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I have about 3300 reads from foxmid library and I'd like to maping to a reference sequence, how should I do? I also have some solexa data to improve my sequence quality. Can I use the some software to map or different?
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you can try new version consed, it can mapping sanger and solexa reads.
good luck -
Yes, I have tried. However, I do not satisfied with the results. I'd like to know some beter way to mapping the reads.Comment
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SHRiMP will happily align both your Solexa and Sanger reads to your reference sequence, allowing for both indels and substitutions: http://compbio.cs.toronto.edu/shrimp/Originally posted by anyone1985 View Post
I have used it for Solexa, SOLID3, Sanger and 454 data with success.Comment
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Thank you for your answer. Can the SHRiMP output the result in the format of ace? I would like to calculate the sequence quality, too.
Originally posted by Torst View PostComment
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You might want to try MIRA, it'll happily map Sanger, 454 and Solexas for you and shell out the results as FASTA, CAF, ACE ... . Screenshot of 454 and Sanger reads mapped to a reference: http://chevreux.org/mira_ex_454sanger.htmlOriginally posted by anyone1985 View Post
B.
Disclaimer: I may be biased, I wrote MIRA.Comment
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Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.Today, 11:43 AM
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I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.
Here are nine questions we think about, in roughly the order they matter, before... -
Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.
The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
...06-02-2026, 10:05 AM
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