1. Gene expression estimation from RNA-Seq data
刘学军

2. Outlines Background RPKM Poisson model N-URD model
Improved Poisson model

3. The Cycle of Forward Genetics
Sequencing
Genotype
Observation
Thinking
Phenotype
Hypothesis
Test Hypothesis
By Genetic Manipulation
Gene Deletion/Replacement
Recombinant Technology

4. Central Dogma
DNA
transcription
mRNA
translation
Protein

5. RNA-Seq protocal RNA is isolated from a sample.
RNA is converted to cDNA fragments
High-throughput sequencing
Reads are mapped to a reference genome (counts of reads – ‘digital’)
Gene expression estimation

6. An example reference ACGTCCCC 12 ACGTC reads 8 CGTCC reads
9 GTCCC reads
5 TCCCC reads
This gene can be summarized by a sequence of counts 12, 8, 9, 5.

7. Advantages of RNA-Seq Large dynamic range Low background noise
Requirement of less sample RNA
Ability to detect novel transcripts

8. Challenges of RNA-Seq Sequencing non-uniformity
Read mapping uncertainty
Paired-end sequencing data

9. Sequencing non-uniformity

10. Source of read mapping uncertainty
Paralogous gene family
Low-complexity sequence
Alternatively spliced isoforms of the same genes
Uncertainty in read alignment
gene multireads and isoform multireads

11. Alternatively spliced isoforms

12. Read mapping uncertainty

13. Paired-end sequencing

14. RPKM
Reads per kilobase of the transcript per million mapped reads to the transcriptome
--gene expression level
--isoform expression level?
Mortazavi et al. (2008) Nature Methods.

15. Jiang et al. (2009) Bioinformatics
Notations:
fg,i: the ith isoform of gene g.
lf: isoform length
kf: the number of transcript copies in the isoform
The total length of the transcripts is
The probability of a read comes from some isoform f is
Define as the expression index of isoform f.

16. Model assumption w: the total number of mapped reads
Given a region of length l in f, the number of reads coming from that region,
which can be approximated by

17. Poisson model For a gene with m exons, with lengths
and n isoforms with expressions
Observations
Xs: number of reads mapped to an exon

18. Poisson model For every X, the Possion parameter is
where cij is 1 if isoform i contains exon j and 0 otherwise.
Data likelihood,

19. Wu et al. (2011) Bioinformatics
URD model -> N-URD model
Global bias curve (GBC)
Local bias curve (LBC)

20. Global bias curve

21. Local bias curve

22. Usage of the bias curve

23. The N-URD models GN-URD: cij - > Gij LN-URD: cij -> Lij
MN-URD: cij -> a*Gij +(1-a)*Lij
1-M: no. of iteration for LBC calculation is 1
5-M: no. of iteration for LBC calculation is 5

25. Li et al. (2010) Genome Biology
Use variable rates for different positions.
Poisson linear model,

26. Non-linear model
Use empirical data to obtain the non-linear relationship between sequencing preference (ai) and the surrounding sequences.
Gene expression level with length L,