Another problem undermining data integrity in the INSDs is the deposition of sequences in the reverse complementary orientation (i.e. backwards and with all purines and pyrimidines transposed). Reverse complementary sequences are generated unintentionally, usually during the sequence assembly step, through human or machine failure to relate the orientation of the sequences under processing to that of the others being generated. Reverse complementary sequences are easy to reorient using publically available software
resources (e.g. Stajich et al., 2002), but to detect them in the first place is not always as straightforward. Contamination of datasets with reverse complementary sequences can seriously affect downstream analysis. Currently, only a few tools such as NCBI blast http://www.selleckchem.com/products/azd9291.html (Altschul et al., selleck chemicals llc 1997) can actually account for the presence of reverse complementary sequences. In contrast, these sequences will introduce analytic noise in analyses such as multiple sequence alignments, phylogenetic classifications and various approaches to sequence-based clustering. These events are usually detectable by manual screening; however, this becomes unfeasible as datasets grow. Automated detection and correction of reverse complementary sequences has therefore become essential in order to screen individually generated
datasets as well as to assess and maintain the integrity of public data repositories. To address the problem of reverse complementary bacterial and archaeal 16S sequences in environmental sequence datasets, we developed v-revcomp, a high-throughput, command-line driven, open-source software package. Drawing from Nilsson et al. (2011), the software is written in Perl and processes arbitrarily large fasta format (Pearson & Lipman, 1988) datasets. Hidden Markov Models (HMMs) recently designed for every conserved region along the bacterial and archaeal Sirolimus price 16S gene (Hartmann et al., 2010) are used to determine the orientation of the sequence. The software attempts to locate up to 18 HMM regions along the query sequence using hmmer version 3 (Eddy, 1998). The query sequence is first screened in its
input orientation and subsequently in the reverse complementary orientation. The ratio of HMM detection frequency between the default and the opposite orientation of a query sequence provides a reliable measure of its orientation. A fasta format output file containing all entries of the input file is generated; in this file, all sequences identified as reverse complementary are given in the correct orientation. A comma-separated value file contains the detection statistics and allows the user to examine sequences with ambiguous detection results in more detail. This output lists the HMM detection frequency in the input and reverse complementary orientation, and provides a prediction of the sequence orientation based on the detection ratio, i.e.
Related posts:
- Problem solving involves the perception of a problem, the generat
- The length of our sequence reads was 100 bp and we allowed 3 mism
- Laboratories and monitors provide medical data for processing, a
- Data for levofloxacin in Table Table22 was obtained from a publi
- 1 1 Addressing the Problem of Nitrite AssessmentNitrates (NO3?)