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How do I do with this error #18

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realzhang opened this issue Sep 7, 2021 · 3 comments
Open

How do I do with this error #18

realzhang opened this issue Sep 7, 2021 · 3 comments

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@realzhang
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I ran DSS with some WGBS data, and after a overnight running with 50 threads on my culster, it showed:

Estimating dispersion for each CpG site, this will take a while ...                                                                                                                          
  |======================================================================| 100%                                                                                                              
                                                                                                                                                                                             
  |======================================================================| 100%                                                                                                              

Error in split.default(1:n0, allchr2) : 组的长度为零但数据的长度大于零

May this be caused by spiked in DNAs? they are used with Chr name Lambda and pUC19.
And another question, DMLtest is extremely slow, which stays 0% for hours. I usually run it overnight, but if it errs like above I'll be very frustrated.
DSS is a great tool for DNA methylation analysis. Your work make life easier. Thanks.

@realzhang
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I am also curious about the second progress bar. If the first row stand for dispersion estimation, what does the 2nd stand for?

@realzhang
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Error in split.default(1:n0, allchr2) : 组的长度为零但数据的长度大于零
I found that an extra space in the input file made this error.

For the slow speed of dmlTest, I am trying to use a less number of cores. (now using workers=10).
I guess allocate big BSobj among threads may cause huge time consuming.

@haowulab
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haowulab commented Sep 7, 2021

I am also curious about the second progress bar. If the first row stand for dispersion estimation, what does the 2nd stand for?

The two bars are for the dispersion estimation for two groups. In a two-group comparison case, the dispersions are assumed to be different thus will be estimated separately.

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