Download Estimation of alternative splicing isoform frequencies from RNA

Estimation of alternative
splicing isoform frequencies
from RNA-Seq data
Ion Mandoiu
Computer Science and Engineering Department
University of Connecticut
Joint work with Marius Nicolae, Serghei Mangul, and Alex Zelikovsky
Outline
•
•
•
•
Introduction
EM Algorithm
Results
Conclusions and future work
Alternative Splicing
[Nilsen & Graveley 10]
RNA-Seq
Make cDNA & shatter into fragments
Sequence fragment ends
Map reads
A
Gene Expression (GE)
B
C
D
Isoform Discovery (ID)
A
B
A
C
D
E
C
E
Isoform Expression (IE)
Gene Expression Challenges
• Read ambiguity (multireads)
A
B
C
• What is the gene length?
D
E
Previous approaches to GE
• Ignore multireads
• [Mortazavi et al. 08]
– Fractionally allocate multireads based on unique read
estimates
• [Pasaniuc et al. 10]
– EM algorithm for solving ambiguities
• Gene length: sum of lengths of exons that appear
in at least one isoform
 Underestimates expression levels for genes with 2 or
more isoforms [Trapnell et al. 10]
Read Ambiguity in IE
A
A
B
C
C
D
E
Previous approaches to IE
• [Jiang&Wong 09]
– Poisson model, single reads only
• [Li et al.10]
– EM Algorithm, single reads only
• [Feng et al. 10]
– Convex quadratic program, pairs used only for ID
• [Trapnell et al. 10]
– Extends Jiang’s model to paired reads
– Fragment length distribution
Our contribution
• EM Algorithm for IE
– Single and paired reads
– Fragment length distribution
– Strand information
– Base quality scores
Read-Isoform Compatibility
wr ,i
wr ,i   OaQa Fa
a
Fragment length distribution
• Paired reads
A
B
A
C
C
• Single reads
A
B
A
C
C
IsoEM algorithm
E-step
M-step
Experimental setup
25000
100000
20000
10000
Number of genes
Number of isoforms
• Human genome UCSC known isoforms
15000
10000
5000
1000
100
0
10
1
10
100
1000
10000
100000
0
5
Isoform length
10 15 20 25 30 35 40 45 50 55
Number of isoforms
• GNFAtlas2 gene expression levels
– Uniform/geometric expression of gene isoforms
• Normally distributed fragment lengths
– Mean 250, std. dev. 25
Accuracy measures
• Error Fraction (EF)
– Percentage of isoforms (or genes) with relative
error larger than given threshold t
• Median Percent Error (MPE)
– Threshold t for which EF is 50%
• r2
Isoform Error Fraction Curves
• 30M single reads of length 25
100
Uniq
Rescue
RSEM
IsoEM
UniqLN
% of isoforms over threshold
90
80
70
60
50
40
30
20
10
0
0
0.2
0.4
0.6
Relative error threshold
0.8
1
Gene Error Fraction Curves
• 30M single reads of length 25
100
90
Uniq
Rescue
GeneEM
RSEM
% of genes over threshold
80
70
60
IsoEM
50
40
30
20
10
0
0
0.2
0.4
0.6
Relative error threshold
0.8
1
Read Length Effect
• Fixed sequencing throughput (750Mb)
0.978
25
0.976
20
Median Percent Error
0.974
r2
0.972
0.97
0.968
0.966
Paired reads
0.964
Single reads
15
10
5
Paired reads
Single reads
0.962
0
25
35
45
55
65
Read length
75
85
95
25
35
45
55
65
Read length
75
85
95
Effect of Pairs & Strand Information
• 1-60M 75bp reads
0.985
0.98
0.975
r2
0.97
RandomStrand-Pairs-PerfectMapping
0.965
RandomStrand-Pairs
0.96
CodingStrand-pairs
0.955
RandomStrand-Single
0.95
CodingStrand-single
0.945
0
10000000
20000000
30000000
40000000
50000000
# reads
• [Trapnell et al. 10] r2=.95 for 13M PE reads
60000000
Conclusions & Future Work
• Presented EM algorithm for estimating
isoform/gene expression levels
– Integrates fragment length distribution, base qualities,
pair and strand info
– http://dna.engr.uconn.edu/software/IsoEM/
• Ongoing work
–
–
–
–
Confidence intervals
Allelic specific expression
Integration with isoform discovery
Reconstruction & frequency estimation for virus
quasispecies
Acknowledgments

NSF awards IIS-0546457, IIS-0916401, and IIS-0916948