EricChu:LabNotesMDA/2014-4-16

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Revision as of 21:14, 17 April 2014 by >Ericchu (Created page with "==Fragment Calling Protocol== * R code smooth.discrete in the mhsmm package 1. Open the varbin.50k file in excel. It has 50,000 rows. Column 4 is the read count of that bin. 2...")
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Fragment Calling Protocol

  • R code smooth.discrete in the mhsmm package

1. Open the varbin.50k file in excel. It has 50,000 rows. Column 4 is the read count of that bin. 2. Copy column 4 to a new sheet 3. Use a function to turn (read counts>20 to a value of 2 and otherwise =1). “2” represents the presence of a DNA strand.

=IF(B1>=20,2,1)		

4. Only save the converted values in CSV form. 5. Repeat this for each chamber for analysis. 6. Load the mshmm package to R 7. Input the CSV file in R as a vector

> y8<-c(scan("PGP1#21CoREChamber8.csv", sep=","))
Read 50000 items

8. Make sure the size was right

> str(y8)
num [1:50000] 2 2 1 1 1 1 1 1 1 1 ...

9. Set parameters

> initial=c(1,0)
> P=matrix(c(0.99,0.01,0.01,0.99),nrow=2)   #transition matrix
> B=P   #emission matrix
# The matrices will eventually be trained and then reflect the actual probability.
# as long as the transition matrix was not too far from the reality (>90% chance of no change)

10. Run all vectors through smooth.discrete (HMM) and plot

> obj8=smooth.discrete(y8,init=initial,trans=P,parms.emission=B)
> plot (y8, ylim=c(0.8,2))
> addStates(obj8$s)
# the addStates function will add a colored bar at the bottom of the plot
> plot (y30[2800:300], ylim=c(0.8,2)) #plot a specific region
> plot(y30, ylim=c(0.8,2)) # or plot the entire genome
> addStates(obj30$s[2800:3000]) # add the visualization of this specific region
> addStates(obj30$s) # or add to the entire genome

11. The state is stored in the vector “obj30$s”. It is the predicted states of 1s and 2s in a vector form.


  • Compare Region 165Mbp-169Mbp of Chromosome 4 from the chambers 10,14,22,24 of PGP1#21 CoRE