Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

ERROR mu * T is too small #1

Open
dynamiskduo opened this issue Mar 2, 2021 · 7 comments
Open

ERROR mu * T is too small #1

dynamiskduo opened this issue Mar 2, 2021 · 7 comments

Comments

@dynamiskduo
Copy link

Hello,
thank you for writing ProPIP, it sounds super cool!
I am trying to use it on a fasta file with ~130 sequences and ~4000 characters as well as the correspondring tree.

When I start the run, it crashes after 2 %. The info file gives me this information

I20210302 11:53:56.959744 36695 main.cpp:837] [PIP model] Fixed PIP parameters to (lambda=15.8,mu=0.06,I=0.948)
I20210302 11:53:56.959820 36695 main.cpp:893] [Substitution model] Number of states: 5
I20210302 11:53:56.960119 36695 main.cpp:920] model=JC69+PIP(lambda=15.800000000000,mu=0.060000000000)
I20210302 11:53:56.960417 36695 main.cpp:968] [Alignment sequences] Starting MSA_t inference using Pro-PIP...
W20210302 11:53:56.962633 36695 progressivePIP.cpp:287] ERROR mu * T is too small: Success [0]
W20210302 11:53:56.962633 36695 progressivePIP.cpp:287] ERROR mu * T is too small: Success [0]
W20210302 11:53:56.962633 36695 progressivePIP.cpp:287] ERROR mu * T is too small: Success [0]
...
W20210302 11:53:56.962633 36695 progressivePIP.cpp:287] ERROR mu * T is too small: Success [0]

Do you know what causes this? Or do you have any ideas on how to work around it?
I am not experienced in C++ so I am having a hard time trying to debug it, and any help is greatly appreciated.

Best,
Amanda

@supermax1234
Copy link
Contributor

Dear Amanda,
this error was generated when the tool calculates the beta(v) probability for a given node v.
The reason for the error is that the product of mu by the branch length is below a given threshold (1e-8). Most likely there is a branch length very close to zero.

Best,
Max

@dynamiskduo
Copy link
Author

dynamiskduo commented Mar 6, 2021

Dear Max,
thank you for your speedy reply :)
Based on your advice, I pruned my tree while maximizing tree length and managed to avoid that error. Yay!
However, the run still crashes after 15 %, but this time I do not get any warnings.

The screen output is:

[Computing the multi-sequence alignment]
Aligner optimised for:.................: ram
Stochastic backtracking active.........: no
[>>>>>>                                ]  15%Killed

and the log.INFO says:

Log file created at: 2021/03/06 15:18:54
Running on machine: g-03-c0181
Running duration (h:mm:ss): 0:00:00
Log line format: [IWEF]yyyymmdd hh:mm:ss.uuuuuu threadid file:line] msg
I20210306 15:18:54.041993 12366 main.cpp:265] alphabet:  DNA | gap-extention 1

Any advice here?
Have a nice day,
best,
Amanda

@supermax1234
Copy link
Contributor

Hi Amanda,
this time I would try monitoring your RAM usage to check if you have enough.
Best,

M

@dynamiskduo
Copy link
Author

Hello again :)
Hmmm, I am running on a cluster and allocate 120GB to analyse my pruned alignment w. 10 seqs.
Is it expected to exceed that?
Best,
Amanda

@supermax1234
Copy link
Contributor

supermax1234 commented Mar 9, 2021 via email

@dynamiskduo
Copy link
Author

Dear Max,
thank you for your advice.
Unfortunately, it still crashes after 15 %:
[Computing the multi-sequence alignment] Aligner optimised for:.................: cpu Stochastic backtracking active.........: no [>>>>>> ] 15%
And the error file says:
*** Aborted at 1615283771 (unix time) try "date -d @1615283771" if you are using GNU date *** PC: @ 0x0 (unknown) *** SIGSEGV (@0x8) received by PID 23409 (TID 0x7ffff69c3600) from PID 8; stack trace: *** @ 0x7ffff47c5630 (unknown) @ 0x43da33 bpp::nodeCPU::DP3D_PIP_node() @ 0x454b1d bpp::CompositePIPnode::PIPnodeAlign() @ 0x44dcdb main @ 0x7ffff32e2555 __libc_start_main @ 0x45237f (unknown) /var/spool/torque/mom_priv/jobs/31087676.SC: line 28: 23409 Segmentation fault (core dumped) ProPIP params=indel_aware.txt
I don't know if the two systems are just incompatible or something..

@supermax1234
Copy link
Contributor

supermax1234 commented Mar 9, 2021 via email

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants