In the second simulation, we generated 30 vectors from the original species abundance vectors used for the first simulation. These 30 vectors were generated by adding to each component the absolute value of one-fifth Gaussian noise, with mean zero and standard deviation equal to the value of that component. Each species abundance vector was randomized and renormalized 10 times, and the 30 vectors, which belonged to three groups with 10 vectors in each group, were obtained (
Simulated Metagenome Generation with Microbial Abundance Variations
In the second simulation, we generated 30 vectors from the original species abundance vectors used for the first simulation. These 30 vectors were generated by adding to each component the absolute value of one-fifth Gaussian noise, with mean zero and standard deviation equal to the value of that component. Each species abundance vector was randomized and renormalized 10 times, and the 30 vectors, which belonged to three groups with 10 vectors in each group, were obtained (
Corresponding Organization : Kyoto Prefectural University
Other organizations : National Institute for Basic Biology, Rakuno Gakuen University, Hokusei Gakuen University, Hokkaido University
Variable analysis
- Relative abundance vectors of the five bacterial species (0.297, 0.507, 0.116, 0.058, 0.022), (0.345, 0.244, 0.281, 0.088, 0.042), and (0.526, 0.320, 0.042, 0.066, 0.046)
- 30 vectors generated by increasing or decreasing each of the five values in the original relative abundance vectors by 5%
- 30 vectors generated by adding one-fifth Gaussian noise (mean 0, standard deviation equal to the value of that component) to the original relative abundance vectors and renormalizing them
- 30 metagenomic samples generated by mixing the randomly sampled short reads from the five bacteria using NeSSM software
- Genomic sequences of the five bacterial species: Sulfolobus islandicus, Proteus mirabilis, Nitrosospira multiformis, Bacteroides fragilis, and Acidobacterium capsulatum
- NeSSM software used for generating the simulated short-read metagenomic datasets
Annotations
Based on most similar protocols
As authors may omit details in methods from publication, our AI will look for missing critical information across the 5 most similar protocols.
About PubCompare
Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.
We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.
However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.
Ready to get started?
Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required
Revolutionizing how scientists
search and build protocols!