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In the REDUCE Suite, a topology is a shorthand form for exploring a sequence motif, possibly including gaps. It is a flexible and convenient way to test different motif patterns as users see fit in a particular application.

For example, X8 means an 8-mer, with 4^8=65,536 possible combinations of the four canonical DNA or RNA bases. As another example, the topology X3--X4 represents a 7-mer with a 2-nt gap in between. The k-mer size (number of X positions) can be greater than 8: the maximum number is 15. Check the source code for details.

Try the utility program Topo2Dictfile to see a list of sequences corresponding to a given topology. These are the base sequences tested by MotifREDUCE/MatrixREDUCE.

Hope this helps,

Xiang-Jun
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General Discussion / How do I choose the topology -topo in MatrixREDUCE or MotifREDUCE?
« Last post by mora on September 13, 2018, 04:23:27 pm »
Is topology equal to kmers size of the binding site? what if I want to explore kmer sizes > 8?
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General Discussion / Re: Multicollinearity
« Last post by hjb2004 on September 10, 2018, 01:55:26 pm »
Dear Anthony,

Following up on Xiang-Jun's reply, you are correct that the Transfactivity program does not explicitly deal with collinearity. This should not be a problem when Transfactivity is used to infer TF activities for additional expression profiles using one more PSAMs generated by MatrixREDUCE, as the stepwise PSAM discovery implemented by MatrixREDUCE was explicitly designed to make the PSAMs distinct from each other. In other words, when AffinityProfile is used with a set of PSAMs discovered by MatrixREDUCE to create a matrix containing total affinities for each sequence (which is also the first step performed by Transfactivity), the columns of that matrix will be close to orthogonal. The value of the regression coefficients in a multi-PSAM linear regression will then be close those obtained in separate single-PSAM fits.

Things are potentially different, however, when Transfactivity is used with a set of PSAMs obtained from another source such as Jaspar. In that case, there is no guarantee that the columns of the affinity matrix created by AffinityProfile are independent of each other, and the behavior of the regression could indeed become unstable due to collinearity. We were dealing with exactly this situation in two of our lab’s previous papers. In one case, we implemented L2-penalized regression in R with a design matrix generated by AffinityProfile to deal with collinearity when inferring protein-level activities for a large number of yeast transcription factors (Lee et al., Mol Syst Biol 2010; https://www.ncbi.nlm.nih.gov/pubmed/20865005). In the second case, when we were doing the same for human transcription factors based on a collection of PWMs from Jaspar, we did some additional preprocessing on the design matrix in R as well (Lee et al., PNAS 2014; https://www.ncbi.nlm.nih.gov/pubmed/24706889; see supplemental methods).

I hope this is useful.

Best regards,
Harmen
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General Discussion / Re: Multicollinearity
« Last post by xiangjun on September 07, 2018, 09:32:52 pm »
Hi,

Thanks for using the REDUCE Suite and for posting your questions on the Forum.

As can be seen from the source code, Transfactivity checks for degeneracy in input data using SVD. However, multicollinearity is not checked by the program, as you already noticed. Users need to deal with the multicollinearity issue using other tools.

Best regards,

Xiang-Jun
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General Discussion / Multicollinearity
« Last post by amathelier on September 07, 2018, 07:13:59 am »
Hello,

I would like to use the Transfactivity tool from the REDUCE suite. One concern that I have is that if you use a large set of matrices (PWMs), some will be very similar and so can induce multicollinearity in their scores at promoter regions, and it will introduce multicollinearity between them in the multiple linear regression analysis. If so, then the activities of each TF associated to the similar PWMs might be wrong. Any insight/advice on how to tackle that? It does not seem that you take that into consideration in the previous usage of the tool.

Thanks
Best
AM
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General Discussion / Re: download previous versions of REDUCE_Suite
« Last post by xiangjun on August 16, 2018, 08:44:17 pm »
Hi Kate,

Sorry, no previous versions of the REDUCE_Suite are available for download.

May I know what you want to achieve with the original Convert2PSAM -source=v1 option, possibly with a concrete example?

Xiang-Jun
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General Discussion / download previous versions of REDUCE_Suite
« Last post by knie on August 16, 2018, 11:58:56 am »
Hi Xiang-Jun,

I'm wondering if there's a way to download the old versions of REDUCE_Suite. I need the `Convert2PSAM -source=v1`option, which was removed in the latest update.

Best,
Kate
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General Discussion / Re: availability of FeatureREDUCE?
« Last post by hjb2004 on July 18, 2018, 04:34:12 pm »
Hello PK,

The latest/only version of FeatureREDUCE is indeed still the 2015 version on GitHub:
https://github.com/FeatureREDUCE/FeatureREDUCE

You may also be interested in No Read Left Behind (NRLB), the latest algorithm from our lab:
https://github.com/BussemakerLab/NRLB
https://www.ncbi.nlm.nih.gov/pubmed/29610332

Best regards,
Harmen Bussemaker
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General Discussion / Re: availability of FeatureREDUCE?
« Last post by pk on July 18, 2018, 03:11:44 pm »
Thanks, Xiang-Jun, for the response!
I'll try asking the first author of the FeatureREDUCE manuscript about the current status of the software/project.
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Documentation / Re: Other utility programs
« Last post by xiangjun on July 18, 2018, 07:53:14 am »
Hi,

Type ProcessFASTA -h for more info. Check the source code for technical details.

Best regards,

Xiang-Jun
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Created and maintained by Dr. Xiang-Jun Lu [律祥俊]. See also http://forum.x3dna.org and http://x3dna.org