Hi Group,

I have QTDT association analysis output for around 900,000 SNP's which
look like this:

QTDT - Quantitative TDT 2.6.1
(c) 1998-2007 Goncalo Abecasis (gonc...@umich.edu)

This program implements tests described by
Abecasis et al, Am J Hum Genet 66:279-292 (2000)
Abecasis et al, Eur J Hum Genet 8:545-551 (2000)
and others

The following parameters are in effect:
           QTDT Data File : qtdt_coga3587_chr22.dat (-dname)
       QTDT Pedigree File : qtdt_coga3587_chr22.ped (-pname)
     QTDT IBD Status File :             qtdt.ibd (-iname)
       Missing Value Code :                    X (-xname)
               Covariates :       USER SPECIFIED (-c{p|s|u|-})
        Association Model :                TOTAL (-a[a|d|f|m|o|p|r|t|
w|-])
     Full Model Variances :         NOT MODELLED (-v{e|c|g|n|t|a|d|-})
     Null Model Variances :           NON SHARED (-w{e|c|g|n|t|a|d|-})
                          &            POLYGENIC
 Parent of Origin Effects :        PATERNAL TEST (-o[f|t|m|p|-])
 Monte-Carlo Permutations :                    0 (-m9999)
              Random Seed :               123456 (-r9999)
        Numeric Minimizer :      NELDER AND MEAD (-n[f|n|p])
     Transmission Scoring :                 NONE (-t[n|p])

Additional Options
 --dominance, --snp [ON], --multi-allelic, --deviates, --references,
 --exclude-founder-phenotypes, --p-values [ON], --no-regress-tbl [ON]

Online documentation http://www.sph.umich.edu/csg/abecasis/QTDT
Comments, bugs: gonc...@umich.edu
Online documentation http://www.sph.umich.edu/csg/abecasis/QTDT
Comments, bugs: gonc...@umich.edu

The following models will be evaluated...
  NULL MODEL
     Means = Mu + sex + Age_at_Interview + age_square
 Variances = Ve + Vg

  FULL MODEL
     Means = Mu + sex + Age_at_Interview + age_square + Xpat
 Variances = Ve + Vg

Testing trait:                       loge_max
=============================================

Testing marker:                     rs1004236
---------------------------------------------

 Allele   df(0) -LnLk(0)   df(X) -LnLk(X)   ChiSq       p
      G    1121  1274.53    1120  1274.53    0.00  0.9514  (1127
probands)

Testing marker:                     rs1062731
---------------------------------------------

 Allele   df(0) -LnLk(0)   df(X) -LnLk(X)   ChiSq       p
      G    1090  1231.86    1089  1231.77    0.17  0.6826  (1096
probands)

Testing marker:                    rs11090516
---------------------------------------------

 Allele   df(0) -LnLk(0)   df(X) -LnLk(X)   ChiSq       p
      C    1087  1230.05    1086  1230.03    0.04  0.8322  (1093
probands)

And so on for each SNP. I want to change this output in tabular form
which may look like this

SNP   Allele   df(0) -LnLk(0)   df(X) -LnLk(X)   ChiSq       p     n
rs1004236   G    1121  1274.53    1120  1274.53    0.00  0.9514  1127
rs1062731  G    1090  1231.86    1089  1231.77    0.17  0.6826  1096

It would be great if someone can help me with script.

Thanks,

Manav

Hi,
I have compiled these sets of commands which do the needful. It would
be great if someone can suggest something with perl or python. As I am
not programmer so my solution is very rough.

#!/bin/sh
awk 'FNR>43' input | \
sed 's/Testing marker:                 *//g' | \
sed 's/---------------------------------------------//g' | \
sed 's/ Allele   df(0) -LnLk(0)   df(X) -LnLk(X)   ChiSq       p//g' |
\
sed 's/probands)/@/g' | \
tr '\n\n\n' ' ' | \
tr '@' '\n' | \
sed 's/  */ /g' | \
sed 's/(//g' | less | \
sed 's/ rs/rs/g' > output
rm input

output file now look like this
rs1004236 G 1121 1274.53 1120 1274.53 0.00 0.9514 1127
rs1062731 G 1090 1231.86 1089 1231.77 0.17 0.6826 1096
rs11090516 C 1087 1230.05 1086 1230.03 0.04 0.8322 1093
rs12106650 C 920 1062.99 919 1062.34 1.29 0.2552 926
rs12170011 G 896 1064.84 895 1063.89 1.89 0.1687 902
rs12330067 A 876 999.93 875 999.85 0.16 0.6901 882
rs13054858 C 995 1142.50 994 1142.20 0.59 0.4432 1001

Manav

On Apr 18, 11:53 am, mannu <kapoor.ma...@gmail.com> wrote: