Hi,

I observed this error when working with tximeta::summarizeToGene for the first time with some datasets.

> gse <- summarizeToGene(se)
loading existing TxDb created: 2020-04-15 15:05:07
Loading required package: GenomicFeatures
Loading required package: AnnotationDbi

Attaching package: 'AnnotationDbi'

The following object is masked from 'package:dplyr':

    select

obtaining transcript-to-gene mapping from TxDb
generating gene ranges
Error in (function (x)  : attempt to apply non-function
summarizing abundance
summarizing counts
summarizing length

Not sure if this is an issue—the gse object seems to be O.K.

Thanks, Kris

Code

#  Load libraries (if commented out, then done above)
load_pack <- c("airway", "tximeta", "DESeq2", "tidyverse")
lapply(load_pack, library, character.only = TRUE)

#  Set working directory
setwd("/Users/ala1zp/Dropbox/professional/_experiments_projects/2020_0324_0400_work_notes_H3K9me3_RNAseq/code_log/tmp_current/RNAseq_work_041020")

#  Load the sample table as a data frame
st <- read.csv("sample_table_041320.csv", row.names = 1, stringsAsFactors = FALSE)

#  Locate and download relevant annotation data, perform transcript-level quantifications
se <- tximeta(st)  # Remember, tximeta "wants" two of the columns to be "files", "names"

#  Examine the structure of the se generated fr/t/Mcaf2 data
dim(se)  #> [1] 140948 4
head(rownames(se))

#  Summarize the transcript-level quantifications to the gene level
gse <- summarizeToGene(se)

#  Examine the structure, features of the gse generated fr/t/Mcaf2 data
dim(gse)  #> [1] 54331 4
head(rownames(gse))

Terminal

> #  Load libraries (if commented out, then done above)
> load_pack <- c("airway", "tximeta", "DESeq2", "tidyverse")
> lapply(load_pack, library, character.only = TRUE)
Loading required package: SummarizedExperiment
Loading required package: GenomicRanges
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’:

    anyDuplicated, append, as.data.frame, basename, cbind, colnames, dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
    grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
    rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply, union, unique, unsplit, which, which.max, which.min

Loading required package: S4Vectors

Attaching package: ‘S4Vectors’

The following object is masked from ‘package:base’:

    expand.grid

Loading required package: IRanges
Loading required package: GenomeInfoDb
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: DelayedArray
Loading required package: matrixStats

Attaching package: ‘matrixStats’

The following objects are masked from ‘package:Biobase’:

    anyMissing, rowMedians

Loading required package: BiocParallel

Attaching package: ‘DelayedArray’

The following objects are masked from ‘package:matrixStats’:

    colMaxs, colMins, colRanges, rowMaxs, rowMins, rowRanges

The following objects are masked from ‘package:base’:

    aperm, apply, rowsum

── Attaching packages ──────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
✓ ggplot2 3.3.0     ✓ purrr   0.3.3
✓ tibble  3.0.0     ✓ dplyr   0.8.5
✓ tidyr   1.0.2     ✓ stringr 1.4.0
✓ readr   1.3.1     ✓ forcats 0.5.0
── Conflicts ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
x dplyr::collapse()   masks IRanges::collapse()
x dplyr::combine()    masks Biobase::combine(), BiocGenerics::combine()
x dplyr::count()      masks matrixStats::count()
x dplyr::desc()       masks IRanges::desc()
x tidyr::expand()     masks S4Vectors::expand()
x dplyr::filter()     masks stats::filter()
x dplyr::first()      masks S4Vectors::first()
x dplyr::lag()        masks stats::lag()
x ggplot2::Position() masks BiocGenerics::Position(), base::Position()
x purrr::reduce()     masks GenomicRanges::reduce(), IRanges::reduce()
x dplyr::rename()     masks S4Vectors::rename()
x purrr::simplify()   masks DelayedArray::simplify()
x dplyr::slice()      masks IRanges::slice()

## * + * + (to decrease the character count for Bioconductor, I cut [[1]], [[2]], and [[3]]) + * + * ##

[[4]]
 [1] "forcats"              "stringr"              "dplyr"                "purrr"                "readr"                "tidyr"               
 [7] "tibble"               "ggplot2"              "tidyverse"            "DESeq2"               "tximeta"              "airway"              
[13] "SummarizedExperiment" "DelayedArray"         "BiocParallel"         "matrixStats"          "Biobase"              "GenomicRanges"       
[19] "GenomeInfoDb"         "IRanges"              "S4Vectors"            "BiocGenerics"         "parallel"             "stats4"              
[25] "stats"                "graphics"             "grDevices"            "utils"                "datasets"             "methods"             
[31] "base"                

> #  Set working directory
> setwd("/Users/ala1zp/Dropbox/professional/_experiments_projects/2020_0324_0400_work_notes_H3K9me3_RNAseq/code_log/tmp_current/RNAseq_work_041020")
> #  Load the sample table as a data frame
> st <- read.csv("sample_table_041320.csv", row.names = 1, stringsAsFactors = FALSE)
> #  Locate and download relevant annotation data, perform transcript-level quantifications
> se <- tximeta(st)  # Remember, tximeta "wants" two of the columns to be "files", "names"
importing quantifications
reading in files with read_tsv
1 2 3 4 

tximeta needs a BiocFileCache directory to access and save TxDb objects.
Do you wish to use the default directory: '/Users/ala1zp/Library/Caches/BiocFileCache'?
If not, a temporary directory that is specific to this R session will be used.

You can always change this directory later by running: setTximetaBFC()
Or enter [0] to exit and set this directory manually now. 

1: Yes (use default)
2: No (use temp)

Selection: 1
/Users/ala1zp/Library/Caches/BiocFileCache
  does not exist, create directory? (yes/no): yes
found matching transcriptome:
[ GENCODE - Mus musculus - release M24 ]
building TxDb with 'GenomicFeatures' package
Import genomic features from the file as a GRanges object ... trying URL 'ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_mouse/release_M24/gencode.vM24.annotation.gtf.gz'
Content type 'unknown' length 28499422 bytes (27.2 MB)
==================================================
OK
Prepare the 'metadata' data frame ... OK
Make the TxDb object ... OK
generating transcript ranges
fetching genome info for GENCODE
Warning message:
In .get_cds_IDX(mcols0$type, mcols0$phase) :
  The "phase" metadata column contains non-NA values for features of type stop_codon. This information was ignored.
> #  Examine the structure of the se generated fr/t/Mcaf2 data
> dim(se)  #> [1] 140948 4
[1] 140948      4
> head(rownames(se))
[1] "ENSMUST00000193812.1" "ENSMUST00000082908.1" "ENSMUST00000162897.1" "ENSMUST00000159265.1" "ENSMUST00000070533.4" "ENSMUST00000192857.1"
> #  Summarize the transcript-level quantifications to the gene level
> gse <- summarizeToGene(se)
loading existing TxDb created: 2020-04-15 15:05:07
Loading required package: GenomicFeatures
Loading required package: AnnotationDbi

Attaching package: 'AnnotationDbi'

The following object is masked from 'package:dplyr':

    select

obtaining transcript-to-gene mapping from TxDb
generating gene ranges
Error in (function (x)  : attempt to apply non-function
summarizing abundance
summarizing counts
summarizing length
> #  Examine the structure, features of the gse generated fr/t/Mcaf2 data
> dim(gse)  #> [1] 54331 4
[1] 54331     4

traceback()

> traceback()
1: (function (x) 
   x$.self$finalize())(<environment>)

sessionInfo()

> sessionInfo()
R version 3.6.3 (2020-02-29)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS Catalina 10.15.2

Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Users/ala1zp/anaconda3/envs/r3-6-2_test_env/lib/libopenblasp-r0.3.7.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

other attached packages:
 [1] GenomicFeatures_1.38.0      AnnotationDbi_1.48.0        forcats_0.5.0               stringr_1.4.0               dplyr_0.8.5                
 [6] purrr_0.3.3                 readr_1.3.1                 tidyr_1.0.2                 tibble_3.0.0                ggplot2_3.3.0              
[11] tidyverse_1.2.1             DESeq2_1.26.0               tximeta_1.4.3               airway_1.6.0                SummarizedExperiment_1.16.0
[16] DelayedArray_0.12.0         BiocParallel_1.20.0         matrixStats_0.56.0          Biobase_2.46.0              GenomicRanges_1.38.0       
[21] GenomeInfoDb_1.22.0         IRanges_2.20.0              S4Vectors_0.24.0            BiocGenerics_0.32.0        

loaded via a namespace (and not attached):
  [1] colorspace_1.4-1         ellipsis_0.3.0           htmlTable_1.13.3         XVector_0.26.0           base64enc_0.1-3         
  [6] rstudioapi_0.11          bit64_0.9-7              fansi_0.4.1              lubridate_1.7.8          xml2_1.3.1              
 [11] splines_3.6.3            tximport_1.14.0          geneplotter_1.64.0       knitr_1.28               Formula_1.2-3           
 [16] jsonlite_1.6.1           Rsamtools_2.2.0          broom_0.5.5              annotate_1.64.0          cluster_2.1.0           
 [21] dbplyr_1.4.2             png_0.1-7                compiler_3.6.3           httr_1.4.1               backports_1.1.6         
 [26] assertthat_0.2.1         Matrix_1.2-18            lazyeval_0.2.2           cli_2.0.2                acepack_1.4.1           
 [31] htmltools_0.4.0          prettyunits_1.1.1        tools_3.6.3              gtable_0.3.0             glue_1.4.0              
 [36] GenomeInfoDbData_1.2.2   rappdirs_0.3.1           Rcpp_1.0.4.6             cellranger_1.1.0         vctrs_0.2.4             
 [41] Biostrings_2.54.0        nlme_3.1-147             rtracklayer_1.46.0       xfun_0.13                rvest_0.3.5             
 [46] lifecycle_0.2.0          ensembldb_2.10.0         XML_3.99-0.3             zlibbioc_1.32.0          scales_1.1.0            
 [51] hms_0.5.3                ProtGenerics_1.18.0      AnnotationFilter_1.10.0  RColorBrewer_1.1-2       yaml_2.2.1              
 [56] curl_4.3                 memoise_1.1.0            gridExtra_2.3            biomaRt_2.42.0           rpart_4.1-15            
 [61] latticeExtra_0.6-29      stringi_1.4.6            RSQLite_2.2.0            genefilter_1.68.0        checkmate_2.0.0         
 [66] rlang_0.4.5              pkgconfig_2.0.3          bitops_1.0-6             lattice_0.20-41          GenomicAlignments_1.22.0
 [71] htmlwidgets_1.5.1        bit_1.1-15.2             tidyselect_1.0.0         magrittr_1.5             R6_2.4.1                
 [76] generics_0.0.2           Hmisc_4.4-0              DBI_1.1.0                withr_2.1.2              pillar_1.4.3            
 [81] haven_2.2.0              foreign_0.8-76           survival_3.1-12          RCurl_1.98-1.1           nnet_7.3-13             
 [86] modelr_0.1.6             crayon_1.3.4             BiocFileCache_1.10.0     jpeg_0.1-8.1             progress_1.2.2          
 [91] readxl_1.3.1             locfit_1.5-9.4           grid_3.6.3               data.table_1.12.8        blob_1.2.1              
 [96] digest_0.6.25            xtable_1.8-4             openssl_1.4.1            munsell_0.5.0            askpass_1.1

The final object looks fine to me

I'm not sure where the error is coming from x$.self$finalize(). That may be part of SummarizedExperiment, but I'm not certain.