Advance negative data generation RNAs not involve in a interaction

[teresa-m]

Idea is to:

• filter data for RNAs that are higly expressed but not involved in an interaction
  • Use mRNA-Seq data produced in same conditions highly expressed RNAs
  • Find expression cutoff for the RNAs
  • Create DB of RNAs involved in RRIs (position, ID, or Biotype)
  • filter so we end up with list or RNAs not involved in RRIs
• RNAs not haveig a RRI find the protein binding profiles
• extract potetioal binding sides by ignoring postions that are bound by proteins.
• check that they have the same binding profile?

The bining profile can be found her for human: https://doi.org/10.1016/j.molcel.2012.05.021

[teresa-m]

Ideas from Rolf. Not sure if I summarized it corretly?

[teresa-m]

https://dorina.mdc-berlin.de/regulators -> get CLIP data from here or from Dominik

[teresa-m]

paper: RBP coverage: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE38355 mRNA-Seq: https://www.ncbi.nlm.nih.gov/gds?LinkName=biosample_gds&from_uid=997837 ... maybe better total RNA-Seq to also get ncRNAs

[teresa-m]

Downloade Data: full mRNAseq: Run	Assay Type	AvgSpotLen	Bases	BioProject	BioSample	Bytes	Center Name	Consent	DATASTORE filetype	DATASTORE provider	DATASTORE region	Experiment	GEO_Accession (exp)	Instrument	Library Name	LibraryLayout	LibrarySelection	LibrarySource	Organism	Platform	purification	ReleaseDate	Sample Name	source_name	SRA	Study	Treatment
SRR500121	RNA-Seq	36	1368141804	PRJNA167851	SAMN00997837	847624134	GEO	public	"sra fastq"	"gs s3 ncbi"	"gs.US s3.us-east-1 ncbi.public"	SRX149162	GSM936076	Illumina Genome Analyzer II	GSM936076: RNAseq_mRNA	SINGLE	cDNA	TRANSCRIPTOMIC	Homo sapiens	ILLUMINA	oligo(dT)	2012-06-06T00:00:00Z	GSM936076	HEK293 cell culture	SRP013463	no treatment (mRNA)

[teresa-m]

Next steps will be to gerate the following position files:

1. expresse positions of mRNA: take total mRNAs -> aligne using RNAstar (build in genome+ gtf of PARIS analysis) -> Blockbuster (find positions of reads over TH) -> end up with list of genomic positions
2. list mRNA interaction postions
3. list of protein profiling positions

Generate potenetal negative mRNA binding sides by filter out all positions of 2 and 3 in one

Next step: How to generate the negative RRIs?

[teresa-m]

Task on how to construct the data set are written here: Generate trainings data using context #25