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Old 11-03-2010, 12:43 PM   #21
bacdirector
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Default thanks, everyone

well, a lot of great feedback and perspective here; looks like a lot of people are doing different things; some use a masking tool, which should allow reads to map in spite of non-calls; that makes sense; we have heard of progressive mapping, but not done it yet, and will be studying that in comparison to what we've found. also, re: # uniquely mapped reads, will be sure to report back on that after we look at that closely (over the various trimmed lengths).

with the various strategies for data representation, filtering on qvals; trimming back based on qvals; and given the various algorithms, i.e., bfast, and bowtie, and right now we're doing nextgene and bioscope, there seems, as usual, to be a combinatorial number of strategies. we've been careful to be to look at the number of valid adjacent errors as well to be sure we're not just mapping short reads anywhere and everywhere.

yeah, the dibase encoding = higher accuracy is real.

looks like we have a lot of careful comparative evaluations to do!

any additional thoughts would be appreciated.
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Old 11-03-2010, 01:26 PM   #22
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For your evaluations (simulations), take a look to this.
The author of bfast talks about simulating reads and then plotting the results using ROC curves to find the best tool for the problem.
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Old 11-04-2010, 11:28 AM   #23
bacdirector
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Default Ok, here it is - Percent of Reads that Map that Also Map Uniquely

In our study that started this thread, I originally reported a doubling of reads mapped from 25 million to 50 million achieved by trimming all reads >35 to 35. At 50b, we get only 25 million reads mapped. This was based on empirical comparisons of reported valid adj errors.

The answer to the question of what percent of reads map uniquely is--- it barely matters. The range is 85.5% to 86.5% Percent of Reads that Map that Also Map Uniquely, with an increasing trend from 85.5% to 86.5% going from 25b trimmed reads to 50b reads.

So far, we've seen the optimal overall response to trimming at 35b. This is for Bioscope, not Nextgene (my bad!!!), but without any masking of -1's..... so in response to feedback from the thread, we'll be expanding our repetoire to include progressive mapping as well as non-call masking. And bfast. And bowtie. We have all the trimmed data sets ready to go, it's just a matter of punching buttons...

thanks, everyone for your interest and feedback!

James Lyons-Weiler
Director
Bioinformatics Analysis Core
University of Pittsburgh
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Old 10-26-2012, 04:47 PM   #24
Chirag
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Hey,

Could anyone help me on how to trim the color space data.
I am using bowtie/tophat to map the data, and i map only around 40% of the reads. Reads are 75 bp long and i had allowed 3 mismatches, where allowing 2 mismatch had given me only 35% mapping.

Could someone help me on how to trim the end of the reads, for eg, last 10/15 bases are trimmed, so could probably map more. But haven't found yet any S/W that does trimming for SoliD ?

regards
Chirag
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Old 10-28-2012, 03:54 PM   #25
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Try this:
http://hts.rutgers.edu/filter
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Old 10-30-2012, 12:27 AM   #26
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The best aligners for CS data use iterative trimming, see for example NovoalignCS and Lifescope.
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