Hello everyone! I'm new in RNAseq data analysis and trying to apply a pipeline from an online course to A.thaliana data in my university course project. The pipeline includes kallisto quantification with subsequent analysis in R. I performed kallisto quantification with A.thaliana transcriptome, which I downloaded from plants.ensembl.org, got all the esential files. Firstly, I imported studydesign and set paths to abundance.tsv files:

targets <- read_tsv("ATstudydesign.txt")
path <- file.path(targets$Sample[1:12], "abundance.tsv")

Now, the main trouble is how to import data from abundance.tsv files to R project and to replace transcript names with gene names.

I need a tx2gene object for tximport() function and, as I understand, there are several ways to create it. I tried to create it by downloading a table from https://plants.ensembl.org/biomart/martview/18f83aa36cd9df8402183dba5ee6d603

Then I imported it into R project:

Tx <- read_tsv("mart_export.txt")
head(Tx)

The Tx file looks good since it has transcripts names in the first column and gene names in the second:

> head(Tx)
# A tibble: 6 × 2
  `Transcript stable ID` `Gene name`
  <chr>                  <chr>      
1 AT3G11415.1            AT3G11415  
2 AT1G31258.1            AT1G31258  
3 AT5G24735.1            AT5G24735  
4 AT2G45780.1            AT2G45780  
5 AT2G42425.1            AT2G42425  
6 AT4G01533.1            AT4G01533

I ran tximport() function but got an error:

> Txi_gene <- tximport(path, 
+                      type = "kallisto", 
+                      tx2gene = Tx, 
+                      txOut = FALSE,
+                      countsFromAbundance = "lengthScaledTPM",
+                      ignoreTxVersion = TRUE)
Note: importing `abundance.h5` is typically faster than `abundance.tsv`
reading in files with read_tsv
1 2 3 4 5 6 7 8 9 10 11 12 
Error in .local(object, ...) : 
  None of the transcripts in the quantification files are present
  in the first column of tx2gene. Check to see that you are using
  the same annotation for both.

Example IDs (file): [AT1G76820, ATMG00060, AT4G16360, ...]

Example IDs (tx2gene): [AT3G11415.1, AT1G31258.1, AT5G24735.1, ...]

  This can sometimes (not always) be fixed using 'ignoreTxVersion' or 'ignoreAfterBar'.

I tried to look at abundance.tsv file by importing the data from it:

Sample <- read_tsv("./RootCtrl1/abundance.tsv")
> head(Sample)
# A tibble: 6 × 5
  target_id   length eff_length est_counts    tpm
  <chr>        <dbl>      <dbl>      <dbl>  <dbl>
1 AT1G76820.1   3857      3645.       21.8  0.934
2 ATMG00060.1    542       333.        2    0.939
3 AT4G16360.1   1685      1473.      465   49.3  
4 AT5G26800.1    637       426.      166   60.9  
5 AT4G16110.1   2666      2454.      293   18.7  
6 AT5G39100.1    808       597.        0    0

I also tried to search several transcript names in abundance.tsv and mart_export.txt and I was able to find them in both files through simple Find in Sublime text editor.

Can't understand what's wrong with these commands and/or files. Maybe someone will share thoughts or suuggestions? Maybe there are alternative ways to create this tx2gene objects? Thanks in advance!

sessionInfo( )

> sessionInfo()
R version 4.2.2 (2022-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19044)

Matrix products: default

locale:
[1] LC_COLLATE=Russian_Russia.utf8  LC_CTYPE=Russian_Russia.utf8    LC_MONETARY=Russian_Russia.utf8
[4] LC_NUMERIC=C                    LC_TIME=Russian_Russia.utf8    

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

other attached packages:
 [1] tximport_1.26.0 forcats_0.5.2   stringr_1.4.1   dplyr_1.0.10    purrr_0.3.5     readr_2.1.3     tidyr_1.2.1    
 [8] tibble_3.1.8    ggplot2_3.4.0   tidyverse_1.3.2

loaded via a namespace (and not attached):
  [1] bitops_1.0-7                matrixStats_0.62.0          fs_1.5.2                    lubridate_1.9.0            
  [5] bit64_4.0.5                 filelock_1.0.2              progress_1.2.2              httr_1.4.4                 
  [9] GenomeInfoDb_1.32.2         tools_4.2.2                 backports_1.4.1             utf8_1.2.2                 
 [13] R6_2.5.1                    DBI_1.1.3                   BiocGenerics_0.42.0         colorspace_2.0-3           
 [17] rhdf5filters_1.8.0          withr_2.5.0                 tidyselect_1.2.0            prettyunits_1.1.1          
 [21] bit_4.0.4                   curl_4.3.3                  compiler_4.2.2              rvest_1.0.3                
 [25] cli_3.3.0                   Biobase_2.56.0              xml2_1.3.3                  DelayedArray_0.22.0        
 [29] rtracklayer_1.56.1          scales_1.2.1                rappdirs_0.3.3              digest_0.6.30              
 [33] Rsamtools_2.12.0            XVector_0.36.0              pkgconfig_2.0.3             MatrixGenerics_1.8.1       
 [37] dbplyr_2.2.1                fastmap_1.1.0               readxl_1.4.1                rlang_1.0.6                
 [41] rstudioapi_0.14             RSQLite_2.2.15              BiocIO_1.6.0                generics_0.1.3             
 [45] jsonlite_1.8.3              vroom_1.6.0                 BiocParallel_1.30.3         googlesheets4_1.0.1        
 [49] RCurl_1.98-1.8              magrittr_2.0.3              GenomeInfoDbData_1.2.8      Matrix_1.5-1               
 [53] Rhdf5lib_1.18.2             Rcpp_1.0.9                  munsell_0.5.0               S4Vectors_0.34.0           
 [57] fansi_1.0.3                 lifecycle_1.0.3             stringi_1.7.8               yaml_2.3.6                 
 [61] SummarizedExperiment_1.26.1 zlibbioc_1.42.0             rhdf5_2.40.0                BiocFileCache_2.4.0        
 [65] grid_4.2.2                  blob_1.2.3                  parallel_4.2.2              crayon_1.5.2               
 [69] lattice_0.20-45             Biostrings_2.64.0           haven_2.5.1                 GenomicFeatures_1.48.3     
 [73] hms_1.1.2                   KEGGREST_1.36.3             pillar_1.8.1                GenomicRanges_1.48.0       
 [77] rjson_0.2.21                codetools_0.2-18            biomaRt_2.52.0              stats4_4.2.2               
 [81] reprex_2.0.2                XML_3.99-0.10               glue_1.6.2                  modelr_0.1.10              
 [85] tzdb_0.3.0                  png_0.1-7                   vctrs_0.5.0                 cellranger_1.1.0           
 [89] gtable_0.3.1                assertthat_0.2.1            cachem_1.0.6                broom_1.0.1                
 [93] restfulr_0.0.15             googledrive_2.0.0           gargle_1.2.1                GenomicAlignments_1.32.1   
 [97] AnnotationDbi_1.58.0        memoise_2.0.1               IRanges_2.30.0              timechange_0.1.1           
[101] ellipsis_0.3.2

One of the things you have to learn when starting out with R (and any software for that matter) is that the error messages mean something. Here is the error message you got.

Error in .local(object, ...) : 
  None of the transcripts in the quantification files are present
  in the first column of tx2gene. Check to see that you are using
  the same annotation for both.

Example IDs (file): [AT1G76820, ATMG00060, AT4G16360, ...]

Example IDs (tx2gene): [AT3G11415.1, AT1G31258.1, AT5G24735.1, ...]

  This can sometimes (not always) be fixed using 'ignoreTxVersion' or 'ignoreAfterBar'.

Which clearly shows you what IDs you are using, and the IDs that are expected, and even recommends the solution! Upon reading that message, you can then do ?tximport, which will provide this, in the arguments section

ignoreTxVersion: logical, whether to split the tx id on the '.'
          character to remove version information to facilitate
          matching with the tx id in 'tx2gene' (default FALSE)