Normalization strategies for comparing mapped reads across samples in RNA-seq
Hi,
I have RNA-seq data from various samples under different conditions, and I'm interested in examining the mapping rate within the centromere and other regions. My plan is to map my reads to the T2T genome using STAR and then extract the centromere region using Bedtools.
However, I'm uncertain about the next steps. Is there a normalization method for mapped reads that allows for comparison between samples? TPM seems like a good method, but it may not be suitable here because it requires gene/transcript length.
Do you have any suggestions?
0 answers
No answers yet.
Log in to answer this question.
More posts like this
-
is there any way to normalize the counts and compare it for the splicing quantification?
written by PK •
-
Off-target % for whole-exome sequencing panel
written by bompipi95 •
-
Blog: How to choose Normalization methods (TPM/RPKM/FPKM) for mRNA expression
written by Novogene •
-
Differential expression tool that can take TPM as input?
written by Tye Kahn •
-
Metric to use for RNAseq expression matrix
written by Ram
-
Comparing gene expression of specific genes between samples in DESeq2 / R
written by masicioglu •
-
Question about normalization and differential expression analysis
written by kamel •
-
Best-suited unit of expression to perform between-sample comparison
written by leaodel
-
GWAS studies with RADSeq
written by Picasa
-
Within-sample comparison of TMM normalized values?
written by Ekarl2
Also because TPM cannot be compared across samples. It's a relative within-sample measure.