aug 05 2015 Nov 06 2014
## GSM1539410 7196843076_G GSM1539410 Public on Aug 05 2015 Nov 06 2014
## GSM1539411 7196843068_B GSM1539411 Public on Aug 05 2015 Nov 06 2014
## GSM1539412 7196843063_B GSM1539412 Public on Aug 05 2015 Nov 06 2014
## GSM1539413 7196843065_L GSM1539413 Public on Aug 05 2015 Nov 06 2014
## GSM1539414 7196843066_H GSM1539414 Public on Aug 05 2015 Nov 06 2014
## last_update_date type channel_count source_name_ch1 organism_ch1
## GSM1539409 May 30 2024 RNA 1 Blood Homo sapiens
## GSM1539410 May 30 2024 RNA 1 Blood Homo sapiens
## GSM1539411 May 30 2024 RNA 1 Blood Homo sapiens
## GSM1539412 May 30 2024 RNA 1 Blood Homo sapiens
## GSM1539413 May 30 2024 RNA 1 Blood Homo sapiens
## GSM1539414 May 30 2024 RNA 1 Blood Homo sapiens
## characteristics_ch1
## GSM1539409 status: MCI
## GSM1539410 status: MCI
## GSM1539411 status: MCI
## GSM1539412 status: MCI
## GSM1539413 status: MCI
## GSM1539414 status: MCIData Integration
Matched expression data with metadata using geo_accession Extracted disease status (group) from characteristics_ch1，Key finding: CTL (control)，AD (Alzheimer’s Disease), MCI (mild cognitive impairment) and others, and I selcted the groups CTL: 134 AD: 139
grep("characteristics|group|diagnosis|disease|source|title", colnames(pheno), value = TRUE)## [1] "title" "source_name_ch1" "characteristics_ch1"
## [4] "characteristics_ch1.1" "characteristics_ch1.2" "characteristics_ch1.3"
## [7] "characteristics_ch1.4" "characteristics_ch1.5"candidate_cols <- grep("characteristics|group|diagnosis|disease|source|title",
colnames(pheno), value = TRUE)
for (cc in candidate_cols) {
cat("\n====================\n")
cat("Column:", cc, "\n")
print(head(pheno[[cc]], 10))
}##
## ====================
## Column: title
## [1] "7196843065_F" "7196843076_G" "7196843068_B" "7196843063_B" "7196843065_L"
## [6] "7196843066_H" "7943280031_C" "7943280031_J" "7196843035_B" "7196843053_L"
##
## ====================
## Column: source_name_ch1
## [1] "Blood" "Blood" "Blood" "Blood" "Blood" "Blood" "Blood" "Blood" "Blood"
## [10] "Blood"
##
## ====================
## Column: characteristics_ch1
## [1] "status: MCI" "status: MCI" "status: MCI" "status: MCI" "status: MCI"
## [6] "status: MCI" "status: MCI" "status: MCI" "status: MCI" "status: MCI"
##
## ====================
## Column: characteristics_ch1.1
## [1] "ethnicity: Western European"
## [2] "ethnicity: Western European"
## [3] "ethnicity: Western European"
## [4] "ethnicity: Western European"
## [5] "ethnicity: Other Caucasian"
## [6] "ethnicity: Other Caucasian"
## [7] "ethnicity: Western European"
## [8] "ethnicity: Any_Other_White_Background"
## [9] "ethnicity: Western European"
## [10] "ethnicity: Western European"
##
## ====================
## Column: characteristics_ch1.2
## [1] "age: 57" "age: 59" "age: 63" "age: 65" "age: 66" "age: 68" "age: 68"
## [8] "age: 68" "age: 69" "age: 69"
##
## ====================
## Column: characteristics_ch1.3
## [1] "gender: Female" "gender: Female" "gender: Female" "gender: Female"
## [5] "gender: Female" "gender: Female" "gender: Female" "gender: Female"
## [9] "gender: Female" "gender: Female"
##
## ====================
## Column: characteristics_ch1.4
## [1] "included in case -control study: yes"
## [2] "included in case -control study: yes"
## [3] "included in case -control study: yes"
## [4] "included in case -control study: yes"
## [5] "included in case -control study: yes"
## [6] "included in case -control study: yes"
## [7] "included in case -control study: yes"
## [8] "included in case -control study: yes"
## [9] "included in case -control study: yes"
## [10] "included in case -control study: yes"
##
## ====================
## Column: characteristics_ch1.5
## [1] "tissue: blood" "tissue: blood" "tissue: blood" "tissue: blood"
## [5] "tissue: blood" "tissue: blood" "tissue: blood" "tissue: blood"
## [9] "tissue: blood" "tissue: blood"head(colnames(expr))## [1] "GSM1539409" "GSM1539410" "GSM1539411" "GSM1539412" "GSM1539413"
## [6] "GSM1539414"head(rownames(pheno))## [1] "GSM1539409" "GSM1539410" "GSM1539411" "GSM1539412" "GSM1539413"
## [6] "GSM1539414"head(pheno$geo_accession)## [1] "GSM1539409" "GSM1539410" "GSM1539411" "GSM1539412" "GSM1539413"
## [6] "GSM1539414"pheno2 <- pheno[match(colnames(expr), pheno$geo_accession), ]
all(pheno2$geo_accession == colnames(expr))## [1] TRUEchar_cols <- grep("^characteristics_ch1", colnames(pheno2), value = TRUE)
char_cols## [1] "characteristics_ch1" "characteristics_ch1.1" "characteristics_ch1.2"
## [4] "characteristics_ch1.3" "characteristics_ch1.4" "characteristics_ch1.5"for (cc in char_cols) {
cat("\n====================\n")
cat("Column:", cc, "\n")
print(unique(pheno2[[cc]])[1:20])
}##
## ====================
## Column: characteristics_ch1
## [1] "status: MCI" "status: CTL" "status: AD"
## [4] "status: borderline MCI" "status: OTHER" "status: CTL to AD"
## [7] "status: MCI to CTL" NA NA
## [10] NA NA NA
## [13] NA NA NA
## [16] NA NA NA
## [19] NA NA
##
## ====================
## Column: characteristics_ch1.1
## [1] "ethnicity: Western European"
## [2] "ethnicity: Other Caucasian"
## [3] "ethnicity: Any_Other_White_Background"
## [4] "ethnicity: Caribbean"
## [5] "ethnicity: Irish"
## [6] "ethnicity: British"
## [7] "ethnicity: Indian"
## [8] "ethnicity: British_English"
## [9] "ethnicity: British English"
## [10] "ethnicity: British_Welsh"
## [11] "ethnicity: Any_Other_Asian_Background"
## [12] "ethnicity: White_And_Asian"
## [13] "ethnicity: British_Scottish"
## [14] "ethnicity: British_Other_Background"
## [15] "ethnicity: Any_Other_Ethnic_Background"
## [16] "ethnicity: Asian"
## [17] "ethnicity: Any_Other_Black_Background"
## [18] "ethnicity: unkown but she's white and speaks english with a slight south african accent"
## [19] NA
## [20] NA
##
## ====================
## Column: characteristics_ch1.2
## [1] "age: 57" "age: 59" "age: 63" "age: 65" "age: 66" "age: 68" "age: 69"
## [8] "age: 70" "age: 71" "age: 73" "age: 74" "age: 75" "age: 64" "age: 67"
## [15] "age: 72" "age: 60" "age: 61" "age: 62" "age: 85" "age: 81"
##
## ====================
## Column: characteristics_ch1.3
## [1] "gender: Female" "gender: Male" NA NA
## [5] NA NA NA NA
## [9] NA NA NA NA
## [13] NA NA NA NA
## [17] NA NA NA NA
##
## ====================
## Column: characteristics_ch1.4
## [1] "included in case -control study: yes"
## [2] "included in case -control study: no"
## [3] NA
## [4] NA
## [5] NA
## [6] NA
## [7] NA
## [8] NA
## [9] NA
## [10] NA
## [11] NA
## [12] NA
## [13] NA
## [14] NA
## [15] NA
## [16] NA
## [17] NA
## [18] NA
## [19] NA
## [20] NA
##
## ====================
## Column: characteristics_ch1.5
## [1] "tissue: blood" NA NA NA
## [5] NA NA NA NA
## [9] NA NA NA NA
## [13] NA NA NA NA
## [17] NA NA NA NAgroup_raw <- pheno2$characteristics_ch1
table(group_raw, useNA = "ifany")## group_raw
## status: AD status: borderline MCI status: CTL
## 139 3 134
## status: CTL to AD status: MCI status: MCI to CTL
## 1 109 1
## status: OTHER
## 1group <- sub("status: ", "", group_raw)
group <- trimws(group)
table(group, useNA = "ifany")## group
## AD borderline MCI CTL CTL to AD MCI
## 139 3 134 1 109
## MCI to CTL OTHER
## 1 1keep <- group %in% c("AD", "CTL")
expr_sub <- expr[, keep]
group_sub <- group[keep]
pheno_sub <- pheno2[keep, ]
table(group_sub)## group_sub
## AD CTL
## 139 134dim(expr_sub)## [1] 32049 273group_sub <- factor(group_sub, levels = c("CTL", "AD"))
table(group_sub)## group_sub
## CTL AD
## 134 139Boxplot — Expression Distribution
Data is well normalized, with no major batch effects or systematic bias.CTL and AD samples have very similar distributions
cols <- c("steelblue", "tomato")[group_sub]
boxplot(expr_sub,
outline = FALSE,
las = 2,
col = cols,
main = "Expression Distribution: CTL vs AD")
legend("topright",
legend = levels(group_sub),
fill = c("steelblue", "tomato"))
PCA — Sample Structure
AD and CTL samples show weak global separation, suggesting that disease-related signals exist but are subtle and not dominant at the global transcriptome level.
pca <- prcomp(t(expr_sub), scale. = TRUE)
plot(pca$x[,1], pca$x[,2],
col = c("steelblue", "tomato")[group_sub],
pch = 19,
xlab = paste0("PC1: ", round(summary(pca)$importance[2,1] * 100, 2), "%"),
ylab = paste0("PC2: ", round(summary(pca)$importance[2,2] * 100, 2), "%"),
main = "PCA: CTL vs AD")
legend("topright",
legend = levels(group_sub),
col = c("steelblue", "tomato"),
pch = 19)
# Hierarchical Clustering ## There is no clear hierarchical separation
between AD and CTL samples, indicating high heterogeneity within
groups.
dist_mat <- dist(t(expr_sub))
hc <- hclust(dist_mat)
plot(hc, labels = FALSE, main = "Sample Clustering: CTL vs AD")
rect.hclust(hc, k = 2, border = "red")
# Heatmap (Top 500 variable genes) ## While certain gene clusters show
distinct expression patterns, overall separation between AD and CTL is
not strong, suggesting complex disease biology.
library(pheatmap)
var_genes <- apply(expr_sub, 1, var)
top_genes <- names(sort(var_genes, decreasing = TRUE))[1:500]
annotation_col <- data.frame(Group = group_sub)
rownames(annotation_col) <- colnames(expr_sub)
pheatmap(expr_sub[top_genes, ],
scale = "row",
show_colnames = FALSE,
annotation_col = annotation_col,
clustering_method = "complete",
main = "Top 500 Variable Genes")
Differential Expression Analysis (limma)
A large number of genes are significantly differentially expressed between AD and CTL samples, despite the weak global separation observed in PCA.
library(limma)## Warning: package 'limma' was built under R version 4.5.2##
## Attaching package: 'limma'## The following object is masked from 'package:BiocGenerics':
##
## plotMAdesign <- model.matrix(~ group_sub)
colnames(design) <- c("Intercept", "AD_vs_CTL")
design## Intercept AD_vs_CTL
## 1 1 0
## 2 1 0
## 3 1 0
## 4 1 0
## 5 1 0
## 6 1 0
## 7 1 0
## 8 1 0
## 9 1 0
## 10 1 0
## 11 1 0
## 12 1 0
## 13 1 0
## 14 1 0
## 15 1 0
## 16 1 0
## 17 1 0
## 18 1 0
## 19 1 0
## 20 1 0
## 21 1 0
## 22 1 0
## 23 1 0
## 24 1 0
## 25 1 0
## 26 1 0
## 27 1 0
## 28 1 0
## 29 1 0
## 30 1 0
## 31 1 0
## 32 1 0
## 33 1 0
## 34 1 0
## 35 1 0
## 36 1 0
## 37 1 0
## 38 1 0
## 39 1 0
## 40 1 0
## 41 1 0
## 42 1 0
## 43 1 0
## 44 1 0
## 45 1 0
## 46 1 0
## 47 1 0
## 48 1 0
## 49 1 0
## 50 1 0
## 51 1 0
## 52 1 0
## 53 1 0
## 54 1 0
## 55 1 0
## 56 1 0
## 57 1 0
## 58 1 0
## 59 1 0
## 60 1 0
## 61 1 0
## 62 1 0
## 63 1 0
## 64 1 0
## 65 1 0
## 66 1 0
## 67 1 0
## 68 1 0
## 69 1 0
## 70 1 0
## 71 1 0
## 72 1 0
## 73 1 1
## 74 1 1
## 75 1 1
## 76 1 1
## 77 1 1
## 78 1 1
## 79 1 1
## 80 1 1
## 81 1 1
## 82 1 1
## 83 1 1
## 84 1 1
## 85 1 1
## 86 1 1
## 87 1 1
## 88 1 1
## 89 1 1
## 90 1 1
## 91 1 1
## 92 1 1
## 93 1 1
## 94 1 1
## 95 1 1
## 96 1 1
## 97 1 1
## 98 1 1
## 99 1 1
## 100 1 1
## 101 1 1
## 102 1 1
## 103 1 1
## 104 1 1
## 105 1 1
## 106 1 1
## 107 1 1
## 108 1 1
## 109 1 1
## 110 1 1
## 111 1 1
## 112 1 1
## 113 1 0
## 114 1 0
## 115 1 1
## 116 1 0
## 117 1 1
## 118 1 1
## 119 1 1
## 120 1 0
## 121 1 1
## 122 1 1
## 123 1 0
## 124 1 1
## 125 1 1
## 126 1 1
## 127 1 0
## 128 1 1
## 129 1 0
## 130 1 1
## 131 1 1
## 132 1 1
## 133 1 0
## 134 1 1
## 135 1 1
## 136 1 0
## 137 1 1
## 138 1 1
## 139 1 0
## 140 1 0
## 141 1 0
## 142 1 1
## 143 1 0
## 144 1 0
## 145 1 0
## 146 1 1
## 147 1 0
## 148 1 1
## 149 1 0
## 150 1 1
## 151 1 0
## 152 1 1
## 153 1 0
## 154 1 1
## 155 1 0
## 156 1 1
## 157 1 1
## 158 1 1
## 159 1 1
## 160 1 1
## 161 1 1
## 162 1 1
## 163 1 1
## 164 1 1
## 165 1 1
## 166 1 1
## 167 1 1
## 168 1 1
## 169 1 1
## 170 1 1
## 171 1 0
## 172 1 1
## 173 1 0
## 174 1 0
## 175 1 0
## 176 1 0
## 177 1 1
## 178 1 1
## 179 1 1
## 180 1 1
## 181 1 0
## 182 1 1
## 183 1 1
## 184 1 0
## 185 1 0
## 186 1 0
## 187 1 1
## 188 1 1
## 189 1 1
## 190 1 1
## 191 1 0
## 192 1 1
## 193 1 0
## 194 1 0
## 195 1 1
## 196 1 1
## 197 1 1
## 198 1 1
## 199 1 1
## 200 1 0
## 201 1 0
## 202 1 1
## 203 1 1
## 204 1 0
## 205 1 1
## 206 1 0
## 207 1 1
## 208 1 0
## 209 1 1
## 210 1 0
## 211 1 0
## 212 1 0
## 213 1 0
## 214 1 0
## 215 1 0
## 216 1 1
## 217 1 0
## 218 1 0
## 219 1 0
## 220 1 1
## 221 1 1
## 222 1 1
## 223 1 1
## 224 1 1
## 225 1 1
## 226 1 1
## 227 1 1
## 228 1 1
## 229 1 1
## 230 1 0
## 231 1 1
## 232 1 1
## 233 1 1
## 234 1 1
## 235 1 0
## 236 1 1
## 237 1 0
## 238 1 1
## 239 1 1
## 240 1 0
## 241 1 1
## 242 1 1
## 243 1 1
## 244 1 1
## 245 1 1
## 246 1 1
## 247 1 0
## 248 1 0
## 249 1 0
## 250 1 0
## 251 1 0
## 252 1 1
## 253 1 0
## 254 1 1
## 255 1 1
## 256 1 1
## 257 1 1
## 258 1 1
## 259 1 0
## 260 1 1
## 261 1 0
## 262 1 1
## 263 1 1
## 264 1 0
## 265 1 1
## 266 1 0
## 267 1 1
## 268 1 1
## 269 1 1
## 270 1 1
## 271 1 1
## 272 1 0
## 273 1 0
## attr(,"assign")
## [1] 0 1
## attr(,"contrasts")
## attr(,"contrasts")$group_sub
## [1] "contr.treatment"fit <- lmFit(expr_sub, design)
fit <- eBayes(fit)
deg <- topTable(fit,
coef = "AD_vs_CTL",
number = Inf,
adjust.method = "BH")
head(deg)## logFC AveExpr t P.Value adj.P.Val B
## ILMN_2189936 -0.4466342 10.408005 -9.435752 1.795640e-18 5.754846e-14 31.18884
## ILMN_2189933 -0.4533286 9.692502 -8.645821 4.653621e-16 5.267952e-12 25.71159
## ILMN_1792528 -0.4550236 12.015340 -8.637390 4.931154e-16 5.267952e-12 25.65455
## ILMN_1784286 -0.4976969 8.390367 -8.457838 1.680800e-15 1.346699e-11 24.44740
## ILMN_1746516 -0.4569375 11.722748 -8.358204 3.298724e-15 2.114416e-11 23.78391
## ILMN_1776104 -0.4219056 7.686509 -8.107747 1.760727e-14 9.404925e-11 22.13674Volcano Plot
Most differentially expressed genes show modest fold changes but high statistical significance, indicating subtle but consistent transcriptional differences between AD and CTL.
plot(deg$logFC, -log10(deg$P.Value),
pch = 20,
main = "Volcano Plot: AD vs CTL",
xlab = "logFC",
ylab = "-log10(P.Value)")
sig <- deg$adj.P.Val < 0.05 & abs(deg$logFC) > 1
points(deg$logFC[sig], -log10(deg$P.Value[sig]), pch = 20, col = "red")
abline(v = c(-1, 1), col = "blue", lty = 2)
abline(h = -log10(0.05), col = "blue", lty = 2)
The exploratory data analysis indicates that the dataset is well normalized and suitable for downstream analysis. Although AD and control samples do not show strong global separation in PCA, we observe significant gene-level differences through differential expression analysis.Importantly, we do not observe a small number of highly dominant genes. Instead, many genes exhibit modest but statistically significant changes. This suggests that Alzheimer’s disease is driven by coordinated, system-level transcriptional changes rather than a single key biomarker. Therefore, this dataset is particularly suitable for identifying potential biomarkers and, more importantly, for pathway-level analysis to better understand disease mechanisms.