Hi,

I am analysing my first Ribo-seq project and I am giving the "RiboProfiling" package a try.

I produced the "offset graphs" (Offset around TSS for the best expressed CDSs on a subset of match sizes) for one sample.

In the vignette - if my understanding is correct - the offsets calculated for various read match sizes are used to set the parameter "shiftValue" for the function "countShiftReads", next in the pipeline.

In the vignette, a consensus value is found: the shift value ranges from -11 to -13 over 4 read map sizes, so -11 is chosen.

There are in my case 5 very different shift values for 4 read map sizes: 2, 11, 15, 19; sum up being +11. Is it reliable with so much variation, and values not being even close? What can be the issue here? How can I proceed?

I'm too newbie to the Ribo-seq field to be able to interpret such a difference: could someone help me understand this?

My code so far:

aln <- GenomicAlignments::readGAlignments(
BamFile("sample1.bam")
)

# Histogram of read match length
matchLenDistr <- histMatchLength(aln, 0)
pdf("Hist_Match_length.pdf")
print(matchLenDistr)
dev.off()

# Read start coverage plot around the TSS
alnGRanges <- readsToStartOrEnd(aln, what="start")

# aroundPromoter: returns the genomic positions flanking the transcript start site (TSS) for the 3% best expressed CDSs
oneBinRanges <- aroundPromoter(TxDb.Mmusculus.UCSC.mm10.ensGene, alnGRanges, percBestExpressed=0.001)

# readStartCov: returns the read start coverage around the TSS on the predefined CDSs.
#the coverage in the TSS flanking region for the reads with match sizes 29:32
listPromoterCov <-
readStartCov(
alnGRanges,
oneBinRanges,
matchSize=c(29:32),
fixedInterval=c(-20, 20),
renameChr="aroundTSS",
charPerc="perc"
)

Thanks!

Sarah

sessionInfo()

R version 3.5.0 (2018-04-23)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.2 (Nitrogen)

Matrix products: default
BLAS/LAPACK: /nfs/software/as/el7.2/EasyBuild/CRG/software/OpenBLAS/0.2.20-GCC-6.4.0-2.28/lib/libopenblas_sandybridgep-r0.2.20.so

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] stats4    parallel  stats     graphics  grDevices utils     datasets
[8] methods   base     

other attached packages:
 [1] RSQLite_2.0                           
 [2] BSgenome.Mmusculus.UCSC.mm10_1.4.0    
 [3] BSgenome_1.48.0                       
 [4] rtracklayer_1.40.3                    
 [5] ggplot2_2.2.1                         
 [6] TxDb.Mmusculus.UCSC.mm10.ensGene_3.4.0
 [7] GenomicFeatures_1.32.0                
 [8] AnnotationDbi_1.42.1                  
 [9] Biobase_2.40.0                        
[10] RiboProfiling_1.10.0                  
[11] Rsamtools_1.32.0                      
[12] Biostrings_2.48.0                     
[13] XVector_0.20.0                        
[14] GenomicRanges_1.32.3                  
[15] GenomeInfoDb_1.16.0                   
[16] IRanges_2.14.10                       
[17] S4Vectors_0.18.3                      
[18] BiocGenerics_0.26.0                   
[19] DBI_1.0.0                             

loaded via a namespace (and not attached):
 [1] ProtGenerics_1.12.0         bitops_1.0-6               
 [3] matrixStats_0.53.1          bit64_0.9-7                
 [5] RColorBrewer_1.1-2          progress_1.1.2             
 [7] httr_1.3.1                  tools_3.5.0                
 [9] backports_1.1.2             R6_2.2.2                   
[11] rpart_4.1-13                Hmisc_4.1-1                
[13] lazyeval_0.2.1              colorspace_1.3-2           
[15] nnet_7.3-12                 gridExtra_2.3              
[17] prettyunits_1.0.2           GGally_1.3.2               
[19] bit_1.1-12                  curl_3.1                   
[21] compiler_3.5.0              chron_2.3-52               
[23] graph_1.58.0                htmlTable_1.11.2           
[25] DelayedArray_0.6.1          labeling_0.3               
[27] ggbio_1.28.0                scales_0.5.0               
[29] checkmate_1.8.5             RBGL_1.56.0                
[31] stringr_1.3.0               digest_0.6.15              
[33] foreign_0.8-69              base64enc_0.1-3            
[35] dichromat_2.0-0             pkgconfig_2.0.1            
[37] htmltools_0.3.6             ensembldb_2.4.1            
[39] htmlwidgets_1.0             rlang_0.2.0                
[41] rstudioapi_0.7              BiocInstaller_1.30.0       
[43] BiocParallel_1.14.1         acepack_1.4.1              
[45] VariantAnnotation_1.26.0    RCurl_1.95-4.10            
[47] magrittr_1.5                GenomeInfoDbData_1.1.0     
[49] Formula_1.2-2               Matrix_1.2-12              
[51] Rcpp_0.12.16                munsell_0.4.3              
[53] proto_1.0.0                 sqldf_0.4-11               
[55] stringi_1.1.7               SummarizedExperiment_1.10.1
[57] zlibbioc_1.26.0             plyr_1.8.4                 
[59] grid_3.5.0                  blob_1.1.0                 
[61] lattice_0.20-35             splines_3.5.0              
[63] knitr_1.20                  pillar_1.2.1               
[65] tcltk_3.5.0                 reshape2_1.4.3             
[67] biomaRt_2.36.1              XML_3.98-1.10              
[69] biovizBase_1.28.0           latticeExtra_0.6-28        
[71] data.table_1.10.4-3         gtable_0.2.0               
[73] reshape_0.8.7               assertthat_0.2.0           
[75] gsubfn_0.7                  AnnotationFilter_1.4.0     
[77] survival_2.41-3             tibble_1.4.2               
[79] OrganismDbi_1.22.0          GenomicAlignments_1.16.0   
[81] memoise_1.1.0               cluster_2.0.6