Thanks for the suggestion. I was already planning on running either StringTie or gmap. But just for clarifications - do you mean using the results of the trinity run (e.g. Trinity.fasta) to map against the indexed genome of the close relative?
something like that:
gmap_build -d Genome -D ./indexedFolder -k 13 closeRelative.fa
gmap -n 0 -D ./indexedFolder -d Genome ../trinity/trinity_output/Trinity.fasta -f gff3_gene > trinity_gmap.gff
How can I than make sense out of the gff file? Did you use transdecoder on the gff file as well?
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Assa Yeroslaviz
If you have a close relative reference genome, why do you consider necesary to do a de novo assembly? which is the purpose? obtain the transcriptome? or evaluate the assembler performance?
the first one. I would like to obtain the annotated transcriptome of the said organism.
Would BLASTing my transcripts from Trinity (
Trinity.fasta) against the genome (genome.fafile) of the close relative would give me good enough results?If you need the transcriptome and the reference genome is closely-related and well annotated, you can just quantify the transcript expression using StrinTie and also look for new isoforms more than compare assembled transcripts.
I have already done two things.
transcript.fastafile with the assembled transcripts. this was followed by running bowtie of the fastq files against the indexedtranscript.fastafile.From both runs i got a bam file, which is needed by StringTie If I run StringTie against the first bam file, I won't have the annotations I need, but running StringTie with the second bam file - I don't have an annotation file (gtf), so I am not sure if this make sense. Can I use as input the bam file from the de-novo assembly, but takes the annotation file from the close relative?
Run Stringtie with the bam of step 1 and the GENOME annotation (GTF, GFF or GFF3), you do not need an extra annotation. Bam file contain the coordinates where each read is aligned to the genome, stringtie just count how many reads align to each annotated gene and calculates relative expression (TPM and FPKM). You can also count the mapped reads (to each annotated gene of bam1 ) with htseq-count and then calculate relative expression.
But I'm not primarily interested in counting the expression. This is only a secondary results of the analysis.
I am more interested in creating an annotation file for my genome, which has no annotations. I would like to try comparative genomics which can assign/predict functionality to my transcripts( I was thinking something like via BLAST or other ORF-reading comparison tools).
you can also use stringtie or cufflinks to annotate your transcripts to the genome. To assign potential functionality to your transcripts you can use blast, but I recommend you Blast2GO, it is more easy to handle and can perform exactly you are looking for.