scholarly journals M&Ms: A software for building realistic Microbial Mock communities

2021 ◽  
Author(s):  
Natalia García-García ◽  
Javier Tamames ◽  
Fernando Puente-Sánchez
Keyword(s):  
Microbial Communities ◽  
In Silico ◽  
Source Code ◽  
Simulated Data ◽  
Bioinformatic Tools ◽  
Sequencing Technologies ◽  
Bioinformatic Tool ◽  
Reference Sequences ◽  
User Friendly ◽  
Mock Communities

Motivation: Advances in sequencing technologies have triggered the development of many bioinformatic tools aimed to analyze these data. As these tools need to be tested, it is important to simulate datasets that resemble realistic conditions. Although there is a large amount of software dedicated to produce reads from in silico microbial communities, often the simulated data diverge widely from real situations. Results: Here, we introduce M&Ms, a user-friendly open-source bioinformatic tool to produce realistic amplicon datasets from reference sequences, based on pragmatic ecological parameters. This tool creates sequence libraries for in silico microbial communities with user-controlled richness, evenness, microdiversity, and source environment. M&Ms allows the user to generate simple to complex read datasets based on real parameters that can be used in developing bioinformatic software or in benchmarking current tools. M&Ms also provides additional figures and files with extensive details on how each synthetic community is composed, so that users can make informed choices when designing their benchmarking pipelines. Availability: The source code of M&Ms is freely available from https://github.com/ggnatalia/MMs

scholarly journals ASaiM: a Galaxy-based framework to analyze raw shotgun data from microbiota

2017 ◽  
Author(s):  
Bérénice Batut ◽  
Kévin Gravouil ◽  
Clémence Defois ◽  
Saskia Hiltemann ◽  
Jean-François Brugère ◽  
...  
Keyword(s):  
Technological Progress ◽  
Source Code ◽  
Command Line ◽  
Bioinformatic Tools ◽  
Link Type ◽  
Data Analyses ◽  
The Galaxy ◽  
Sequencing Platforms ◽  
User Friendly ◽  
New Generation

AbstractBackgroundNew generation of sequencing platforms coupled to numerous bioinformatics tools has led to rapid technological progress in metagenomics and metatranscriptomics to investigate complex microorganism communities. Nevertheless, a combination of different bioinformatic tools remains necessary to draw conclusions out of microbiota studies. Modular and user-friendly tools would greatly improve such studies.FindingsWe therefore developed ASaiM, an Open-Source Galaxy-based framework dedicated to microbiota data analyses. ASaiM provides a curated collection of tools to explore and visualize taxonomic and functional information from raw amplicon, metagenomic or metatranscriptomic sequences. To guide different analyses, several customizable workflows are included. All workflows are supported by tutorials and Galaxy interactive tours to guide the users through the analyses step by step. ASaiM is implemented as Galaxy Docker flavour. It is scalable to many thousand datasets, but also can be used a normal PC. The associated source code is available under Apache 2 license at https://github.com/ASaiM/framework and documentation can be found online (http://asaim.readthedocs.io/)ConclusionsBased on the Galaxy framework, ASaiM offers sophisticated analyses to scientists without command-line knowledge. ASaiM provides a powerful framework to easily and quickly explore microbiota data in a reproducible and transparent environment.

scholarly journals MOSGA: Modular Open-Source Genome Annotator

2020 ◽  
Author(s):  
Roman Martin ◽  
Thomas Hackl ◽  
Georges Hattab ◽  
Matthias G Fischer ◽  
Dominik Heider
Keyword(s):  
Open Source ◽  
Source Code ◽  
Supplementary Information ◽  
Web Interface ◽  
Fully Integrated ◽  
Sequencing Technologies ◽  
A Genome ◽  
Wide Range ◽  
User Friendly ◽  
Eukaryotic Genomes

Abstract Motivation The generation of high-quality assemblies, even for large eukaryotic genomes, has become a routine task for many biologists thanks to recent advances in sequencing technologies. However, the annotation of these assemblies—a crucial step toward unlocking the biology of the organism of interest—has remained a complex challenge that often requires advanced bioinformatics expertise. Results Here, we present MOSGA (Modular Open-Source Genome Annotator), a genome annotation framework for eukaryotic genomes with a user-friendly web-interface that generates and integrates annotations from various tools. The aggregated results can be analyzed with a fully integrated genome browser and are provided in a format ready for submission to NCBI. MOSGA is built on a portable, customizable and easily extendible Snakemake backend, and thus, can be tailored to a wide range of users and projects. Availability and implementation We provide MOSGA as a web service at https://mosga.mathematik.uni-marburg.de and as a docker container at registry.gitlab.com/mosga/mosga: latest. Source code can be found at https://gitlab.com/mosga/mosga Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals The lncRNA Toolkit: Databases and In Silico Tools for lncRNA Analysis

2020 ◽  
Vol 6 (4) ◽  
pp. 49
Author(s):  
Holly R. Pinkney ◽  
Brandon M. Wright ◽  
Sarah D. Diermeier
Keyword(s):  
In Silico ◽  
In Silico Analysis ◽  
Small Subset ◽  
Specific Expression ◽  
Protein Coding ◽  
Bioinformatic Tools ◽  
Structural Conformation ◽  
Starting Point ◽  
Wet Lab ◽  
User Friendly

Long non-coding RNAs (lncRNAs) are a rapidly expanding field of research, with many new transcripts identified each year. However, only a small subset of lncRNAs has been characterized functionally thus far. To aid investigating the mechanisms of action by which new lncRNAs act, bioinformatic tools and databases are invaluable. Here, we review a selection of computational tools and databases for the in silico analysis of lncRNAs, including tissue-specific expression, protein coding potential, subcellular localization, structural conformation, and interaction partners. The assembled lncRNA toolkit is aimed primarily at experimental researchers as a useful starting point to guide wet-lab experiments, mainly containing multi-functional, user-friendly interfaces. With more and more new lncRNA analysis tools available, it will be essential to provide continuous updates and maintain the availability of key software in the future.

Comparative Study on Mitogen Activated Protein Kinase of Plasmodium Species by Using In silico Method

2012 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Mohd Fakharul Zaman Raja Yahya ◽  
Hasidah Mohd Sidek
Keyword(s):  
Amino Acid ◽  
In Silico ◽  
Nuclear Export ◽  
Nuclear Export Signal ◽  
Plasmodium Species ◽  
Mitogen Activated Protein Kinase ◽  
Multiple Sequence ◽  
Bioinformatic Tools ◽  
Wide Range ◽  
Human Plasmodium

Malaria parasites, Plasmodium can infect a wide range ofhosts including humans and rodents. There are two copies ofmitogen activated protein kinases (MAPKs) in Plasmodium, namely MAPK1 and MAPK2. The MAPKs have been studied extensively in the human Plasmodium, P. falciparum. However, the MAPKs from other Plasmodium species have not been characterized and it is therefore the premise ofpresented study to characterize the MAPKs from other Plasmodium species-P. vivax, P. knowlesi, P. berghei, P. chabaudi and P.yoelli using a series ofpublicly available bioinformatic tools. In silico data indicates that all Plasmodium MAPKs are nuclear-localizedandcontain both a nuclear localization signal (NLS) anda Leucine-rich nuclear export signal (NES). The activation motifs ofTDYand TSH werefound to befully conserved in Plasmodium MAPK1 and MAPK2, respectively. The detailed manual inspection ofa multiple sequence alignment (MSA) construct revealed a total of 17 amino acid stack patterns comprising ofdifferent amino acids present in MAPK1 and MAPK2 respectively, with respect to rodent and human Plasmodia. 1t is proposed that these amino acid stack patterns may be useful in explaining the disparity between rodent and human Plasmodium MAPKs.

scholarly journals How to Use Online Tools to Generate New Hypotheses for Mammary Gland Biology Research: A Case Study for Wnt7b

2021 ◽  
Author(s):  
Yorick Bernardus Cornelis van de Grift ◽  
Nika Heijmans ◽  
Renée van Amerongen
Keyword(s):  
Mammary Gland ◽  
In Silico ◽  
Online Tools ◽  
Mammary Gland Biology ◽  
User Friendly ◽  
In Silico Analyses ◽  
Biology Research ◽  
Selection Of

AbstractAn increasing number of ‘-omics’ datasets, generated by labs all across the world, are becoming available. They contain a wealth of data that are largely unexplored. Not every scientist, however, will have access to the required resources and expertise to analyze such data from scratch. Fortunately, a growing number of investigators is dedicating their time and effort to the development of user friendly, online applications that allow researchers to use and investigate these datasets. Here, we will illustrate the usefulness of such an approach. Using regulation of Wnt7b expression as an example, we will highlight a selection of accessible tools and resources that are available to researchers in the area of mammary gland biology. We show how they can be used for in silico analyses of gene regulatory mechanisms, resulting in new hypotheses and providing leads for experimental follow up. We also call out to the mammary gland community to join forces in a coordinated effort to generate and share additional tissue-specific ‘-omics’ datasets and thereby expand the in silico toolbox.

scholarly journals BioCommons: a robust java library for RNA structural bioinformatics

2021 ◽  
Author(s):  
Tomasz Zok
Keyword(s):  
Source Code ◽  
Structural Bioinformatics ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Bioinformatic Tools ◽  
Data Formats ◽  
Central Repository ◽  
Diverse Data ◽  
2D And 3D ◽  
Java Library

Abstract Motivation Biomolecular structures come in multiple representations and diverse data formats. Their incompatibility with the requirements of data analysis programs significantly hinders the analytics and the creation of new structure-oriented bioinformatic tools. Therefore, the need for robust libraries of data processing functions is still growing. Results BioCommons is an open-source, Java library for structural bioinformatics. It contains many functions working with the 2D and 3D structures of biomolecules, with a particular emphasis on RNA. Availability and implementation The library is available in Maven Central Repository and its source code is hosted on GitHub: https://github.com/tzok/BioCommons Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Bioinformatic tools help molecular characterization of Perkinsus olseni differentially expressed genes

2011 ◽  
Vol 8 (3) ◽  
pp. 130-140 ◽  
Author(s):  
Rita M. T. Ascenso
Keyword(s):  
Molecular Characterization ◽  
Protozoan Parasite ◽  
Bioinformatic Tools ◽  
Host Interaction ◽  
Ria Formosa ◽  
Genes Expression ◽  
Bioinformatic Tool ◽  
Southern Portugal ◽  
Heavy Mortality

Abstract In the 80ies, in Southern Europe and in particular in Ria Formosa there was an episode of heavy mortality of the economically relevant clam Ruditapes (R.) decussatus associated with a debilitating disease (Perkinsosis) caused by Perkinsus olseni. This protozoan parasite was poorly known concerning its’ differential transcriptome in response to its host, R. decussatus. This laboratory available protozoan system was used to identify parasite genes related to host interaction. Beyond the application of molecular biology technologies and methodologies, only the help of Bioinformatics tools allowed to analyze the results of the study. The strategy started with SSH technique, allowing the identification of parasite up-regulated genes in response to its natural host, then a macroarray was constructed and hybridized to characterize the parasite genes expression when exposed to bivalves hemolymph from permissive host (R. decussatus), resistant host (R. philippinarum) and non permissive bivalve (Donax trunculus) that cohabit in the same or adjacent habitats in Southern Portugal. Genes and respective peptides full molecular characterization depended on several Bioinformatic tools application. Also a new Bioinformatic tool was developed.

Phylum-Specific Primer Design and Implication in Quantification of the Microbial Community Structure in GuJingGong Pit Mud

2014 ◽  
Vol 1051 ◽  
pp. 311-316 ◽  
Author(s):  
Xi Mei Luo ◽  
Zhi Lei Gao ◽  
Hui Min Zhang ◽  
An Jun Li ◽  
Hong Kui He ◽  
...  
Keyword(s):  
Community Structure ◽  
Microbial Community ◽  
Microbial Communities ◽  
Microbial Community Structure ◽  
Real Time Quantitative Pcr ◽  
Sequencing Technologies ◽  
Specific Pcr ◽  
Pit Mud ◽  
Almost All ◽  
Polymerase Chain Reaction Primers

In recent years, despite the significant improvement of sequencing technologies such as the pyrosequencing, rapid evaluation of microbial community structures remains very difficult because of the abundance and complexity of organisms in almost all natural microbial communities. In this paper, a group of phylum-specific primers were elaborately designed based on a single nucleotide discrimination technology to quantify the main microbial community structure from GuJingGong pit mud samples using the real-time quantitative PCR (qPCR). Specific PCR (polymerase chain reaction) primers targeting a particular group would provide promising sensitivity and more in-depth assessment of microbial communities.

scholarly journals Deciphering the evolution of microbial interactions: in silico studies of two-member microbial communities

2022 ◽  
Author(s):  
Gayathri Sambamoorthy ◽  
Karthik Raman
Keyword(s):  
Microbial Communities ◽  
In Silico ◽  
Microbial Interactions ◽  
Interaction Patterns ◽  
Wild Type ◽  
Community Function ◽  
Evolutionary Forces ◽  
In Silico Studies ◽  
Wide Range ◽  
In The Wild

Microbes thrive in communities, embedded in a complex web of interactions. These interactions, particularly metabolic interactions, play a crucial role in maintaining the community structure and function. As the organisms thrive and evolve, a variety of evolutionary processes alter the interactions among the organisms in the community, although the community function remains intact. In this work, we simulate the evolution of two-member microbial communities in silico to study how evolutionary forces can shape the interactions between organisms. We employ genomescale metabolic models of organisms from the human gut, which exhibit a range of interaction patterns, from mutualism to parasitism. We observe that the evolution of microbial interactions varies depending upon the starting interaction and also on the metabolic capabilities of the organisms in the community. We find that evolutionary constraints play a significant role in shaping the dependencies of organisms in the community. Evolution of microbial communities yields fitness benefits in only a small fraction of the communities, and is also dependent on the interaction type of the wild-type communities. The metabolites cross-fed in the wild-type communities appear in only less than 50% of the evolved communities. A wide range of new metabolites are cross-fed as the communities evolve. Further, the dynamics of microbial interactions are not specific to the interaction of the wild-type community but vary depending on the organisms present in the community. Our approach of evolving microbial communities in silico provides an exciting glimpse of the dynamics of microbial interactions and offers several avenues for future investigations.

scholarly journals A phylogenetic transform enhances analysis of compositional microbiota data

2016 ◽  
Author(s):  
Justin D Silverman ◽  
Alex Washburne ◽  
Sayan Mukherjee ◽  
Lawrence A David
Keyword(s):  
Microbial Communities ◽  
Relative Abundance ◽  
Dominant Role ◽  
Phylogenetic Information ◽  
Abundance Data ◽  
Sequencing Technologies ◽  
Environmental Selection ◽  
Health And Disease ◽  
High Throughput Dna Sequencing ◽  
Spurious Results

ABSTRACTHigh-throughput DNA sequencing technologies have revolutionized the study of microbial communities (microbiota) and have revealed their importance in both human health and disease. However, due to technical limitations, data from microbiota surveys reflect the relative abundance of bacterial taxa and not their absolute levels. It is well known that applying common statistical methods, such as correlation or hypothesis testing, to relative abundance data can lead to spurious results. Here, we introduce the PhILR transform, a data transform that utilizes microbial phylogenetic information. This transform enables off-the-shelf statistical tools to be applied to microbiota surveys free from artifacts usually associated with analysis of relative abundance data. Using environmental and human-associated microbial community datasets as benchmarks, we find that the PhILR transform significantly improves the performance of distance-based and machine learning-based statistics, boosting the accuracy of widely used algorithms on reference benchmarks by 90%. Because the PhILR transform relies on bacterial phylogenies, statistics applied in the PhILR coordinate system are also framed within an evolutionary perspective. Regression on PhILR transformed human microbiota data identified evolutionarily neighboring bacterial clades that may have differentiated to adapt to distinct body sites. Variance statistics showed that the degree of covariation of bacterial clades across human body sites tended to increase with phylogenetic relatedness between clades. These findings support the hypothesis that environmental selection, not competition between bacteria, plays a dominant role in structuring human-associated microbial communities.

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