This page was generated on 2018-04-12 13:09:17 -0400 (Thu, 12 Apr 2018).
MLP 1.26.0 Tobias Verbeke
 
| Snapshot Date: 2018-04-11 16:45:18 -0400 (Wed, 11 Apr 2018) |  
| URL: https://git.bioconductor.org/packages/MLP |  
| Branch: RELEASE_3_6 |  
| Last Commit: fe34cce |  
| Last Changed Date: 2017-10-30 12:39:31 -0400 (Mon, 30 Oct 2017) |  
 
 | malbec1  | Linux (Ubuntu 16.04.1 LTS) / x86_64  |  OK  |  OK  | [ OK ] |  |   | 
| tokay1  | Windows Server 2012 R2 Standard / x64  |  OK  |  OK  |  OK  |  OK  |   | 
| veracruz1  | OS X 10.11.6 El Capitan / x86_64  |  OK  |  OK  |  OK  |  OK  |   | 
R version 3.4.4 (2018-03-15) -- "Someone to Lean On"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> require(MLP)	
Loading required package: MLP
Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
    IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':
    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colMeans, colSums, colnames, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
    pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
    setdiff, sort, table, tapply, union, unique, unsplit, which,
    which.max, which.min
Loading required package: Biobase
Welcome to Bioconductor
    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.
Loading required package: IRanges
Loading required package: S4Vectors
Attaching package: 'S4Vectors'
The following object is masked from 'package:base':
    expand.grid
Loading required package: affy
Loading required package: plotrix
Loading required package: gplots
Attaching package: 'gplots'
The following object is masked from 'package:plotrix':
    plotCI
The following object is masked from 'package:IRanges':
    space
The following object is masked from 'package:S4Vectors':
    space
The following object is masked from 'package:stats':
    lowess
Loading required package: gmodels
Loading required package: gdata
gdata: read.xls support for 'XLS' (Excel 97-2004) files ENABLED.
gdata: read.xls support for 'XLSX' (Excel 2007+) files ENABLED.
Attaching package: 'gdata'
The following object is masked from 'package:IRanges':
    trim
The following objects are masked from 'package:S4Vectors':
    first, first<-
The following object is masked from 'package:Biobase':
    combine
The following object is masked from 'package:BiocGenerics':
    combine
The following object is masked from 'package:stats4':
    nobs
The following object is masked from 'package:stats':
    nobs
The following object is masked from 'package:utils':
    object.size
The following object is masked from 'package:base':
    startsWith
Loading required package: gtools
> set.seed(479)
> 
> # This is just the expressionset for this experiment.
> 
> pathExampleData <- system.file("exampleFiles", "expressionSetGcrma.rda", package = "MLP")
> load(pathExampleData)
> 
> # Libraries needed
> library(limma)
Attaching package: 'limma'
The following object is masked from 'package:BiocGenerics':
    plotMA
> library(org.Mm.eg.db) # for mouse
> 
> exprs(expressionSetGcrma)[1:2,]
              2760     2763     2765     2766     2768     2769     2761
100009600 2.371111 2.170060 2.233383 2.180717 2.325886 2.239441 2.297301
100012    2.176163 2.318876 2.419263 2.223307 2.585125 2.346060 2.292061
              2762    2764     2767     2770     2771
100009600 2.409001 2.49458 2.115814 2.371262 2.267459
100012    2.336415 2.47979 2.361981 2.330418 2.520918
> #              2760     2763     2765     2766     2768     2769     2761     2762    2764     2767
> #100009600 2.371111 2.170060 2.233383 2.180717 2.325886 2.239441 2.297301 2.409001 2.49458 2.115814
> #100012    2.176163 2.318876 2.419263 2.223307 2.585125 2.346060 2.292061 2.336415 2.47979 2.361981
> #              2770     2771
> #100009600 2.371262 2.267459
> #100012    2.330418 2.520918
> 
> pData(expressionSetGcrma)
     sample subGroup sampleColor subGroup1
2760      1        1     #FF0000        WT
2763      4        1     #FF0000        WT
2765      6        1     #FF0000        WT
2766      7        1     #FF0000        WT
2768      9        1     #FF0000        WT
2769     10        1     #FF0000        WT
2761      2        2     #0000FF        KO
2762      3        2     #0000FF        KO
2764      5        2     #0000FF        KO
2767      8        2     #0000FF        KO
2770     11        2     #0000FF        KO
2771     12        2     #0000FF        KO
> #     sample subGroup sampleColor
> #2760      1        1     #FF0000
> #2763      4        1     #FF0000
> #2765      6        1     #FF0000
> #2766      7        1     #FF0000
> #2768      9        1     #FF0000
> #2769     10        1     #FF0000
> #2761      2        2     #0000FF
> #2762      3        2     #0000FF
> #2764      5        2     #0000FF
> #2767      8        2     #0000FF
> #2770     11        2     #0000FF
> #2771     12        2     #0000FF
> 
> pData(expressionSetGcrma)$subGroup1 <- ifelse(pData(expressionSetGcrma)$subGroup==1,"WT","KO")
> 
> ###==============================================GENERATING LIMMA p-VALUES=================================
> 
> # boxplot(data.frame(exprs(expressionSetGcrma))
> normDat  <- normalizeQuantiles(exprs(expressionSetGcrma), ties=TRUE)
> subGroup <- pData(expressionSetGcrma)$subGroup
> design <- model.matrix(˜ -1 +factor(subGroup ))
> 
> colnames(design) <- c("group1", "group2")
> contrast.matrix <- makeContrasts(group1-group2, levels=design)
> fit <- lmFit(normDat,design)
> fit2 <- contrasts.fit(fit, contrast.matrix)
> fit2 <- eBayes(fit2)
> normDat.p <- fit2$p.value
> 
> normDat.p[1:5]
[1] 0.4328583 0.7448996 0.6088859 0.1845008 0.2312761
> #[1] 0.4328583 0.7448996 0.6088859 0.1845008 0.2312761
> 
> system.time(goGeneSet <- getGeneSets(species = "Mouse", geneSetSource = "GOBP", entrezIdentifiers = featureNames(expressionSetGcrma)))
Loading required package: GO.db
   user  system elapsed 
 22.140   0.440  22.594 
> goGeneSet[1:3]
$`GO:0000002`
 [1] "11545"  "16882"  "17258"  "17527"  "18975"  "19017"  "19819"  "22059" 
 [9] "23797"  "27393"  "27395"  "27397"  "50776"  "57813"  "66592"  "70556" 
[17] "72170"  "72962"  "74143"  "74244"  "74528"  "83408"  "83945"  "98496" 
[25] "192287" "208084" "216021" "216805" "226153" "230784" "327762" "382985"
[33] "408022"
$`GO:0000003`
   [1] "11287"     "11352"     "11421"     "11430"     "11434"     "11441"    
   [7] "11477"     "11479"     "11480"     "11486"     "11495"     "11497"    
  [13] "11504"     "11516"     "11517"     "11535"     "11551"     "11552"    
  [19] "11553"     "11576"     "11600"     "11606"     "11614"     "11622"    
  [25] "11625"     "11647"     "11651"     "11705"     "11757"     "11789"    
  [31] "11797"     "11804"     "11819"     "11820"     "11835"     "11839"    
  [37] "11857"     "11863"     "11865"     "11883"     "11920"     "11998"    
  [43] "12009"     "12018"     "12028"     "12034"     "12043"     "12048"    
  [49] "12050"     "12053"     "12124"     "12125"     "12142"     "12155"    
  [55] "12159"     "12160"     "12161"     "12162"     "12163"     "12164"    
  [61] "12166"     "12167"     "12168"     "12173"     "12190"     "12192"    
  [67] "12211"     "12235"     "12236"     "12237"     "12261"     "12305"    
  [73] "12310"     "12316"     "12317"     "12323"     "12344"     "12363"    
  [79] "12366"     "12380"     "12387"     "12394"     "12411"     "12416"    
  [85] "12426"     "12427"     "12443"     "12447"     "12448"     "12449"    
  [91] "12458"     "12461"     "12462"     "12464"     "12465"     "12466"    
  [97] "12468"     "12469"     "12505"     "12527"     "12531"     "12534"    
 [103] "12550"     "12566"     "12576"     "12577"     "12589"     "12591"    
 [109] "12592"     "12606"     "12608"     "12617"     "12638"     "12640"    
 [115] "12659"     "12702"     "12704"     "12705"     "12745"     "12753"    
 [121] "12767"     "12801"     "12804"     "12841"     "12846"     "12877"    
 [127] "12916"     "12918"     "12919"     "12946"     "12977"     "12981"    
 [133] "13006"     "13030"     "13039"     "13046"     "13052"     "13070"    
 [139] "13075"     "13123"     "13134"     "13164"     "13166"     "13206"    
 [145] "13363"     "13382"     "13383"     "13393"     "13404"     "13435"    
 [151] "13487"     "13488"     "13491"     "13492"     "13498"     "13524"    
 [157] "13525"     "13526"     "13529"     "13615"     "13617"     "13618"    
 [163] "13649"     "13653"     "13667"     "13731"     "13813"     "13819"    
 [169] "13852"     "13854"     "13856"     "13857"     "13866"     "13870"    
 [175] "13874"     "13875"     "13982"     "13983"     "13984"     "14008"    
 [181] "14011"     "14087"     "14088"     "14155"     "14160"     "14165"    
 [187] "14178"     "14179"     "14180"     "14183"     "14211"     "14228"    
 [193] "14238"     "14283"     "14308"     "14309"     "14313"     "14366"    
 [199] "14367"     "14388"     "14421"     "14431"     "14460"     "14461"    
 [205] "14462"     "14463"     "14531"     "14536"     "14566"     "14595"    
 [211] "14598"     "14610"     "14620"     "14622"     "14632"     "14633"    
 [217] "14654"     "14658"     "14682"     "14714"     "14725"     "14748"    
 [223] "14764"     "14766"     "14782"     "14784"     "14810"     "14815"    
 [229] "14824"     "15013"     "15018"     "15078"     "15081"     "15110"    
 [235] "15194"     "15204"     "15205"     "15211"     "15212"     "15213"    
 [241] "15214"     "15221"     "15235"     "15251"     "15270"     "15361"    
 [247] "15364"     "15373"     "15375"     "15377"     "15378"     "15387"    
 [253] "15395"     "15396"     "15398"     "15405"     "15408"     "15423"    
 [259] "15430"     "15431"     "15433"     "15438"     "15446"     "15463"    
 [265] "15482"     "15484"     "15486"     "15487"     "15488"     "15499"    
 [271] "15500"     "15502"     "15511"     "15512"     "15516"     "15567"    
 [277] "15570"     "15574"     "15894"     "15904"     "16000"     "16001"    
 [283] "16002"     "16007"     "16011"     "16147"     "16153"     "16157"    
 [289] "16173"     "16175"     "16176"     "16322"     "16323"     "16324"    
 [295] "16330"     "16336"     "16337"     "16365"     "16401"     "16410"    
 [301] "16412"     "16433"     "16450"     "16477"     "16532"     "16542"    
 [307] "16590"     "16601"     "16650"     "16669"     "16691"     "16777"    
 [313] "16783"     "16842"     "16846"     "16847"     "16848"     "16859"    
 [319] "16866"     "16867"     "16869"     "16871"     "16872"     "16875"    
 [325] "16876"     "16878"     "16886"     "16970"     "16974"     "17125"    
 [331] "17128"     "17129"     "17149"     "17171"     "17173"     "17191"    
 [337] "17221"     "17235"     "17240"     "17256"     "17283"     "17289"    
 [343] "17295"     "17300"     "17304"     "17311"     "17319"     "17345"    
 [349] "17350"     "17381"     "17390"     "17395"     "17427"     "17450"    
 [355] "17451"     "17535"     "17684"     "17685"     "17687"     "17701"    
 [361] "17702"     "17761"     "17771"     "17776"     "17836"     "17864"    
 [367] "17886"     "17977"     "17978"     "17979"     "17986"     "18000"    
 [373] "18004"     "18005"     "18011"     "18014"     "18022"     "18072"    
 [379] "18095"     "18119"     "18121"     "18127"     "18128"     "18129"    
 [385] "18142"     "18159"     "18168"     "18194"     "18211"     "18285"    
 [391] "18286"     "18291"     "18292"     "18387"     "18413"     "18417"    
 [397] "18426"     "18429"     "18430"     "18431"     "18436"     "18441"    
 [403] "18442"     "18472"     "18475"     "18476"     "18504"     "18507"    
 [409] "18514"     "18551"     "18552"     "18555"     "18591"     "18595"    
 [415] "18617"     "18667"     "18747"     "18749"     "18763"     "18764"    
 [421] "18766"     "18783"     "18787"     "18791"     "18792"     "18793"    
 [427] "18795"     "18799"     "18802"     "18815"     "18817"     "18861"    
 [433] "18952"     "19014"     "19015"     "19016"     "19049"     "19052"    
 [439] "19059"     "19090"     "19109"     "19116"     "19118"     "19119"    
 [445] "19120"     "19143"     "19156"     "19183"     "19204"     "19211"    
 [451] "19214"     "19215"     "19219"     "19223"     "19225"     "19229"    
 [457] "19247"     "19275"     "19294"     "19317"     "19355"     "19359"    
 [463] "19360"     "19361"     "19363"     "19364"     "19401"     "19411"    
 [469] "19662"     "19664"     "19701"     "19725"     "19733"     "19735"    
 [475] "19773"     "19821"     "19886"     "20017"     "20104"     "20112"    
 [481] "20181"     "20182"     "20315"     "20317"     "20319"     "20346"    
 [487] "20363"     "20377"     "20397"     "20415"     "20423"     "20437"    
 [493] "20474"     "20475"     "20520"     "20541"     "20613"     "20655"    
 [499] "20662"     "20671"     "20674"     "20675"     "20681"     "20682"    
 [505] "20683"     "20686"     "20687"     "20690"     "20708"     "20719"    
 [511] "20720"     "20724"     "20729"     "20730"     "20732"     "20733"    
 [517] "20744"     "20758"     "20779"     "20826"     "20843"     "20848"    
 [523] "20850"     "20851"     "20860"     "20869"     "20871"     "20873"    
 [529] "20878"     "20892"     "20897"     "20899"     "20905"     "20910"    
 [535] "20957"     "20962"     "20997"     "21336"     "21357"     "21386"    
 [541] "21405"     "21410"     "21412"     "21414"     "21416"     "21425"    
 [547] "21454"     "21463"     "21674"     "21679"     "21744"     "21749"    
 [553] "21803"     "21808"     "21812"     "21821"     "21823"     "21824"    
 [559] "21830"     "21833"     "21834"     "21843"     "21849"     "21857"    
 [565] "21869"     "21887"     "21923"     "21945"     "21958"     "21959"    
 [571] "21973"     "21974"     "22022"     "22026"     "22061"     "22064"    
 [577] "22065"     "22068"     "22092"     "22113"     "22114"     "22115"    
 [583] "22127"     "22137"     "22174"     "22187"     "22209"     "22210"    
 [589] "22215"     "22329"     "22337"     "22339"     "22353"     "22371"    
 [595] "22384"     "22412"     "22413"     "22415"     "22417"     "22418"    
 [601] "22421"     "22422"     "22431"     "22441"     "22445"     "22446"    
 [607] "22526"     "22589"     "22632"     "22635"     "22661"     "22668"    
 [613] "22691"     "22694"     "22696"     "22697"     "22698"     "22701"    
 [619] "22702"     "22762"     "22764"     "22786"     "22787"     "22788"    
 [625] "22789"     "23793"     "23885"     "23920"     "23950"     "23967"    
 [631] "23968"     "23980"     "23991"     "23997"     "24061"     "24086"    
 [637] "24127"     "24128"     "26357"     "26362"     "26370"     "26380"    
 [643] "26384"     "26395"     "26407"     "26413"     "26416"     "26423"    
 [649] "26434"     "26437"     "26564"     "26909"     "26910"     "26927"    
 [655] "26934"     "26942"     "26946"     "26972"     "27061"     "27083"    
 [661] "27084"     "27206"     "27222"     "27354"     "27356"     "27386"    
 [667] "28036"     "28088"     "28105"     "28114"     "28135"     "29871"    
 [673] "29876"     "30054"     "30841"     "30939"     "30953"     "30959"    
 [679] "50500"     "50501"     "50505"     "50525"     "50722"     "50785"    
 [685] "50790"     "50796"     "50878"     "50915"     "51792"     "51885"    
 [691] "52020"     "52028"     "52679"     "52683"     "52864"     "53381"    
 [697] "53419"     "53422"     "53424"     "53601"     "53604"     "53614"    
 [703] "53814"     "53878"     "53885"     "53897"     "53975"     "54003"    
 [709] "54004"     "54137"     "54140"     "54204"     "54383"     "54388"    
 [715] "54418"     "54427"     "54486"     "54524"     "54562"     "54608"    
 [721] "54611"     "54650"     "54725"     "55925"     "55993"     "55994"    
 [727] "56092"     "56094"     "56096"     "56213"     "56218"     "56220"    
 [733] "56223"     "56228"     "56274"     "56291"     "56312"     "56334"    
 [739] "56371"     "56406"     "56427"     "56436"     "56449"     "56484"    
 [745] "56503"     "56526"     "56693"     "56710"     "56711"     "56717"    
 [751] "56739"     "56746"     "57256"     "57264"     "57320"     "57434"    
 [757] "57746"     "57749"     "57815"     "57816"     "57908"     "58186"    
 [763] "58226"     "58230"     "58231"     "58864"     "58991"     "58998"    
 [769] "59030"     "59083"     "60530"     "60534"     "60597"     "63872"    
 [775] "64009"     "64335"     "64383"     "64707"     "64931"     "65247"    
 [781] "65971"     "66197"     "66313"     "66515"     "66573"     "66634"    
 [787] "66654"     "66707"     "66712"     "66713"     "66720"     "66722"    
 [793] "66923"     "66934"     "66983"     "67010"     "67030"     "67077"    
 [799] "67121"     "67141"     "67181"     "67204"     "67231"     "67320"    
 [805] "67331"     "67345"     "67378"     "67402"     "67504"     "67555"    
 [811] "67561"     "67652"     "67690"     "67713"     "67753"     "67869"    
 [817] "67909"     "67946"     "67968"     "67981"     "68107"     "68166"    
 [823] "68231"     "68275"     "68298"     "68328"     "68549"     "68708"    
 [829] "68767"     "68911"     "69032"     "69064"     "69260"     "69286"    
 [835] "69287"     "69307"     "69310"     "69376"     "69444"     "69538"    
 [841] "69546"     "69707"     "69716"     "69865"     "69928"     "69982"    
 [847] "70069"     "70093"     "70099"     "70235"     "70248"     "70375"    
 [853] "70441"     "70465"     "70503"     "70691"     "70772"     "70840"    
 [859] "70862"     "70873"     "70891"     "70956"     "70977"     "71062"    
 [865] "71099"     "71132"     "71175"     "71241"     "71242"     "71371"    
 [871] "71567"     "71709"     "71711"     "71765"     "71830"     "71836"    
 [877] "71840"     "71846"     "71854"     "71904"     "71914"     "71950"    
 [883] "71981"     "72135"     "72148"     "72236"     "72284"     "72415"    
 [889] "72469"     "72504"     "72508"     "72634"     "72780"     "72787"    
 [895] "72891"     "73242"     "73296"     "73316"     "73329"     "73412"    
 [901] "73456"     "73472"     "73542"     "73673"     "73679"     "73721"    
 [907] "74041"     "74068"     "74075"     "74090"     "74117"     "74174"    
 [913] "74229"     "74237"     "74267"     "74286"     "74288"     "74297"    
 [919] "74309"     "74335"     "74354"     "74360"     "74369"     "74401"    
 [925] "74434"     "74446"     "74450"     "74468"     "74469"     "74691"    
 [931] "74716"     "74754"     "74847"     "74927"     "75019"     "75033"    
 [937] "75140"     "75178"     "75202"     "75388"     "75410"     "75459"    
 [943] "75469"     "75514"     "75533"     "75571"     "75605"     "75622"    
 [949] "75642"     "75753"     "75801"     "75826"     "75828"     "75909"    
 [955] "76378"     "76407"     "76486"     "76499"     "76718"     "76800"    
 [961] "76850"     "76856"     "76858"     "76867"     "76915"     "76925"    
 [967] "76943"     "77053"     "77128"     "77424"     "77595"     "77684"    
 [973] "77963"     "77980"     "78081"     "78124"     "78284"     "78619"    
 [979] "78634"     "78658"     "78709"     "78784"     "78801"     "78803"    
 [985] "78925"     "80297"     "80517"     "80838"     "80884"     "80912"    
 [991] "81018"     "83456"     "83557"     "83558"     "83560"     "83561"    
 [997] "83964"     "83984"     "93684"     "93736"     "93757"     "93759"    
[1003] "93760"     "93837"     "93960"     "94221"     "94224"     "94244"    
[1009] "94246"     "97165"     "98558"     "98711"     "99412"     "99929"    
[1015] "100121"    "100535"    "100986"    "101187"    "101476"    "102774"   
[1021] "103468"    "103554"    "103733"    "104083"    "104111"    "104148"   
[1027] "104156"    "104263"    "104271"    "104310"    "104362"    "104601"   
[1033] "104799"    "104806"    "105349"    "105511"    "105988"    "106389"   
[1039] "106757"    "107515"    "107586"    "107626"    "107656"    "107889"   
[1045] "107970"    "107995"    "108829"    "108961"    "109689"    "109727"   
[1051] "109785"    "110012"    "110147"    "110355"    "110459"    "110542"   
[1057] "110957"    "110958"    "112405"    "114606"    "114642"    "114661"   
[1063] "114662"    "114714"    "114875"    "140498"    "140557"    "170676"   
[1069] "171285"    "171429"    "171506"    "192119"    "192195"    "192199"   
[1075] "192897"    "193838"    "194908"    "195434"    "207165"    "207304"   
[1081] "207352"    "208169"    "208188"    "209091"    "210510"    "210554"   
[1087] "211064"    "211484"    "211651"    "212390"    "212670"    "212937"   
[1093] "213081"    "213236"    "213272"    "213389"    "213742"    "214105"   
[1099] "214253"    "214292"    "214384"    "214572"    "214575"    "214593"   
[1105] "214901"    "215095"    "215387"    "215854"    "216350"    "216725"   
[1111] "216869"    "217039"    "217116"    "217325"    "217715"    "217716"   
[1117] "218214"    "218454"    "218914"    "223593"    "223697"    "223825"   
[1123] "223921"    "223989"    "224045"    "224171"    "224640"    "224661"   
[1129] "224727"    "224826"    "224902"    "225182"    "225865"    "226090"   
[1135] "226162"    "226841"    "227210"    "227394"    "227615"    "227631"   
[1141] "227736"    "228421"    "228980"    "229227"    "229357"    "229700"   
[1147] "230103"    "230126"    "230861"    "230899"    "231051"    "231633"   
[1153] "231672"    "231832"    "231912"    "232174"    "232223"    "232286"   
[1159] "232345"    "232664"    "233276"    "234378"    "234396"    "234857"   
[1165] "235072"    "235320"    "235559"    "235626"    "235628"    "236266"   
[1171] "236899"    "237336"    "237625"    "237911"    "238055"    "238057"   
[1177] "238247"    "238328"    "238330"    "239083"    "239167"    "239731"   
[1183] "240590"    "240697"    "240725"    "240899"    "241624"    "242202"   
[1189] "242523"    "243862"    "243897"    "243905"    "244551"    "245000"   
[1195] "245865"    "246747"    "252828"    "252868"    "252967"    "252973"   
[1201] "259279"    "264134"    "268396"    "268420"    "268465"    "268491"   
[1207] "268591"    "268697"    "268755"    "268860"    "268903"    "269254"   
[1213] "269275"    "269610"    "269682"    "270624"    "271036"    "271127"   
[1219] "271639"    "272643"    "276920"    "277353"    "278240"    "280287"   
[1225] "280667"    "280668"    "317653"    "319177"    "319448"    "319953"   
[1231] "320022"    "320244"    "320277"    "320558"    "320752"    "320790"   
[1237] "327826"    "328019"    "328365"    "328401"    "328440"    "328580"   
[1243] "328845"    "328971"    "329954"    "330149"    "330188"    "330319"   
[1249] "330409"    "330470"    "330830"    "330890"    "331046"    "331416"   
[1255] "378430"    "378462"    "380654"    "380664"    "380684"    "380709"   
[1261] "380773"    "380855"    "380993"    "380994"    "381022"    "381196"   
[1267] "381404"    "381489"    "381677"    "381759"    "382077"    "382217"   
[1273] "382275"    "382277"    "382301"    "383491"    "384619"    "387139"   
[1279] "387140"    "387153"    "387156"    "387161"    "387162"    "387177"   
[1285] "387178"    "387179"    "387188"    "387198"    "387218"    "387244"   
[1291] "387245"    "387246"    "387247"    "408198"    "433178"    "433181"   
[1297] "433700"    "434438"    "434784"    "434794"    "442829"    "545156"   
[1303] "546118"    "546272"    "546282"    "574428"    "574437"    "574438"   
[1309] "619517"    "619697"    "619991"    "622554"    "625249"    "627081"   
[1315] "664799"    "664829"    "665270"    "665780"    "666528"    "666842"   
[1321] "668110"    "668929"    "671232"    "671564"    "723849"    "723868"   
[1327] "723886"    "723932"    "723939"    "723955"    "723956"    "723962"   
[1333] "723965"    "723966"    "735262"    "735309"    "751535"    "100009600"
[1339] "100038417" "100038971" "100038977" "100039030" "100039065" "100039120"
[1345] "100039240" "100039324" "100039377" "100039467" "100039550" "100039585"
[1351] "100039842" "100039905" "100040054" "100040363" "100040483" "100040608"
[1357] "100040867" "100040894" "100041812" "100041897" "100042109" "100042144"
[1363] "100042175" "100042357" "100042709" "100042855" "100043216" "100049545"
[1369] "100049546" "100049548" "100113365" "100124460" "100124479" "100124480"
[1375] "100190765" "100270744" "100504195" "100504642" "100861637" "100861665"
[1381] "100861734" "100861779" "100861839" "100861881" "100862113" "100862125"
[1387] "100862147" "101055632" "101055766" "101055773" "101056109" "101056116"
[1393] "101056194" "101056210" "102631559" "102632183" "102632745" "102632829"
[1399] "102633256" "102633451" "102633564" "102633842" "102634493" "102636418"
[1405] "102636419" "102636501" "102638101" "102638579" "102638610" "102638793"
[1411] "102639094" "102639490" "102639895"
$`GO:0000011`
[1] "78287"
> # output changes with annotation version !
> 
> y <- normDat.p[,1]
> names(y) <- featureNames(expressionSetGcrma)
> 
> y[1:10]
100009600    100012    100017    100019 100034251 100036521 100037258 100037278 
0.4328583 0.7448996 0.6088859 0.1845008 0.2312761 0.7865153 0.7772888 0.1037431 
100038570 100038635 
0.1368744 0.3272610 
> # 100009600    100012    100017    100019 100034251 100036521 100037258 100037278 
> # 0.4328583 0.7448996 0.6088859 0.1845008 0.2312761 0.7865153 0.7772888 0.1037431 
> # 100038570 100038635 
> # 0.1368744 0.3272610 
> 
> mlpObject <- MLP(geneSet = goGeneSet, geneStatistic = y, minGenes = 5, maxGenes = 100, rowPermutations = TRUE, 
+     nPermutations = 6, smoothPValues = TRUE)
> 
> 
> 
> mlpObject[1:10, ]
           totalGeneSetSize testedGeneSetSize geneSetStatistic geneSetPValue
GO:1901264               54                49        0.7860371   0.002286536
GO:0019886               14                14        1.0549211   0.002659958
GO:0060179                9                 8        1.2309410   0.003119398
GO:0002495               19                19        0.9388391   0.003596939
GO:0002478               21                21        0.8986539   0.004198666
GO:0002504               20                20        0.9113723   0.004205216
GO:0019884               26                25        0.8339649   0.006067905
GO:0030238               15                13        0.9359497   0.009844571
GO:0007617               33                28        0.7816689   0.009960218
GO:0010815                6                 6        1.1507789   0.010347308
                                                                                  geneSetDescription
GO:1901264                                                         carbohydrate derivative transport
GO:0019886         antigen processing and presentation of exogenous peptide antigen via MHC class II
GO:0060179                                                                      male mating behavior
GO:0002495                   antigen processing and presentation of peptide antigen via MHC class II
GO:0002478                          antigen processing and presentation of exogenous peptide antigen
GO:0002504 antigen processing and presentation of peptide or polysaccharide antigen via MHC class II
GO:0019884                                  antigen processing and presentation of exogenous antigen
GO:0030238                                                                    male sex determination
GO:0007617                                                                           mating behavior
GO:0010815                                                              bradykinin catabolic process
> # output changes with annotation version !
> 
> plotGOgraph(object = mlpObject, main = "test of main")
Loading required package: Rgraphviz
Loading required package: graph
Loading required package: grid
Attaching package: 'Rgraphviz'
The following objects are masked from 'package:IRanges':
    from, to
The following objects are masked from 'package:S4Vectors':
    from, to
Loading required package: GOstats
Loading required package: Category
Loading required package: Matrix
Attaching package: 'Matrix'
The following object is masked from 'package:S4Vectors':
    expand
Attaching package: 'GOstats'
The following object is masked from 'package:AnnotationDbi':
    makeGOGraph
Loading required package: annotate
Loading required package: XML
Attaching package: 'XML'
The following object is masked from 'package:graph':
    addNode
Attaching package: 'annotate'
The following object is masked from 'package:Rgraphviz':
    toFile
> 
> pdf(file = "test10.pdf", width = 10, height = 10)
> # x11(width = 10, height = 10)
> plot(mlpObject, nRow = 10) # by default:  type = "barplot"
> dev.off()
pdf 
  2 
> 
> unlink("test10.pdf")
> 
> if (FALSE){
+   pdf(file = "test5.pdf", width =10, height = 10)
+   mlpBarplot(object = mlpObject, geneSetSource = "GOBP", nRow = 10, descriptionLength = 5)
+   dev.off()
+   
+   unlink("test5.pdf")
+   
+   pdf(file = "test100.pdf", width =10, height = 20)
+   mlpBarplot(object = mlpObject, geneSetSource = "GOBP", nRow = 10, descriptionLength = 100)
+   dev.off()
+   
+   unlink("test100.pdf")
+ }
> 
> plot(mlpObject, type = "quantileCurves")
> plot(mlpObject, type = "GOgraph")
> 
> proc.time()
   user  system elapsed 
 47.464   0.620  48.518