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Test your microbiome analysis pipeline with PLuMA

Study of the microbiome and metagenomics are actively developing areas of research. In the meantime, analyzing microbiome data has become increasingly complex, with multiple tools required to be run sequentially. Running these so-called “pipelines” of tools can be challenging because of the diversity of coding languages and compatibility issues.   To overcome this problem, Trevor Cickovski and Giri Narasimhan from the Bioinformatics Research Group of the Florida International University have developed PLuMA, a Plugin-Based Microbiome Analysis lightweight back end pipeline that supports multiple dynamically loaded plugin extensions. Here, they describe their tool and its main features.   Plugin-Based Microbiome Analysis   If you are an algorithm developer who wants to prototype, test and debug a new pipeline stage in your …

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Evaluate the quality of your read alignment with GeneQC

RNA-sequencing has replaced gene array and is now the leading technology in gene expression analysis. After a sequencing step, reads need to be mapped to a reference genome. However, this step is not perfect and errors can impact all downstream analyses. To address this issue, Adam McDermaid and colleagues have developed GeneQC, a tool to evaluate the quality of read alignment. Here, he describes GeneQC and its features. Quality control of read alignment One of the main benefits of using modern RNA-Sequencing (RNA-Seq) technology is the more accurate gene expression estimations compared with previous generations of expression data, such as the microarray. However, numerous issues can result in the possibility that an RNA-Seq read can be mapped to multiple locations …

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qPCR techniques and analysis software tools

Quantitative real-time polymerase chain reaction (qPCR) is widely used for the detection of specific nucleic acids, measurement of RNA transcript abundance and validation of high-throughput experimental results. While high-throughput sequencing (HTS) has revolutionized the fields of genomics and transcriptomics, qPCR techniques have evolved and can now be performed in a high-throughput fashion. Introduction qPCR is an easy-to-perform technique to evaluate the relative (or absolute) expression of genes as compared to each other and/or a reference. Traditional qPCR is often used to validate results from gene arrays or HTS, as it is more precise, rapid to perform, and cheap.   Recently, new technologies have been developed to increase the number of genes that can be tested simultaneously. Next generation qPCR platforms …

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Explore gene-expression datasets with the Omics Dashboard

The advent of omics technologies has fostered the generation of a flood of complex, high-resolution datasets, the analysis of which remains a major hurdle and requires conversion into actionable biological knowledge. To address this challenge, Peter Karp and his colleagues from the SRI Bioinformatics Research Group have developed the Omics Dashboard within the BioCyc.org website. Here, they present their tool and its main features. The Omics Dashboard The Dashboard provides a multi-level visual read out of an expression dataset, from the cellular level to the gene level.  The user can probe their data in a fast and intuitive manner to gain a deep understanding of the data at multiple biological levels.   At the highest echelon (Figure 1) the Dashboard provides …

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Virtualize your computing with IaaS

Since the advent of high-throughput sequencing, the number and complexity of biological data has exploded. Though information technology and computers have paralleled this development, researchers rarely meet the computational power and storage capability required to perform the analysis of their data (Ben Langmead and Abhinav Nellore). Infrastructure as a service to the rescue For this, infrastructures as a service (IaaS) have been created to let users run large-scale computing workloads on the cloud – that is, on virtual machines hosted on dedicated infrastructures – and to stock up to exabits of data.   According to the National Institute of Standards and Technology, IaaS can be described as:   The capability provided to the consumer is to provision processing, storage, networks, …

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Your top 3 RNA-seq quantification and differential expression tools

RNA-sequencing is progressively replacing microarrays for the study of transcriptomes, and comparison of gene expression. One advantage of this technique is the ability to identify and quantify the expression of isoforms and unknown transcripts.   To help you perform your experiments in the best conditions, we are closing our series of surveys on RNA-sequencing by asking OMICtools members to choose their favorite quantification and differential expression tools. RNA quantification and differential expression While microarrays produce a numerical estimate of the relative expression of genes across the genome, RNA-sequencing experiments rely on read-count distributions. After mapping reads to a reference genome, the expression level for each gene or isoform are estimated and normalized, and finally differentially-expressed genes are identified using statistical methods. …

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Promoting standards in biological research

Most research advances are built upon pre-existing data and findings. This paradigm implies that researchers must be able to reproduce data on which they base their own research. Yet a number of promising pre-clinical researches do not go into clinics because of the inability to reproduce the work (Freedman and Inglese). For this, it has become essential to set standards and good practices in life sciences research. Initiatives promoting standards in biology A number of initiatives have been created to set and promote standards in biology research. Some society are proposing standards to cover all areas of basic research and clinics, while others are focusing on specific research fields. Here are some of the most advanced organizations which develop standards …

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Your top 3 RNA-seq read alignment tools

RNA-sequencing (RNA-seq) is currently the leading technology for transcriptome analysis. RNA-seq has a wide range of applications, from the study of alternative gene splicing, post-transcriptional modifications, to comparison of relative gene expression between different biological samples.   To help you perform your RNA-seq experiments in the best conditions, we are continuing our series of surveys by asking you to choose your favorite analysis tools step by step. Mapping reads to reference genome  After a first step of quality control (previous blog post here), the next step in the analysis of your RNA-seq experiment is alignment of reads to a reference genome or a transcriptome database.   There are two types of aligners: Splice-unaware and splice-aware. Splice-unaware aligners are able to align continuous reads to a …

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