Came up with a paper on BMC genoics comparing five different somatic snp callers.

GATK UnifiedGenotyper in NaiveSubtract
MuTect1
SomaticSniper from the original paper
Installation help document for Strelka with updated user's guide and a quick start guide
And the original paper on somatic-sniper
VarScan2 from the original paper
Classical samtools method also works.

Calling variants with samtools/bcftools

Help from samtools protocol
Help from samtools/bcftools protocol

Working with Rmarkdown seems quite beneficial, as one can keep good record and Rmarkdown produces html or pdf report.

I need to work with Yicheng on a project on my github. From my existing repository, I need to make a branch and work with him

	
I found out a help post, and I am following it step-by-step
	
git checkout -b Rproj_w_yicheng
	
git checkout Rproj_w_yicheng
        
git remote add ocri3-w-yicheng https://github.com/ImageRecognitionMaster/myOCRI-iii
	
git branch
	
git branch -D Rproj_w_yicheng
	
git push origin :Rproj_w_yicheng

Here is the end results.

Here are a few python doc with high regards.

Official python3 online doc

bcbio-nextgen has the high reputation but it is hard to set up.
Getting Genetics Done by Stephen Turner on WES coverage with bedtools

ggplot manual is available

Goal 1: ggplot without grid — someone has the post
Goal 2: Modify with no legend
Goal 3: Add x/y labels

Goal 4: Plot SNP panels with multiple samples

Do some researching and found this post is very helpful and can be used as the starting point

Goal 5: save a vector figure, .emf

p <- ggplot (someObject)
usage: ggsave ("someFigure.emf", p)

It has been a while, but I need to make sure that EMMA works for Dr. Kleeberger’s project

Understand the population genetics

A hands on tutorial here.

Understand the Mixed model

plink provides many good tools.

Implementation with R — I encountered some hurdles with R programming and would like to document them here before I forget.

If fctr.cols are the names of your factor columns, to convert
them to characters

X[, fctr.cols] <- sapply(X[, fctr.cols], as.character)

distances <- matrix(1:25, nrow=5, ncol=5)
Now, 
apply(distances, c(1, 2), function(x) 0)
distances[] <- 0L
distances*0

Viewing/reporting the results

I found a very useful and handy help doc on Manhattan Plot

A good note on using EMMA

Or, I can get EMMAx from Ed Burk’s GAPIT bundle.
Here FastMap has moved to a new location
Where is snpster??

Fact about EMMA

• Kang,H published EMMA in 2008 on Genetics

• Kang,H extended EMMA to EMMAX

• Zhou, present the EMMA in GEMMA. It seems to be very similar to EMMA without citing EMMA’s work.
• GenABEL seems to quite popular in the community.

FastMap note

I need to take a note on this

Hi Jianying:

I hope you are doing well and having a nice week so far.  I hate to
 bother you with this question, but depending on whether I will have 
the data to do so, I may be running a principal component analysis 
on some past data from the lab.  I need to speak with Dr. Kleeberger
tomorrow morning so that I can clarify some things, but if possible,
would you possibly be available to meet sometime tomorrow afternoon or 
anytime on Friday so that I can discuss the principal component 
analysis?  I just want to be sure I do it correctly and I would feel 
better knowing I had your expertise.  If you do not have the time, 
though, please do not worry and know that I understand .  
Thank you for your consideration, regardless.

Sincerely,
Heather

Well, I found a very good lecture note from PennState on Principal Component Analysis