I completed a differential gene expression analysis and I essentially have close to 3000 genes that pass all filters (adj p-value and log2FC). I want to run some sort of downstream analysis (GSEA or something else) on these genes so I have tried annotating the genes with both biomaRt and org.hs.eg.db. In both cases, the genes that cannot be annotated are described as "novel transcripts" and "pseudogenes", and "antisense". There are about 700/3000 genes that have these descriptions and I am wondering if there is any way to resolve this. Using biomaRt improved the number of genes with annotation but there are still many that cannot be annotated. Should I throw away these genes to make downstream analysis easier? What if I throw away something important? Is this too many genes to throw away? I am stuck because I cannot seem to find a way to recover any more genes with annotation. I am using the correct reference chromosome (GRCh38.p13) and my data is in the form of ensemble ID's so using biomaRt should give me the most annotations, but it does not. Attached is a photo of the description of some of these genes that cannot be annotated. What should I do?
•
written
by
turcoa1 •
1 answer
What should I do?
Experiments to characterize the genes that have unknown functions. You could direct your experimental work for example by clustering the genes and guessing what process(es) they may be involved in by which annotated genes are present in the same cluster.
Log in to answer this question.
-
should I remove the transcripts from annotate peak region in ATAC-seq
written by QX •
-
GSEA vs Functional Annotation
written by turcoa1 •
-
biomaRt not finding all genes
written by danielcgingerich •
-
what should I do first: transciptome annotation or DE analysis?
written by vinicius •
-
Changing distance to TSS (tssRegion in ChIPseeker) during peak annotation in ChIP-seq analysis does…
written by vyazar •
-
ENSEMBL annotation of genes start with "Gm" end with "Rik"
written by SMILE
-
How to perform lncRNA differential gene expression analysis (unstranded)?
written by mmitra •
-
Empty ENSEMBL gene annotations
written by emblake •
-
How to search for conserved Pseudogenes in nematodes?
written by virg4l •
-
hg19.p13 annotation files
written by deepthithomaskannan
It makes no difference I think if you toss or not. Any enrichment analysis is focused on known pathways, and almost all genes in known pathways (such as REACTOME or KEGG) are protein-coding, so you anyway won't get much meaning out of these "exotic" types of genes, such as pseudogenes and antisense. One often simply has no idea what they do.