On #IAmAResearchParasite, professional development and various RNA-Seq pipelines
Having just graduated with a M.Sc. I've got some free-time I would like to dedicate to learning some new bioinformatics software.
RNA-seq can give many views of biology depending on the pipeline: differential expression, genetic variation (SNVs,indels, transversions), gene fusion detection, finding ncRNAs and new genes, predicting polyA sites and gain/loss of miRNA binding sites, to even investigating the RNA for remaining reads (coming from viruses/bacteria/other).
As my dissertation experiment was designed to investigate differential expression patterns I would like to know if it is appropriate to investigate the data in another way (using another pipeline listed above)? I've been considering asking my PI for extended access to the HPC so I can learn a new pipeline; ideally I scratch his back in return by proposing a side project I could get another manuscript out of.
I believe my previous question relates to #IAmAResearchParasite in the following way. I've heard that some researchers analyze public available datasets (NIH, EMBL, CGAT, etc.) but I'm wondering about how to best select an appropriate dataset (and question of interest). Is there concerns of not understanding the choices made in the generation and collection of the data by the original authors? What might they be?
Has anyone had experience approaching the investigators with their own ideas and working symbiotically with them? Ideally, I would like to identify a potential collaborators whose collected data may be useful in assessing another hypothesis which they may not have thought of, lacked the time or even technical ability to perform that analysis.
Comments greatly appreciated
RNA-seq can give many views of biology depending on the pipeline: differential expression, genetic variation (SNVs,indels, transversions), gene fusion detection, finding ncRNAs and new genes, predicting polyA sites and gain/loss of miRNA binding sites, to even investigating the RNA for remaining reads (coming from viruses/bacteria/other).
As my dissertation experiment was designed to investigate differential expression patterns I would like to know if it is appropriate to investigate the data in another way (using another pipeline listed above)? I've been considering asking my PI for extended access to the HPC so I can learn a new pipeline; ideally I scratch his back in return by proposing a side project I could get another manuscript out of.
I believe my previous question relates to #IAmAResearchParasite in the following way. I've heard that some researchers analyze public available datasets (NIH, EMBL, CGAT, etc.) but I'm wondering about how to best select an appropriate dataset (and question of interest). Is there concerns of not understanding the choices made in the generation and collection of the data by the original authors? What might they be?
Has anyone had experience approaching the investigators with their own ideas and working symbiotically with them? Ideally, I would like to identify a potential collaborators whose collected data may be useful in assessing another hypothesis which they may not have thought of, lacked the time or even technical ability to perform that analysis.
Comments greatly appreciated