Discovering microRNAs from deep sequencing data using miRDeep
Lin Min
miRNA
1. Map to genome and discard reads • Map to many loci • Map to rRNA tRNA
Flow Chart
2. Excise sequence from genome using not discarded reads
Flow Chart
3. Predict secondary structure and discard unlikely ones
Flow Chart
Core algorithm
Flow Chart
Features: • Reads signature
Core Algorithm
Find features to distinguish miRNA from noise
Features: • Reads signature • Structural stability
Core Algorithm
Find features to distinguish miRNA from noise
Core algorithm
Features: • Reads signature • Structural stability • 3’ end overhang
Core Algorithm
Find features to distinguish miRNA from noise
Features: • Reads signature • Structural stability • 3’ end overhang • 5’ end conservation
Core Algorithm
Find features to distinguish miRNA from noise
Core algorithm
Features: • Reads signature • Structural stability • 3’ end overhang • 5’ end conservation
Pre/bgr
Naïve Bayesian Model
C. elegans.
116 Passed Cut off 103 previously known 13 new
5 are verified by northern 4 out of them are detected
Results
Human
173 Passed Cut off 163 previously known (28%) 10 new
Results
206 Passed Cut off 3 previously known 203 new
Dog
Results
Thank you
