Question

error message in GoSeq in if (matched_frac == 0)

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Hello, I performed an analysis with EdgeR followed by an analysis with GoSeq and then I got this error message, saying there is an error in if (matched_frac == 0) { :missing value where TRUE/FALSE is required > pwf=nullp(genes,"hg19","ensGene") Loading hg19 length data... Erreur dans if (matched_frac == 0) { : valeur manquante l?? o?? TRUE / FALSE est requis thank you for your help, best regards, anna -- output of sessionInfo(): R version 2.15.2 (2012-10-26) Platform: i386-w64-mingw32/i386 (32-bit) locale: [1] LC_COLLATE=French_France.1252 LC_CTYPE=French_France.1252 [3] LC_MONETARY=French_France.1252 LC_NUMERIC=C [5] LC_TIME=French_France.1252 attached base packages: [1] splines stats graphics grDevices utils datasets methods [8] base other attached packages: [1] goseq_1.10.0 geneLenDataBase_0.99.10 BiasedUrn_1.04 [4] edgeR_3.0.4 limma_3.14.1 loaded via a namespace (and not attached): [1] AnnotationDbi_1.20.3 Biobase_2.18.0 BiocGenerics_0.4.0 [4] biomaRt_2.14.0 Biostrings_2.26.2 bitops_1.0-5 [7] BSgenome_1.26.1 DBI_0.2-5 GenomicFeatures_1.10.1 [10] GenomicRanges_1.10.5 grid_2.15.2 IRanges_1.16.4 [13] lattice_0.20-10 Matrix_1.0-10 mgcv_1.7-22 [16] nlme_3.1-105 parallel_2.15.2 RCurl_1.95-3 [19] Rsamtools_1.10.2 RSQLite_0.11.2 rtracklayer_1.18.1 [22] stats4_2.15.2 tools_2.15.2 XML_3.95-0.1 [25] zlibbioc_1.4.0 -- Sent via the guest posting facility at bioconductor.org.

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ADD COMMENT • link updated 12.0 years ago by fire1976 wyoming ▴ 380 • written 12.0 years ago by Guest User ★ 13k

score 0 · Answer 1 · 2012-11-25

Hi, I am trying some basic logistic regression analysis using glm. I just have one dependent variable (Outcome) which is binary in nature and one independent variable (Weight). I fit a model using a training data set (train) which has 85 observations and try to apply it on an independent dataset (test) which has 55 observations. When I apply the predict function on the fitted model for the new dataset, I get the following warning "Warning message: 'newdata' had 55 rows but variable(s) found have 85 rows" and the predict works on the training observations and not on the test observations. Following is he session info, code and the training and test datasets I am using. What am I doing wrong? Any help would be greatly appreciated. Thanks, S. > train <- read.table("train_data.txt", header=T, row.names=1, sep="\t") > test<- read.table("test_data.txt", header=T, row.names=1, sep="\t") > mylogit <- glm(train$Outcome ~ train$Weight, data=train, family = binomial("logit")) > predictions <- predict(mylogit, newdata = test, type= "response") Warning message: 'newdata' had 55 rows but variable(s) found have 85 rows > sessionInfo() R version 2.15.0 (2012-03-30) Platform: x86_64-pc-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252 [4] LC_NUMERIC=C LC_TIME=English_United States.1252 attached base packages: [1] stats graphics grDevices utils datasets methods base > train Outcome Weight AB256939_21 0 0.331 AB257076_21 0 0.308 AB257079_21 0 0.453 AB415508_21 0 0.303 AB700497_21 0 0.354 AB904508_21 0 0.336 AC048719_21 0 0.420 AC185939_21 0 0.249 AC185940_21 0 1.525 AC445840_21 0 0.261 E7490523_21 0 0.269 E7490524_21 0 0.213 E7659579_21 0 0.360 E7661528_21 0 0.271 E7781094_21 0 0.156 E7781095_21 0 0.221 E7781096_21 0 0.098 E7969081_21 0 0.430 E8117594_21 0 0.321 E8133295_21 0 0.166 E8161578_22 0 0.269 E8483037_21 0 0.162 E8559720_21 0 0.226 L1065550_18 0 0.396 L1065607_17 0 0.541 L1065944_24 0 0.131 L1066017_20 0 0.421 L1069261_12 0 0.357 L1069262_14 0 0.309 L1069263_27 0 0.283 L1069297_24 0 0.620 L1081528_21 0 0.561 L1084066_21 0 0.564 L1086090_21 0 0.649 L1104280_17 0 0.181 L1111362_22 0 0.199 L1118063_15 0 0.369 L1133550_21 0 0.302 L1144201_14 0 0.249 L1155023_7 0 0.257 L1158386_21 0 0.470 L1163051_4 0 0.446 ........................... ........................... ........................... > test Weight AB256870_21 0.364 AB256873_21 0.329 AB415518_21 0.219 AB460669_21 0.481 AB609036_21 0.313 AB609038_21 0.196 AB700495_21 0.402 AB700498_21 0.343 AC112834_21 0.372 AC185937_21 0.270 AC269527_21 0.285 E7352023_21 0.358 E7661554_21 0.471 E7750502_21 0.437 E7845183_21 0.232 E7854155_21 0.474 E7854156_21 0.121 E7924877_21 0.312 E7969079_21 0.423 E8139256_21 0.329 E8161577_22 1.060 E8161580_21 0.157 E8364473_21 0.227 E8364474_21 0.069 L1065940_14 0.256 L1065946_10 0.184 L1066018_25 0.282 L1069260_15 1.094 ................................ ................................ [[alternative HTML version deleted]]