|Combinations of algorithms tested for the processing of pyrosequencing datasets for dT-RFLP profiling in PyroTRF-ID|
|Pyrosequencing data processing procedure||Processing algorithms|
|PHRED-filteringa||Sequence length cut-off||Denoising||Filtering by SW mapping scoreb||Restriction of sequencesc|
|1) Standard dT-RFLPd||>20e||>300 bp||Yes||>150f||Yes|
|2) Filtered dT-RFLPe||>20||>300 bp||No||>150||Yes|
|3) Raw dT-RFLPd||>20||>300 bp||No||No (0)g||Yes|
a PHRED score = −10 log Perror with Perror = 10-PHRED/10 as the probability that a base was called incorrectly. For all trials, the raw pyrosequencing datasets were systematically filtered according to the PHRED quality score. Only sequences with a related PHRED score above 20 were conserved. This corresponds to a Perror of 1/100.
b A SW mapping score of 150 was set as cutoff. In the case when sequences were preliminarily denoised, it was nevertheless observed that no denoised sequence was rejected at the mapping stage. Processing without filtering by the SW mapping score was done by setting a cutoff of 0.
c The processed sequences were digested in silico with the restriction enzyme.
d The first combination with denoising was defined as the standard PyroTRF-ID procedure.
e In the second combination, only a filtering method at the mapping stage was considered.
f In the third combination, raw datasets of sequences obtained after PHRED-filtering of the pyrosequencing datasets were digested without post-processing.
Weissbrodt et al. BMC Microbiology 2012 12:306 doi:10.1186/1471-2180-12-306