HMS, motif finding tool for ChIP-Seq

[wjyzidane]

I'm also getting 'Segmentation fault', any ideas ?

all the files in HMS_source_code should be in the same fold as the executable file.

[Retr0]

I'm also getting 'Segmentation fault', any ideas ?

[danielfortin86]

I'm also having the same problem. What was the solution?

[ECO]

Why not share your solution?

[demis001]

Found the problem

Sorry, I found the problem!

Disregard this question.....

DD

[demis001]

HMS-Segmentation fault

Hi,

I tried to run the test run using the sample data described on the user manual. However, I am keep getting "segmentation fault" error that was some what confusing. Usually, "segmentation fault" error spewed when there is a memory problem. I have tested on two system with 8GB RAM and 32GB RAM Linux workstations and getting the same result.

I then took the top 5 fasta line from the input and rerun the command described below. Still got the same result.

./hms -i top500.nrsf.hpeak.seq -w 21 -dna 4 -iteration 10 -chain 20 -seqprop 0.1 -strand 2 -nobase dep 2

Would you please comment what might go wrong?

DD

Hey, Abhi, thank you for your interest.

All the source of our data can be found in our supplementary document at

http://www.sph.umich.edu/csg/qin/HMS/nar-02346-s-2009-File002.pdf

The one at BCGSC

http://www.bcgsc.ca/data/chipseq

contains dataset that we did not analyze. You can try that.

I will try to find more and posted here later.


Best,

[GAanalyzer]

Hi Hanat,

Thank you for your interest in our program. You can find the C source code for background model at the HMS website:

http://www.sph.umich.edu/csg/qin/HMS/getProg.shtml

The command of this C source code can be found in HMS manual page 22.

http://www.sph.umich.edu/csg/qin/HMS/manual_hms.pdf

Free feel to contact me if you have any question.

Best,

Ming

[hannat]

hi
I've read the paper, and i found out that the background model is estimated from human promoter sequence. I wonder if you could also give the source code for background markov chain model estimation, because i am dealing with Drosophila sequence, i cant use the existing markov chain models.

regards

[GAanalyzer]

Hey, Abhi, thank you for your interest.

All the source of our data can be found in our supplementary document at

http://www.sph.umich.edu/csg/qin/HMS/nar-02346-s-2009-File002.pdf

The one at BCGSC

http://www.bcgsc.ca/data/chipseq

contains dataset that we did not analyze. You can try that.

I will try to find more and posted here later.


Best,

[apratap]

Hey

I am actually trying to get some hands on Chip-Seq data. Do you happen to know some good dataset @ SRA which I can download and play with HMS.

Thanks!
-Abhi

[GAanalyzer]

This is such a nice forum. I am impressed by the experience and enthusiasm of you guys. I just want to bring your attention to a paper we just published:

On the detection and refinement of transcription factor binding sites using ChIP-Seq data

Abstract

Coupling chromatin immunoprecipitation (ChIP) with recently developed massively parallel sequencing technologies has enabled genome-wide detection of protein-DNA interactions with unprecedented sensitivity and specificity. This new technology, ChIP-Seq, presents opportunities for in-depth analysis of transcription regulation. In this study, we explore the value of using ChIP-Seq data to better detect and refine transcription factor binding sites (TFBS). We introduce a novel computational algorithm named Hybrid Motif Sampler (HMS), specifically designed for TFBS motif discovery in ChIP-Seq data. We propose a Bayesian model that incorporates sequencing depth information to aid motif identification. Our model also allows intra-motif dependency to describe more accurately the underlying motif pattern. Our algorithm combines stochastic sampling and deterministic “greedy” search steps into a novel hybrid iterative scheme. This combination accelerates the computation process. Simulation studies demonstrate favorable performance of HMS compared to other existing methods. When applying HMS to real ChIP-Seq datasets, we find that (i) the accuracy of existing TFBS motif patterns can be significantly improved; and (ii) there is significant intra-motif dependency inside all the TFBS motifs we tested; modeling these dependencies further improves the accuracy of these TFBS motif patterns. These findings may offer new biological insights into the mechanisms of transcription factor regulation.

It is open access at

http://nar.oxfordjournals.org/cgi/content/abstract/gkp1180

Our HMS program is freely available at

http://www.sph.umich.edu/csg/qin/HMS/

Please give HMS a try. I hope that you find it useful. Questions, comments, suggestions and criticisms are welcomed and can be sent to me at [email protected]. Thank you very much.

Best,
Ming