What is RPKM in RNA-seq?

Reads Per Kilobase of transcript, per Million mapped reads (RPKM) is a normalized unit of transcript expression. It scales by transcript length to compensate for the fact that most RNA-seq protocols will generate more sequencing reads from longer RNA molecules.

What is FPKM in RNA sequencing?

FPKM stands for fragments per kilobase of exon per million mapped fragments. It is analogous to RPKM and is used specifically in paired-end RNA-seq experiments [17].

How do you calculate FPKM?

Count up the total reads in a sample and divide that number by 1,000,000 – this is our “per million” scaling factor. Divide the read counts by the “per million” scaling factor. This normalizes for sequencing depth, giving you reads per million (RPM) Divide the RPM values by the length of the gene, in kilobases.

What is the difference between TPM and FPKM?

The only difference between RPKM and FPKM is that FPKM takes into account that two reads can map to one fragment (and so it doesn’t count this fragment twice). TPM is very similar to RPKM and FPKM. The only difference is the order of operations.

How many reads for RNA-seq?

Generally, we recommend 5-10 million reads per sample for small genomes (e.g. bacteria) and 20-30 million reads per sample for large genomes (e.g. human, mouse). Medium genomes often depend on the project, but we would generally recommend between 15-20 million reads per sample.

Is FPKM normalized?

The name “FPKM” – fragments per kilobase of exon per million reads – implies that FPKM is a measure of gene expression normalized by exonic length and library size, in contrast to raw counts.

Can you compare TPM between samples?

TPM should never be used for quantitative comparisons across samples when the total RNA contents and its distributions are very different. However, under appropriate circumstances, TPM can be still useful for qualitative comparison such as PCA and clustering analysis.

What is FPKM value?

FPKM stands for Fragments Per Kilobase of transcript per Million mapped reads. In RNA-Seq, the relative expression of a transcript is proportional to the number of cDNA fragments that originate from it.

What TPM means?

Total Productive Maintenance
TPM stands for Total Productive Maintenance. It is a concept that creates a team-based system, which constantly aims to improve equipment effectiveness by focusing on proactive as well as preventative techniques for increasing plant and equipment reliability.

How much RNA do you need for RNA-seq?

The standard protocol for library construction requires between 100 ng and 1 μg of total RNA. There are kits available for ultra-low RNA input that start with as little is 10 pg-10ng of RNA; however, the reproducibility increases considerably when starting with 1-2 ng.

Is RNA-seq better than microarray?

“mRNA-Seq offers improved specificity, so it’s better at detecting transcripts, and specifically isoforms, than microarrays. It’s also more sensitive in detecting differential expression and offers increased dynamic range.”

Why do we normalize RNA-Seq data?

Normalization is an essential step in an RNA-Seq analysis, in which the read count matrix is transformed to allow for meaningful comparisons of counts across samples. Another reason normalization is required is that the proportion of mRNA corresponding to a given gene may change across biological conditions.