Hi,

I have troubles with using tximeta from the sample table (Cov below).

I loaded the sample table (3 columns, names (all unique), files (absolute paths to quant.sf) & condition (all "A")). I have created a linked transcriptome from downloaded files using:

makeLinkedTxome(
    indexDir=<abs path to salmon indices directory>, 
    source="Gencode", organism="Homo sapiens", release="31", genome="GRCh38", 
    fasta=<absolute path to the gentrome.fa file obtained from salmon tools>, 
    gtf=<absolute path to the GENCODE gtf file>, 
    write=TRUE
)

The command seems to be successful, it creates a json file near the salmon indices directory.

When I try to import the data, it fails:

> se <- tximeta(Cov)
Error in FUN(X[[i]], ...) : file.exists(jsonPath) is not TRUE
> traceback()
5: stop(simpleError(msg, call = if (p <- sys.parent(1L)) sys.call(p)))
4: stopifnot(file.exists(jsonPath))
3: FUN(X[[i]], ...)
2: lapply(files, getMetaInfo)
1: tximeta(Cov)

It seems that it can't find file aux_info/meta_info.json. Indeed, there are no such file, neither in the cache, nor in the indices, nor with the quant.sf files.

I am not sure what I am doing wrong here. I am using salmon 0.14.1, and the sessionInfo is shown below.

Thanks for your help, Eric

R version 3.6.0 (2019-04-26)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.6 LTS

Matrix products: default
BLAS:   /usr/lib/libblas/libblas.so.3.6.0
LAPACK: /usr/lib/lapack/liblapack.so.3.6.0

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
[1] tximeta_1.2.2 magrittr_1.5 

loaded via a namespace (and not attached):
 [1] SummarizedExperiment_1.13.0 tximport_1.12.3            
 [3] progress_1.2.0              tidyselect_0.2.5           
 [5] purrr_0.3.2                 lattice_0.20-38            
 [7] stats4_3.6.0                BiocFileCache_1.8.0        
 [9] rtracklayer_1.43.6          GenomicFeatures_1.35.12    
[11] blob_1.1.1                  XML_3.98-1.19              
[13] rlang_0.3.4                 pillar_1.4.1               
[15] glue_1.3.1                  DBI_1.0.0                  
[17] ensembldb_2.8.0             BiocParallel_1.17.19       
[19] rappdirs_0.3.1              BiocGenerics_0.29.2        
[21] bit64_0.9-7                 dbplyr_1.4.2               
[23] matrixStats_0.54.0          GenomeInfoDbData_1.2.1     
[25] ProtGenerics_1.16.0         stringr_1.4.0              
[27] zlibbioc_1.29.0             Biostrings_2.51.5          
[29] memoise_1.1.0               Biobase_2.43.1             
[31] IRanges_2.17.6              biomaRt_2.39.4             
[33] GenomeInfoDb_1.19.3         parallel_3.6.0             
[35] curl_3.3                    AnnotationDbi_1.45.1       
[37] Rcpp_1.0.1                  readr_1.3.1                
[39] BiocManager_1.30.4          DelayedArray_0.9.9         
[41] S4Vectors_0.21.24           jsonlite_1.6               
[43] XVector_0.23.2              bit_1.1-14                 
[45] Rsamtools_1.99.6            hms_0.4.2                  
[47] digest_0.6.18               stringi_1.4.3              
[49] dplyr_0.8.1                 GenomicRanges_1.35.2       
[51] grid_3.6.0                  tools_3.6.0                
[53] bitops_1.0-6                lazyeval_0.2.2             
[55] RCurl_1.95-4.12             tibble_2.1.3               
[57] RSQLite_2.1.1               crayon_1.3.4               
[59] pkgconfig_2.0.2             Matrix_1.2-17              
[61] prettyunits_1.0.2           assertthat_0.2.1           
[63] httr_1.4.0                  AnnotationFilter_1.8.0     
[65] R6_2.4.0                    GenomicAlignments_1.19.1   
[67] compiler_3.6.0             

Good question. It looks like I could definitely improve both the error messaging and documentation on this point:

The quant.sf files are just one part of the Salmon output directory. tximeta makes use of and requires the entire directory as it was output by Salmon. It's generally a good idea with any bioinformatic software output to preserve the entire output as is (if it outputs a directory of plaintext files instead of a single binarized file), as it will ensure that downstream software will work as intended.