What is FPKM in RNA-seq?
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 is a good number of reads for RNA-seq?
The number of reads required depends upon the genome size, the number of known genes, and transcripts. 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).
What is the difference between RPKM 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.
What is a good read depth?
In fact, this will depend on the purpose of the experiment and type of sample used, but as a very rough generalization an average read depth of about 20 is considered adequate for human genomes.
How do you convert RPKM to FPKM?
In case of single end data, RPKM=FPKM ( R eads p er k ilobase per m illion reads and F ragments p er k ilobase per m illion reads). In case of paired end data, you have for every read-pair one fragment. Thus, divide the RPKM by two.
How do you calculate fold change from FPKM?
First, you have to divide the FPKM of the second value (of the second group) on the FPKM of the first value to get the Fold Change (FC). then, put the equation in Excel =Log(FC, 2) to get the log2 fold change value from FPKM value.
How do you convert FPKM to counts?
One way to convert FPKM values is to multiply the FPKM values with transcript length and the number of reads mapped in million. Trascript length can be obtained using HTSeq. I can’t understand why it is not valid to convert FPKM values into counts and use edgeR or DESeq to test for differential expression.