Athurva Gore: Difference between revisions
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**Hopefully find a good way to fit normal distributions to the data; create some plots for this | **Hopefully find a good way to fit normal distributions to the data; create some plots for this | ||
**Test CES22k set for proximal and distal bases as well (just as with Dr. Li's data and Cosmic set above) | **Test CES22k set for proximal and distal bases as well (just as with Dr. Li's data and Cosmic set above) | ||
*''' | *'''Analysis of Cosmic and CES22k Data Set''' | ||
*''' | **R^2 value of fit is very low due to large number of data points. | ||
**Idea from Dr. Zhang; check high and low end points for input factors (maybe outside 1 std. deviation?) | |||
***This might increase Signal-to-Noise ratio for the data. | |||
*'''Proximal and Distal Arm Base Comparison''' | |||
**The above analysis (using makeHist.pl) was repeated for the CES22k set. The results are below. | |||
*'''Slides to illustrate findings so far''' | *'''Slides to illustrate findings so far''' |
Revision as of 19:28, 29 August 2008
Lab Rotation
- Will add daily entries once schedule settles down a bit.
August 4th - August 10th
- Received CpG island probe code from Dr. Zhang.
- Need to make modifications discussed in meeting:
- Necessary modifications:
- Remove bisulfite conversion function - DONE
- Create dummy function that simply does not do a replacement, but creates fwd and rev strands
- Commented code to find/replace
- Question: parts we are looking at; do they have N's in them? Probably shouldn't.
- Remove CG score penalty - DONE
- in function getProbeList
- remove section starting with "my $CG_penalty"
- set CG_penalty as always zero for quick fix, remove CG finding code later
- Add function to check sequence uniqueness in human genome (build hash table ahead of time, check Dr. Zhang's functions)
- Looks like function oligoFreq does this; currently just uses log of each side
- Modify probe score calculation to favor segment B being more unique
- See function getProbeList
- Modify score calculation so that Tm of segment A should be high and Tm of segment B should be low
- At the moment, Tm score is used in p_score calculation
- Simply modify to adjust so that A has high Tm, B has low Tm
- See function getProbeList
- Specific thresholds?
- Exon database
- Ask about our current UCSC data; it comes in format on PGP server, or is this modified?
- Found Exon-Intron Database; uses GenBank
- Show Dr. Zhang the readme
- Remove bisulfite conversion function - DONE
August 11th - August 17th
- Will copy from notebook
August 18th - August 24th
- Will copy from Notebook
August 27th
- Have code to read and analyze Cosmic set data; file is "readCosmic.pl"
- Comparison of Cosmic set data to Dr. Li's data (Harvard Collaborator)
- Dr. Li's data showed that the last base pair of the ligation arm was important.
- Dr. Li checked average expression for each base.
- G was preferred for ligation, followed by A, C, and T.
- File:08 22 2008 JinLi Ligation Arm Base Dist.png
- Average expression was calculated using the "makeHist.pl" file.
- This file averages the abundance of the probes that used each base.
- The results were slightly different.
- For the COSMIC set, it was found that for the proximal ligation arm, G was preferred, followed by C, A, and T.
- This makes intuitive sense, as the bond between G and C is stronger than the bond between A and T.
- The results were also much less pronounced than Dr. Li's results; the difference in base performance is much smaller.
- Dr. Li's data showed that the last base pair of the ligation arm was important.
Cosmic Set Results | ||||||||||||||||||||
Base: | A | T | G | C | ||||||||||||||||
Proximal Extension Arm: | 98.2276826484018 | 105.4814504701790 | 97.8751164168995 | 105.1120477176380 | ||||||||||||||||
Distal Extension Arm: | 104.9745183977170 | 107.4126226040130 | 106.5526921141540 | 88.8525735059634 | ||||||||||||||||
Proximal Ligation Arm: | 95.1374247734938 | 83.7531848897751 | 135.360909000299 | 107.876484056988 | ||||||||||||||||
Distal Ligation Arm: | 103.1547820103830 | 113.0664396095970 | 96.5690024678530 | 96.7110820814283 |
- File:Proximal Ligation Base.png
- Analyze these results later; perhaps add in a preference on the Proximal Ligation Arm to favor G or C over A or T in the score.
- Implementation of new probe set algorithm.
- Algorithm is summarized above.
- Implement in Perl using hash table in getCpGIslands.pl file.
- Use R to analyze Cosmic Data Set
- Downloaded and installed GNU R and R-commander (GUI)
- Can load CSV and tab-separated files.
- lm command can do a linear model fit to the data.
- May need to take the log of several pieces of data however in order to improve fit (if data is exponentially correlated).
- Initial lm results for Cosmic set show a very poor correlation...probably need to take log of several pieces of data set.
- Earlier, Dr. Zhang's analysis on CES22K set used the following factors:
- ProbeDist: distribution of oligo abundance determined by Solexa sequencing. - Don't have this for the Cosmic set
- H1_Tm, H2_Tm: H1 (ligation arm), H2 (extension arm), 12bp sub-sequences of H1 and H2. - Normalized for the Cosmic set; very close to 62 C in all cases
- H1R_dist, H2L_dist: K-mer distribution of H1&H2 12bp sub-sequences in the human genome. - Have this
- Core_25bp_genomic_homology: weighted score of the 25bp homologous sequences in the human genome, mapped by SOAP with <=3bp mismatches. - Not sure what this is...ask Dr. Zhang
- Downloaded and installed GNU R and R-commander (GUI)
August 28th
- TO DO TODAY:
- Take log of various factors in R, see if this affects lm results.
- See if any other combinations of factors produce better fits in R.
- Implement algorithm to select probes in Perl.
- R Analysis of Cosmic Data Set
- Tried taking the log of all factors aside from Tm, checked fit.
- Fit is still not very good
- Very low R^2 value
- Checked by plotting in Octave; fit does not match up to data well at all.
- Perhaps a different, non-linear, non-logarithmic model is needed?
- One issue with the Cosmic Data Set is that there is no data for oligonucleotide bias on the chip.
- Agilent's chips have some inherent bias in what molecules are present and not present.
- This bias was measured for the CES22k set that Dr. Zhang worked on but not for the Cosmic set.
- This may be causing issues with fitting a curve to the Cosmic set, as this bias cannot be used in the fit.
- Came up with some ideas while working from home.
- Perhaps instead of log or linear fit, use a normal distribution type fit?
- Could fit a normal distribution to each factor and try and standardize it; this might result in a better overall fit.
- I am currently looking into how to easily do this in R or Octave; shouldn't be too hard to do a fit this way.
- Received data for CES22K set
- A preliminary look at the data in Octave makes it seem that R^2 values will remain very low.
- Confirmed that fit is not that great in Octave.
- However, data for bias is present; this means that this can be factored into the analysis.
- Work on this tomorrow.
August 29th
- TO DO TODAY:
- Make some slides for Cosmic and CES22k sets to illustrate findings for linear and log fits
- Hopefully find a good way to fit normal distributions to the data; create some plots for this
- Test CES22k set for proximal and distal bases as well (just as with Dr. Li's data and Cosmic set above)
- Analysis of Cosmic and CES22k Data Set
- R^2 value of fit is very low due to large number of data points.
- Idea from Dr. Zhang; check high and low end points for input factors (maybe outside 1 std. deviation?)
- This might increase Signal-to-Noise ratio for the data.
- Proximal and Distal Arm Base Comparison
- The above analysis (using makeHist.pl) was repeated for the CES22k set. The results are below.
- Slides to illustrate findings so far