README.qpfstats

qpfstats
--------
         DIR:                 /home/np29/biologyx/v41x/yamdir2/testdir 
          S1:                     qdata1  
         S1X:                     qdata1  
   indivname:                DIR/S1X.ind
     snpname:                 DIR/S1.snp
genotypename:                DIR/S1.geno
 poplistname:                      lista
## must be present.  ne popuation / line.  First population is base
 fstatsoutname:                    fstatsa.txt 
## first line is header.  Must be retained
 allsnps:                          YES 
## default NO  -- dangerous bend
 inbreed:                           NO 
## default NO
 scale:                             NO 
## default YES -- when fstats are scaled to "match" fst in least squares sense 

qpfmv 
-----
 fstatsname:     fstatsa.txt
 popfilename:      f4sslist
## 4 pops / line (as in qpDstat) but f2, f3, f4 can be mixed.  So code A C B C for f3 stat 
     fmvoutname:  fmvq2.out 


New parameters for qpAdm (which should be upwards compatible) 
fstatsname:   <output from qpfstats> 
## if present no need to specify .ind .snp .geno 
numboot:    <# of bootstrap samples + antithetical samples> 
## default 1000 

New parameters for qpWave (which should be upwards compatible) 
fstatsname:   <output from qpfstats> 

New parameters for qpGraph (which should be upwards compatible) 
qpGraph allows to to make qpfstats file 
Example 
1) Make qpfstats  :: ~np29/newadm19/src/jtest1/ww2dir/testdir/qpfs_example/parw2 
D2:          /home/np29/broaddatax/v41  
D1:          D2
S1:           jd1               
indivname:    D1/S1.ind
snpname:      D1/S1.snp 
genotypename: D1/S1.geno
fstatsoutname:  fstatsw2    
allsnps:        YES
## there is an option oldallsnps: YES for compatiblity.  Not recommended. 
loadf3:         YES 
## this is needed to get qpfstats calculated
graphname:       graph1   
diag:           .0001

2) Use qpfstats  
fstatsname:  fstatsw2    
graphname:       graph1   
diag:           .0001

*** qpfstats with allsnps: YES  is a much better way to use all the data than 
the older allsnps mode.   Standard errors are often much reduced and the theory 
is now defensible!

See ./qpfs.pdf for a brief explanation of the theory.