2 answers
I think the most appropriate method is to analyse the data just like you would for all RNA-seq, and filter out the lncRNAs after you get the differentially expressed genes from the full analysis. Preselecting genes will only bias your results.
I'd think the default UCSC/Ensembl annotation will contain already a bunch of lncRNAs, you could complement these if you like with e.g. Lncipedia data.
moreover, do you have R code for the filtering step?
That's quite basic R, see for example here
Ensembl Biomart allows you to download what you need.
First: select what is needed e.g. Dataset: Ensembl 89 + then choose species --> Filter: gene type --> lincRNA --> Attributes: Gene ID, Gene Name, Gene Type
Second: Click "results"
Third: Export all results to TSV --> Go
During RNA-seq data analysis, reads may get aligned to different types of transcripts including mRNA, lncRNA, miRnA etc. However, there may be some artifacts in these alignments. For example, ncRNA should not exist in polyA enrich samples. How do we identify these false mappings? Or is it just based on empirical knowledge?
LncRNAs are often polyadenylated.
Check this post for workflow
A: Any One please provide protocol for Analysing long noncoding RNA illumina NGS da
Ad for R Differential Expression steps in R,
Log in to answer this question.
-
lncRNA differential expression analysis
written by seta
-
How to analyze scRNA-seq data to compare lncRNA and mRNA
written by Kedu •
-
Conversion RPKM in counts using R
written by Eisuan •
-
How to perform lncRNA differential gene expression analysis (unstranded)?
written by mmitra •
-
nearby genes expression
written by ta_awwad
-
convert Ensemble format wig to UCSC format
written by ta_awwad
-
vennDigram for multiple RNA-seq data
written by ta_awwad
-
Enrichment Analysis from DESeq2 data
written by gkuffel22 •
-
ChIp-seq RNA-seq overlap
written by Federico •
-
Rna-Seq pipeline in R
written by ta_awwad
