Hello,

I have finished the RNA seq analysis and I am trying to perform some pathway analysis. I have used the gage package and I was looking online about another package called goseq that takes into account length bias. However, when I run the code I get an error. How to solve that as I am not sure what the error means?

library(goseq)
supportedOrganisms() %>% filter(str_detect(Genome, "hg"))
#Step 1
#prepare the results for goseq
de.genes<-as.data.frame(resSig)
de.genes<- de.genes %>%
  mutate(DE_status=1)

res_non_de_genes<-res[!row.names(res) %in% row.names(resSig),]
res_non_de_genes<-as.data.frame(res_non_de_genes) %>%
  mutate(DE_status=0)

total.de.genes<-bind_rows(de.genes,res_non_de_genes)
nrow(total.de.genes)
total.de.genes$geneid<-row.names(total.de.genes)
total.de.genes$geneid<- substr(rownames(total.de.genes), 1, 15)
status<-total.de.genes$DE_status
names(status)<-total.de.genes$geneid


#to extract gene length
# Read the data into R 
genelength<- readDGE(rawfiles, columns=c(1,6), comment.char = "#")
# (as data frame to strip names of lists containing dimnames):
genelength <- data.frame(genelength$counts)
#to remove the extra header name
genelength<-genelength
for ( i in 1:ncol(genelength)){
  colnames(genelength)[i] <-  sub("_H.*", "", colnames(genelength)[i])
} 
# Convert count data to a matrix of appropriate form that DEseq2 can read
sampleIndex_genelength <- grepl("IGF\\d+", colnames(genelength))
genelength<- as.matrix(genelength[,sampleIndex_genelength])
check<-rowAlls(genelength)
all(check)
#we have check the all our samples have the same geneids and the same gene lenght
#we need a vector of gene ids and gene length only
genelength<-genelength[,1]
str(genelength)
genelength<-as.data.frame(genelength)
genelength$geneid<-row.names(genelength)
genelength<-genelength[row.names(total.de.genes),]
genelength$geneid<- substr(rownames(genelength), 1, 15)


all(rownames(genelength) %in% rownames(total.de.genes)) 
all(rownames(genelength) == rownames(total.de.genes))
gene_length<-genelength$genelength
names(gene_length)<-genelength$geneid


#fit the probability function
pwf <- nullp(status, "hg38", "ensGene", bias.data = gene_length)

#GO enrichment analysis
goResults <- goseq(pwf, "hg38","ensGene", test.cats=c("GO:BP","GO:CC","GO:MF"))

Fetching GO annotations... Error in (function (cond) : error in evaluating the argument 'x' in selecting a method for function 'toTable': disk I/O error

What does the error mean? I check and my data are in the right format. Any suggestions?

Thanks, Maria

sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)

Matrix products: default

locale:
[1] LC_COLLATE=English_United Kingdom.1252  LC_CTYPE=English_United Kingdom.1252   
[3] LC_MONETARY=English_United Kingdom.1252 LC_NUMERIC=C                           
[5] LC_TIME=English_United Kingdom.1252    

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] rtracklayer_1.54.0          goseq_1.46.0                geneLenDataBase_1.30.0     
 [4] BiasedUrn_1.07              pathview_1.32.0             org.Hs.eg.db_3.13.0        
 [7] GO.db_3.13.0                AnnotationDbi_1.56.2        gage_2.42.0                
[10] ggbeeswarm_0.6.0            RColorBrewer_1.1-2          vsn_3.60.0                 
[13] pcaExplorer_2.18.0          UpSetR_1.4.0                pheatmap_1.0.12            
[16] magrittr_2.0.2              DEFormats_1.20.0            reshape2_1.4.4             
[19] ggpubr_0.4.0                DESeq2_1.32.0               SummarizedExperiment_1.22.0
[22] Biobase_2.52.0              MatrixGenerics_1.4.3        matrixStats_0.61.0         
[25] GenomicRanges_1.44.0        GenomeInfoDb_1.28.4         IRanges_2.26.0             
[28] S4Vectors_0.30.0            BiocGenerics_0.38.0         forcats_0.5.1              
[31] stringr_1.4.0               dplyr_1.0.8                 purrr_0.3.4                
[34] readr_2.1.2                 tidyr_1.2.0                 tibble_3.1.6               
[37] ggplot2_3.3.5               tidyverse_1.3.1             edgeR_3.34.1               
[40] limma_3.48.3               

loaded via a namespace (and not attached):
  [1] utf8_1.2.2               shinydashboard_0.7.2     tidyselect_1.1.2        
  [4] heatmaply_1.3.0          RSQLite_2.2.10           htmlwidgets_1.5.4       
  [7] grid_4.1.2               TSP_1.1-11               BiocParallel_1.26.2     
 [10] munsell_0.5.0            preprocessCore_1.54.0    codetools_0.2-18        
 [13] DT_0.21                  withr_2.4.3              colorspace_2.0-2        
 [16] Category_2.60.0          filelock_1.0.2           knitr_1.37              
 [19] rstudioapi_0.13          ggsignif_0.6.3           NMF_0.23.0              
 [22] KEGGgraph_1.54.0         GenomeInfoDbData_1.2.7   topGO_2.46.0            
 [25] bit64_4.0.5              vctrs_0.3.8              generics_0.1.2          
 [28] xfun_0.29                BiocFileCache_2.2.1      R6_2.5.1                
 [31] doParallel_1.0.17        seriation_1.3.2          locfit_1.5-9.4          
 [34] bitops_1.0-7             cachem_1.0.6             shinyAce_0.4.1          
 [37] DelayedArray_0.18.0      assertthat_0.2.1         BiocIO_1.4.0            
 [40] promises_1.2.0.1         scales_1.1.1             beeswarm_0.4.0          
 [43] gtable_0.3.0             affy_1.70.0              rlang_1.0.1             
 [46] genefilter_1.74.0        splines_4.1.2            rstatix_0.7.0           
 [49] lazyeval_0.2.2           shinyBS_0.61             broom_0.7.12            
 [52] checkmate_2.0.0          yaml_2.3.5               BiocManager_1.30.16     
 [55] abind_1.4-5              modelr_0.1.8             GenomicFeatures_1.46.5  
 [58] threejs_0.3.3            crosstalk_1.2.0          backports_1.4.1         
 [61] httpuv_1.6.5             RBGL_1.68.0              tools_4.1.2             
 [64] gridBase_0.4-7           affyio_1.62.0            ellipsis_0.3.2          
 [67] Rcpp_1.0.8               plyr_1.8.6               base64enc_0.1-3         
 [70] progress_1.2.2           zlibbioc_1.38.0          RCurl_1.98-1.6          
 [73] prettyunits_1.1.1        viridis_0.6.2            haven_2.4.3             
 [76] ggrepel_0.9.1            cluster_2.1.2            fs_1.5.2                
 [79] data.table_1.14.2        SparseM_1.81             reprex_2.0.1            
 [82] hms_1.1.1                mime_0.12                evaluate_0.15           
 [85] xtable_1.8-4             XML_3.99-0.8             readxl_1.3.1            
 [88] gridExtra_2.3            compiler_4.1.2           biomaRt_2.50.3          
 [91] crayon_1.5.0             htmltools_0.5.2          GOstats_2.60.0          
 [94] mgcv_1.8-39              later_1.3.0              tzdb_0.2.0              
 [97] geneplotter_1.72.0       lubridate_1.8.0          DBI_1.1.2               
[100] dbplyr_2.1.1             MASS_7.3-55              rappdirs_0.3.3          
[103] Matrix_1.4-0             car_3.0-12               cli_3.2.0               
[106] glmpca_0.2.0             igraph_1.2.11            pkgconfig_2.0.3         
[109] GenomicAlignments_1.30.0 registry_0.5-1           plotly_4.10.0           
[112] xml2_1.3.3               foreach_1.5.2            annotate_1.72.0         
[115] vipor_0.4.5              rngtools_1.5.2           pkgmaker_0.32.2         
[118] webshot_0.5.2            XVector_0.32.0           AnnotationForge_1.36.0  
[121] rvest_1.0.2              digest_0.6.29            graph_1.70.0            
[124] Biostrings_2.60.2        rmarkdown_2.11           cellranger_1.1.0        
[127] dendextend_1.15.2        GSEABase_1.56.0          restfulr_0.0.13         
[130] curl_4.3.2               Rsamtools_2.10.0         shiny_1.7.1             
[133] rjson_0.2.21             nlme_3.1-155             lifecycle_1.0.1         
[136] jsonlite_1.7.3           carData_3.0-5            viridisLite_0.4.0       
[139] fansi_1.0.2              pillar_1.7.0             lattice_0.20-45         
[142] KEGGREST_1.34.0          fastmap_1.1.0            httr_1.4.2              
[145] survival_3.2-13          glue_1.6.1               png_0.1-7               
[148] iterators_1.0.14         bit_4.0.4                Rgraphviz_2.36.0        
[151] stringi_1.7.6            blob_1.2.2               memoise_2.0.1           
>

The disk I/O error makes me think that your hard drive is full, although it is not clear to me at which point toTable should be writing anything to disk.

But the call to toTable is

x <- toTable(org.Hs.egGO2ALLEGS)

Which you could try running yourself to see if you can replicate the error. But I would check your disk space first.