New upstream version 7.2.1+dfsg

See ../README for high-level documentation of the entire EIGENSOFT package.

This file contains documentation of EIGENSTRAT programs:

  smartpca.pl: run PCA on input genotype data (calls smartpca)

  smarteigenstrat.pl: run EIGENSTRAT stratification correction.  This program 

  smartpca.perl: run PCA on input genotype data (calls smartpca)

  smarteigenstrat.perl: run EIGENSTRAT stratification correction.  This program 

    supports all 5 file formats, and supports quantitative phenotypes.

  gc.pl: apply Genomic Control (Devlin and Roeder, 1999) to the

  gc.perl: apply Genomic Control (Devlin and Roeder, 1999) to the

    association statistics computed by EIGENSTRAT.

We note that the programs eigenstrat and eigenstratQTL of EIGENSOFT version 2.0

have been replaced by smarteigenstrat.pl.  However, we have retained the old

have been replaced by smarteigenstrat.perl.  However, we have retained the old

programs for backwards compatibility (see below).

See ./example.perl and ./exampleQTL.perl for toy examples using our programs.

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DOCUMENTATION of smartpca.pl program:

DOCUMENTATION of smartpca.perl program:

This program calls the smartpca program (see ../POPGEN/README). 

For this to work, the bin directory containing smartpca MUST be in your path. 

See ./example.perl for a toy example.

../bin/smartpca.pl

../bin/smartpca.perl

-i example.geno  : genotype file in any format (see ../CONVERTF/README)

-a example.snp   : snp file in any format (see ../CONVERTF/README)

-b example.ind   : indiv file in any format (see ../CONVERTF/README)

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DOCUMENTATION of smarteigenstrat.pl program: [run smartpca.pl program first]

DOCUMENTATION of smarteigenstrat.perl program: [run smartpca.perl program first]

This program is a PERL wrapper which calls the C program smarteigenstrat. 

  Note: the bin directory containing smarteigenstrat MUST be in your path. 

  See ./example.perl for a toy example.

We recommend smarteigenstrat.pl for users who prefer command-line flags.

We recommend smarteigenstrat.perl for users who prefer command-line flags.

However, users who prefer parameter files can run smarteigenstrat instead.

../bin/smarteigenstrat.pl

../bin/smarteigenstrat.perl

-i example.geno : genotype file in any format (see ../CONVERTF/README)

-a example.snp : snp file in any format (see ../CONVERTF/README)

-b example.ind : individual file in any format (see ../CONVERTF/README).

  should be real numbers.  The value -100.0 signifies "missing data".

  If -q is set to NO, these values should be "Case" or "Control".

  The default value for the -q parameter is NO.     

-p example.pca : input file of principal components (output of smartpca.pl)

-p example.pca : input file of principal components (output of smartpca.perl)

-k 1 : (Default is 10) number of principal components along which to

  correct for stratification.  Note that l must be less than or equal to

  the number of principal components reported in the file example.pca.

    consider to be appropriate.

-l example.log : standard output file

The running time of smarteigenstrat.pl is very fast compared to

  the running time of smartpca.pl.

The running time of smarteigenstrat.perl is very fast compared to

  the running time of smartpca.perl.

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DOCUMENTATION of smarteigenstrat program:

Users who prefer parameter files to command-line flags can run the

C program smarteigenstrat instead of the PERL wrapper smarteigenstrat.pl.

C program smarteigenstrat instead of the PERL wrapper smarteigenstrat.perl.

The syntax of smarteigenstrat is "../bin/smarteigenstrat -p parfile"

DESCRIPTION OF EACH PARAMETER in parameter file for smarteigenstrat:

numeigs:          number of principal components to correct for

qtmode:           YES for quantitative phenotype, NO (default) otherwise 

For details, see documentation of smarteigenstrat.pl above.

For details, see documentation of smarteigenstrat.perl above.

OPTIONAL PARAMETERS:

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DOCUMENTATION of gc.pl: [run smartpca.pl & smarteigenstrat.pl first]

DOCUMENTATION of gc.perl: [run smartpca.perl & smarteigenstrat.perl first]

../bin/gc.pl infile outfile

../bin/gc.perl infile outfile

infile is input file of chisq statistics produced by eigenstrat program.

  It contains both uncorrected and EIGENSTRAT statistics for each SNP.

outfile is output file.  It lists

A lambda above 1 indicates inflation in chisq statistics.

By definition, lambda is not allowed to be less than 1.

Running time of the gc.pl program is very fast.

Running time of the gc.perl program is very fast.

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which have now been replaced by our new program smarteigenstratQTL.perl.  

See ./example.oldstyle.perl for an example involving the eigenstrat program. 

Most users will want to use our new program smarteigenstrat.pl, which has

Most users will want to use our new program smarteigenstrat.perl, which has

added functionality.  However, users wishing to understand or modify our 

source code may find it advantageous to instead work with the simpler 

eigenstrat programs.

For backwards compatibility with the 07/23/06 EIGENSTRAT release, we have also

included our old program pca used in that release, which has now been replaced

by our new program smartpca.pl.  See ./example.oldstyle.perl for an example

by our new program smartpca.perl.  See ./example.oldstyle.perl for an example

involving the pca program. 

Most users will want to use our new program smartpca.pl, which calls

Most users will want to use our new program smartpca.perl, which calls

the smartpca program and has added functionality.  However, users wishing

to understand or modify our source code may find it advantageous to instead

work with the simpler pca program.

candidate marker from the set of markers used to infer principal components

used to correct for stratification at the candidate marker.  In the case of

a data set which uses ancestry-informative markers to infer ancestry, a

good way to do this is to run smartpca.pl to infer principal components 

good way to do this is to run smartpca.perl to infer principal components 

*only* using ancestry-informative markers, excluding the candidate markers 

(and excluding any ancestry-informative marker in LD with a candidate marker),

and then run eigenstrat on candidate markers.