Hoffman Lab Tech Talk

1. ChIP-seq analytics and
confidence estimation by
CHANCE
Mehran Karimzadeh
A Hoffman lab tech talk

2. What you can do by CHANCE
● Strength of immunoprecipitation: insufficient depths,
PCR bias, batch effects
● Sequence content/quality: biases by sonication,
chemical digestion & library prep
● Cross validation with ChIP-qPCR and public profiles
(ENCODE)

3. Estimating strength of IP enrichment
Signal Extraction Scaling (based on order statistics) to decompose peaks in two
groups: Those pulled by antibody and background.
SES estimates percentage of data enriched for biological signal and a
normalization factor to properly normalize IP and input together.
Based on divergence statistic of thousands of ENCODE experiments, it reports a
pFDR for IP enrichment level that may identify failed experiments.

4. CHANCE workflow

5. Results by CHANCE (I)

6. Results by CHANCE (II)

7. Results by CHANCE (III)

8. Summary
Pros:
● Graphic interface
● Easy to install on windows
● Useful information and comparisons
Cons:
● Only graphic interface
● Written in MATLAB - requires MCR
● Only support mm9, hg18 and hg19

9. Read density module
Uses spectral analysis to identify if
density of reads follows a poisson
distribution according to distance
from TSS