Unfortunately, this was the best position I was able to capture for a live talk! I hope that the most important information can still be viewed and understood. :)

can you describe your query parameters / provide a link to a screenshot of your settings. Typically, you need to select raw reads on one of the panels, although I believe the ENA has recently updated their online interface. You can batch search / pulldown information better by querying the API: ena-docs.readthedocs.io/en/latest/retrieval/programmatic-access.html

@@makethebrainhappy-scientificex yeah, the api worked well, thank you

I would suggest that the median gene length is the most representative as it would average transcripts B and C (assuming A>B>C>D) which would more appropriately reflect the effective size that is being transcribed. However, ultimately if the locus has significant expression then transcript-level alignment and normalization based on transcript length would be more appropriate. Ultimately, we calculate gene length because we are unable for NGSS to resolve transcript level differences. However, if you have significant number of NGSS reads aligned especially on short transcripts (300-500 nt), then you should be able to resolve this on the level of the transcript.

@@makethebrainhappy-scientificex Thanks. Just one question more. At the time I have transcript quantification for A, B, C and D, Can I sums the transcript quantification value to get the gene expression? (assuming A, B, C and D are transcripts, or isoforms, for a single gene).

@@Cesar06100090 Yes, this is a valid way to summarize gene expression from transcript quantifications.

The data which I am accessing is available through the NCBI's public repository: www.ncbi.nlm.nih.gov/ (with the SRR accession number shown in the video). The code is based on the tutorials available on the fastp github page. Right now the google colaboratory has not been released publicly; stay tuned for that!

@@makethebrainhappy-scientificex Thanks very much for your reply!

Depending on the sequencing prep protocol that you use there will be a range of junction sizes as shown in this graph: www.researchgate.net/figure/Library-insert-size-Libraries-were-constructed-using-the-standard-A-or-reaction-E_fig1_258822778

Like a lot of bioinformatics content the diagram comes from a BIOSTARs thread: www.biostars.org/p/267167/ Enjoy!

The "library sizes" - i.e. the sizes of the different fragments (an article that has some better definitions: thegenomefactory.blogspot.com/2013/08/paired-end-read-confusion-library.html) typically have a distribution that look something like this histogram (www.researchgate.net/figure/Library-insert-size-Libraries-were-constructed-using-the-standard-A-or-reaction-E_fig1_258822778). Once you have mapped the pair-end reads to a reference genome you can figure out the average insert size and standard distribution within your sample (www.biostars.org/p/14339/). This article also has an interesting perspective on the question (www.ncbi.nlm.nih.gov/pmc/articles/PMC3906532/).

@@makethebrainhappy-scientificex Thank You for the fast reply! :D But unfortunately I can't open any of the links you sent me, l receive "Not found" errors like the links are mispelled, I'm sorry... I'll make my own research, anyway ;)

@@michaelbellini3946 Oh my apologies. It looks like the final parenthesis was include in all the links. In order: thegenomefactory.blogspot.com/2013/08/paired-end-read-confusion-library.html www.researchgate.net/figure/Library-insert-size-Libraries-were-constructed-using-the-standard-A-or-reaction-E_fig1_258822778 www.biostars.org/p/14339/ www.ncbi.nlm.nih.gov/pmc/articles/PMC3906532/

@@makethebrainhappy-scientificex Thank You Very much! I have everything clear💪 Molecular Genetics exam coming soon for me hahah

@@michaelbellini3946 Good luck! :-)

Thank you! :-)

There are numerous packages that will perform bulk RNAseq deconvolution with scRNAseq data: academic.oup.com/bib/advance-article/doi/10.1093/bib/bbz166/5699815, journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007510, www.nature.com/articles/s41467-018-08023-x . However all of these require paired scRNAseq and bulkSeq data from the same sample which is quite difficult to find.

Although the question the researchers were trying to answer in that study involved 2x150 vs. 2x100 reads, their protocol utilized the number of cycles as shown in the figure. Please see this link for more information: blog.limbus-medtec.com/should-we-sequence-at-2x150-or-2x100-cycles-16391a78a228

@@makethebrainhappy-scientificex ok... Just trying to understand if that was just a obo

BECAUSE THE standard number of cycles is 150 not 151