Rsubread - featureCounts for extracting read counts from De novo assembled transcripts
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Alan Smith ▴ 150
@alan-smith-5987
Last seen 7.0 years ago
United States
Hello, I'm trying to use featureCounts to extract read counts per transcript from the SAM file (generated using Bowtie2) mapped to de novo assembled transcripts (for DE analysis). I made annotation file as per the SAF requirements: Eg: *GeneID Chr Start End Strand* Locus_47_Transcript_16/31_Confidence_0.158_Length_1485 Locus_47_Transcript_16/31_Confidence_0.158_Length_1485 1 1485 + Locus_58_Transcript_85/85_Confidence_0.017_Length_650 Locus_58_Transcript_85/85_Confidence_0.017_Length_650 1 650 + Here I made both the GeneID and the Chr columns same with *Start* being 1 and *End* as the length of the transcript and the Strand as + for all transcripts. When I used the following code, it does nothing for a while and then R crashes. library(Rsubread) counts <- featureCounts(files="AssembledTranscriptome-LMcontrol1.sam",annot="Ann otRsubreadSAF.txt",isGTFAnnotationFile=FALSE) Rsubread works great with GTF as annot parameter on genome mapped SAM files but not with the SAF, as I tried here. Please let me know where I'm wrong here or if anyone tried other packages that serves the purpose. sessionInfo() R version 3.0.1 (2013-05-16) Platform: x86_64-redhat-linux-gnu (64-bit) locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C 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 LC_PAPER=C LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] splines parallel grid stats graphics grDevices utils datasets methods base other attached packages: [1] Rsamtools_1.12.3 edgeR_3.2.4 Rsubread_1.10.5 [4] ChIPpeakAnno_2.8.0 GenomicFeatures_1.12.3 limma_3.16.7 [7] org.Hs.eg.db_2.9.0 GO.db_2.9.0 RSQLite_0.11.4 [10] DBI_0.2-7 AnnotationDbi_1.22.6 BSgenome.Ecoli.NCBI.20080805_1.3.17 [13] BSgenome_1.28.0 GenomicRanges_1.12.4 Biostrings_2.28.0 [16] IRanges_1.18.2 multtest_2.16.0 Biobase_2.20.1 [19] biomaRt_2.16.0 BiocGenerics_0.6.0 VennDiagram_1.6.4 [22] sendmailR_1.1-2 base64enc_0.1-1 BiocInstaller_1.10.3 loaded via a namespace (and not attached): [1] bitops_1.0-5 MASS_7.3-26 RCurl_1.95-4.1 rtracklayer_1.20.4 stats4_3.0.1 [6] survival_2.37-4 tools_3.0.1 XML_3.98-1.1 zlibbioc_1.6.0 [[alternative HTML version deleted]]
Annotation GO BSgenome BSgenome Annotation GO BSgenome BSgenome • 1.1k views
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