I am collaborating in a project in which we are trying to detect aberrant splicing of mRNA of tumoral cells of patients with leukemia and studying the metabolic routes affected by the aberrant proteins generated in this type of cells...
To tackle this problem, in the first place I have posed me to carry out a filtering of the data tagged/flagged as "j" (which identifies novel splicing alternative transcript on the novelSplicingVariant files), with his back analysis of level of expression and enrichment (using the R libraries of and/or enrichment through web services like the provided by reactome, GO or DAVID).
But once exploded and exhausted this way, I'd like to know if starting from RNA-Seq raw fastq files, there would be some alternative way, reliable and more specific to face this problem, if possible, with tools that are available publicly at galaxy's servers.
On the other hand, I would also like :
To know approximately what would be the minimum value of FPKM (the data is paired-end) of a certain isoform (aberrant or not) from which we could consider it as not relevant for the case study.
If there is a specific workflow or protocol similar to Tuxedo for this purpose, since I have not found any to date.
How I could get the aberrant assembled sequence of mRNA.
For the analysis performed by the company that sequenced the samples, they made a similar approximation to the following:
1.- Fastqc (Quality Control of reads).
2.- Trimmomatic (Preprocesing of reads).
3.- TopHat (Mapping to reference genome, a splice-aware alligner).
4.- Cufflinks (Assembling aligned reads that contain paired-end information. That provides us information of known transcripts, novel transcripts, and alternative splicing transcripts, with their expression profiles).
They also Use:
5.- STAR with GATK (SNV calling of RNA-seq Dates, mapping quality reassignment, indel realignment, and basic recalibration. The reads created in the previous step were used for variant calling with HaplotypeCaller).
6.- deFuse (Fusion gene prediction).
In advance, thank you for your collaboration and answers.