[SOLVED] pacoxph not fit for Chr 3 only.

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ericyin
Posts: 4
Joined: Mon Jul 20, 2015 10:03 am

[SOLVED] pacoxph not fit for Chr 3 only.

Postby ericyin » Mon Jul 20, 2015 10:18 am

Hi,

I am using pacoxph to fit all my chromosomes data to cox ph models, and I run probABEL under linux system (v.0.4.5). I wrote my shell script for all the chromosomes together, and finished the analysis with proper outputs expect chr 3 only? Chr 3 output shows "nan" for beta-esimation and "nan" for se for each SNP... I am not sure what is wrong? Re-run the programme for chr 3 won't solve the problem.

pacoxph -p ProbABEL_pheno_coxph.txt -d Data_3.dose.fvi -i Data_3.mlinfo --out Data_output_3

Please note, I used "ProbABEL_pheno_coxph.txt" for other chromosomes as well.
Data_3.dose.fvi file is transferred by DataABEL, as others, e.g. Data_1.dose.fvi.
Data_3.mlinfo was prepared the same way as others. These files were used to fit a logistic regression model, which returned analysis results with no problem.

Anyone can comment/suggest on this would be appreciate!

BW,
Eric
Last edited by ericyin on Wed Jul 22, 2015 1:25 pm, edited 1 time in total.

lckarssen
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Re: pacoxph not fit for Chr 3 only..

Postby lckarssen » Wed Jul 22, 2015 12:19 pm

That's really strange...
Can you post the screen output you get when running pacoxph on chr 3? Are there any error messages?
-------
Lennart Karssen
PolyOmica
The Netherlands
-------

ericyin
Posts: 4
Joined: Mon Jul 20, 2015 10:03 am

Re: pacoxph not fit for Chr 3 only..

Postby ericyin » Wed Jul 22, 2015 1:24 pm

There is no error message. The output (stdout):

Code: Select all

$ cat stdout
probabel v. 0.4.5
(C) Yurii Aulchenko, Lennart C. Karssen, Maarten Kooyman, Maksim Struchalin, The GenABEL team, EMC Rotterdam

Using EIGEN version 3.2.0 for matrix operations
Options in effect:
         --pheno       = ProbABEL_pheno_coxph.txt
         --info        = Data_3.mlinfo
         --dose        = Data_3.dose.fvi
                     (using FVF data)
         --ntraits     = 2
         --ngpreds     = 1
         --interaction = 0
         --interaction_only = 0
         --mmscore = not in output
         --map     = not in output
         --nids    = estimated from data
         --chrom   = not in output
         --out     = Data_output_3
         --skipd   = 2
         --separat = " "
         --score   = OFF
         --nohead  = OFF
         --allcov  = OFF
         --robust  = OFF

Reading info data...                                                                           72.35%...Number of SNPs = 1966777                                                                       72.66%...Reading phenotype data...
Actual number of people in phenofile = 1357; using all of these
Coxph model: ( Days_FU1 , primary_endpoint ) ~ mu + age + BMI + SNP_A1
Reading genotype data... done.
 loaded null data... estimated null model... formed regression object...
Analysis: 100.00%... done                                                                      100.00%... done



Code: Select all

$more Data_output_3_add.out.txt
name A1 A2 Freq1 MAF Quality Rsq n Mean_predictor_allele beta_SNP_add sebeta_SNP_add chi2_SNP
rs150901214 C T 1 0 1 0.9 1274 0 nan nan nan
rs183712112 C T 1 0 1 0.9 1274 0 nan nan nan
rs35142429 G A 0.984067 0.015933 0.90583 0.9 1274 0 nan nan nan
rs142928618 G A 1 0 1 0.9 1274 0 nan nan nan
rs150873824 T C 1 0 0.0043962 0.9 1274 0 nan nan nan
rs143031574 T C 1 0 1 0.9 1274 0 nan nan nan
rs114130114 C T 0.987218 0.012782 0.79662 0.9 1274 0 nan nan nan
rs146124268 C T 1 0 0.0037347 0.9 1274 0 nan nan nan
rs199799888 CCTGG C 0.991162 0.0088382 0.99823 0.9 1274 0 nan nan nan
rs149690339 G A 1 0 1 0.9 1274 0 nan nan nan
rs145537857 G T 1 0 1 0.9 1274 0 nan nan nan
rs148396999 T C 0.969868 0.030132 0.95173 0.9 1274 0 nan nan nan
rs116611036 G C 1 0 0.030021 0.9 1274 0 nan nan nan
rs147632070 T C 0.995208 0.0047917 0.62723 0.9 1274 0 nan nan nan
rs1401928 C T 0.50565 0.49435 0.99638 0.9 1274 0 nan nan nan
rs145909339 G A 1 0 1 0.9 1274 0 nan nan nan
rs114688427 T C 0.999463 0.00053651 0.21126 0.9 1274 0 nan nan nan
rs113879143 T A 0.999754 0.00024635 0.11576 0.9 1274 0 nan nan nan
rs72863194 G A 0.999255 0.00074481 0.19507 0.9 1274 0 nan nan nan
rs140337609 C T 0.999232 0.00076787 0.999 0.9 1274 0 nan nan nan
rs150217664 T A 0.999754 0.00024635 0.11576 0.9 1274 0 nan nan nan
rs117227960 G A 1 0 1 0.9 1274 0 nan nan nan
rs149341934 T C 0.999655 0.0003455 0.44849 0.9 1274 0 nan nan nan
rs189472885 G T 1 0 0.0075946 0.9 1274 0 nan nan nan
rs145651404 G T 1 0 0.0049981 0.9 1274 0 nan nan nan
rs143072238 T A 0.986307 0.013693 0.67013 0.9 1274 0 nan nan nan
rs181458739 T A 0.999614 0.00038586 0.48476 0.9 1274 0 nan nan nan
rs6764811 A C 0.50562 0.49438 0.99648 0.9 1274 0 nan nan nan
rs114649570 G A 0.998067 0.0019331 0.44331 0.9 1274 0 nan nan nan
rs141536498 C T 0.995209 0.0047913 0.62722 0.9 1274 0 nan nan nan
rs7645399 C G 0.996922 0.0030784 0.89604 0.9 1274 0 nan nan nan
rs17030573 C A 0.998036 0.0019635 0.27252 0.9 1274 0 nan nan nan
rs147140531 G A 1 0 1 0.9 1274 0 nan nan nan
rs77450516 G A 0.999229 0.00077056 0.99552 0.9 1274 0 nan nan nan
rs144504278 C T 0.998429 0.0015707 0.73966 0.9 1274 0 nan nan nan
rs73085655 A G 0.987523 0.012477 0.95651 0.9 1274 0 nan nan nan
rs147861896 G A 0.990721 0.0092795 0.7018 0.9 1274 0 nan nan nan
rs148873320 G T 0.992611 0.0073885 0.70004 0.9 1274 0 nan nan nan
rs60122785 C T 0.93715 0.06285 0.80568 0.9 1274 0 nan nan nan
rs115670776 C A 1 0 0.020193 0.9 1274 0 nan nan nan
rs142626062 C T 0.991054 0.0089458 0.98663 0.9 1274 0 nan nan nan
rs151267533 T C 1 0 0.0065295 0.9 1274 0 nan nan nan
rs140501043 A G 1 0 1 0.9 1274 0 nan nan nan
rs145618173 G A 1 0 1 0.9 1274 0 nan nan nan
rs116102556 C T 0.998066 0.0019335 0.4434 0.9 1274 0 nan nan nan
rs78191219 T C 0.999832 0.00016756 0.010674 0.9 1274 0 nan nan nan
rs138205075 T C 0.991493 0.0085069 0.62643 0.9 1274 0 nan nan nan
rs9835356 C G 0.50565 0.49435 0.99637 0.9 1274 0 nan nan nan
rs9839155 C T 0.50565 0.49435 0.99637 0.9 1274 0 nan nan nan
rs145150847 A T 0.997893 0.0021068 0.44643 0.9 1274 0 nan nan nan
rs190360434 C T 1 0 0.19698 0.9 1274 0 nan nan nan
rs1467255 C T 0.50565 0.49435 0.99637 0.9 1274 0 nan nan nan
rs138966251 G A 1 0 1 0.9 1274 0 nan nan nan
......

lckarssen
Site Admin
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Posts: 321
Joined: Tue Jan 04, 2011 3:04 pm
Location: Utrecht, The Netherlands

Re: pacoxph not fit for Chr 3 only..

Postby lckarssen » Wed Jul 22, 2015 3:39 pm

Strange that logistic regression did give proper output. Can you post the same few lines from that output?

I see some strange things in the output you posted: Mean_predictor_allele column contains only 0s. I assume that column is non-zero in the logistic regression output. This is likely linked to the fact that Freq1 contains only 1 and MAF only 0s again, this means that the data is monomorphic for all SNPs. Is that really true? Is the info file correct?
-------
Lennart Karssen
PolyOmica
The Netherlands
-------

ericyin
Posts: 4
Joined: Mon Jul 20, 2015 10:03 am

Re: pacoxph not fit for Chr 3 only..

Postby ericyin » Tue Sep 22, 2015 4:45 pm

Hello.

I finally sorted it out. It turns out there is nothing wrong with the Programme, nothing wrong with the Code. It is the memory size! I submitted the same job to different but larger and faster computers and it finished the job with no errors! glad to share this with folker using GenABEL and ProbABEL. We need to make sure the computers have large enough memory size especially using GenABEL to convert the data format..

I run the computing jobs in our university clusters, and they did lots of upgrades. That is why Chr 3 job was interrupted I guess.

lckarssen
Site Admin
Site Admin
Posts: 321
Joined: Tue Jan 04, 2011 3:04 pm
Location: Utrecht, The Netherlands

Re: pacoxph not fit for Chr 3 only..

Postby lckarssen » Sat Sep 26, 2015 2:01 pm

That is great news! Thank you for reporting back to us.

Marking this thread as SOLVED.
-------
Lennart Karssen
PolyOmica
The Netherlands
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