Clc main workbench v7
CLC Main Workbench v7 is a bioinformatics software suite developed by Qiagen. It provides tools for analyzing and visualizing biological sequence data, including DNA, RNA, and protein sequences. The software supports a range of functionalities, such as sequence alignment, phylogenetic analysis, and genome assembly, among others.
Lab products found in correlation
13 protocols using clc main workbench v7
Sequence Assembly and SNP Identification
Sequencing and Analysis of Pfcrt Gene
16S rRNA Gene Sequencing Protocol
Bacterial Identification by 16S rRNA Sequencing
The 16S rRNA gene was amplified using primers SSU-bact-27F (5 -AGAGTTTGATCMTGGCTGAG-3 ) and SSU-bact-519R (5 -GWATTACCGCGGCKGCTG-3 ) [28]. Amplification was performed in a total volume of 20 μl containing 2-mM deoxynucleoside triphosphates, 10X Taq buffer, 25 mM MgCl 2, 20 μM of each primer and 5 U/μl of HotStart AmpliTaq Gold DNA polymerase. The thermal cycling conditions were the following: 95 for 12 min, followed by 30 cycles of 94 • C for 30 s, 53 • C for 30 s and 72 • C for 1 min, and a final extension of 72 • C for 10 min. The resulting PCR products were sequenced on the Genetic Analyzer 3500 (Applied Biosystems TM , CA, USA). Obtained sequences were extracted using Sequencing Analysis v5.4 software (Applied Biosystems), assembled using CLC Main Workbench v7.0.2 (CLC-bio, Aarhus, Denmark) and blasted against the NCBI 16S rRNA database.
Centipede Venom Protein GC Analysis
Bushmeat Species Identification by DNA Barcoding
All statistical analyses were performed in R v3.4.4 [29 ]. The kappa2 function of the IRR package was used to determine concordance between seller-reported and laboratory-confirmed results[30 ]. A Chi-squared test was performed to test whether the match/mismatch percentages were similar between different reported species using the prop.test function in R. The prop.test function was also used to perform pairwise analysis of the individual species (seller-reported versus laboratory-confirmed) [16 (link)]. One-sample t-test power analysis was performed to calculate the sample size with the following assumptions: power = 0.95, Significance = 0.05, an Effect size of 0.25.
Phylogenetic Analysis of Representative Burkholderia Genomes
Viral dsRNA Extraction and Sequencing Protocol
Amplification and Sequencing of Putative Regulatory Regions
Phylogenetic Analysis of Genetic Sequences
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