You should have this tool if you have a 454 sequencer. We will show an example with two 454 runs ( run1.sff and run2.sff).įrom the raw, binary sff file, three files need to be generated for each run with the sffinfo tool from 454. ![]() Afterwards the output files are combined for OTU picking. In short, each 454 run needs to be preprocessed with split_libraries.py and denoised separately. If there are multiple, large 454 runs, follow this tutorial to denoise the data set and analyze it with QIIME. The goal for the denoising procedure is to reduce the amount of erroneous OTUs and thus increasing the accuracy of the whole QIIME pipeline. ![]() Most of the sequences contain none or only a few errors, but a few sequences contain enough errors to be classified as an additional rare OTU. The pyrosequencing technology employed by 454 sequencing machines produces characteristic sequencing errors, mostly imprecise signals for longer homopolymers runs.
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