Functional renal MRI promises access to a wide range of physiologically relevant parameters such as blood oxygenation, perfusion, tissue microstructure, pH, and sodium concentration. For quantitative comparison of res...
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Functional renal MRI promises access to a wide range of physiologically relevant parameters such as blood oxygenation, perfusion, tissue microstructure, pH, and sodium concentration. For quantitative comparison of results, representative values must be extracted from the parametric maps obtained with these different MRI techniques. To improve reproducibility of results this should be done based on regions-of-interest (ROIs) that are clearly and objectively defined. Semiautomated subsegmentation of the kidney in magnetic resonance images represents a simple but very valuable approach for the quantitative analysis of imaging parameters in multiple ROIs that are associated with specific anatomic locations. Thereby, it facilitates comparing MR parameters between different kidney regions, as well as tracking changes over time. Here we provide detailed step-by-step instructions for two recently developed subsegmentation techniques that are suitable for kidneys of small rodents: i) the placement of ROIs in cortex, outer and the inner medulla based on typical kidney morphology and ii) the division of the kidney into concentrically oriented layers. This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. less
Recent advances in MS/MS technology have made it possible to use proteomic data to predict protein-coding sequences. This approach is called proteogenomics, and it allows to correctly translate start and stop sites an...
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Recent advances in MS/MS technology have made it possible to use proteomic data to predict protein-coding sequences. This approach is called proteogenomics, and it allows to correctly translate start and stop sites and to reveal new open reading frames. Here, we focus on using proteogenomics to improve the annotation of Mycobacteriumtuberculosis strains. We also describe detail procedures of the extraction of proteins and their further preparation for LC–MS/MS analysis and outline the main steps of data analysis. less
Bioinformatic scientists are often asked to do widespread analyses of publicly available datasets in order to identify genetic alterations in cancer for genes of interest; therefore, we sought to create a set of tools...
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Bioinformatic scientists are often asked to do widespread analyses of publicly available datasets in order to identify genetic alterations in cancer for genes of interest; therefore, we sought to create a set of tools to conduct common statistical analyses of The Cancer Genome Atlas (TCGA) data. These tools have been developed in response to requests from our collaborators to ask questions, validate findings, and better understand the function of their gene of interest. We describe here what data we have used, how to obtain it, and what figures we have found useful. less
Ribosome profiling, or Ribo-seq, provides precise information about the position of actively translating ribosomes. It can be used to identify open reading frames (ORFs) that are translated in a given sample. The Ribo...
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Ribosome profiling, or Ribo-seq, provides precise information about the position of actively translating ribosomes. It can be used to identify open reading frames (ORFs) that are translated in a given sample. The RiboTaper pipeline, and the ORFquant R package, leverages the periodic distribution of such ribosomes along the ORF to perform a statistically robust test for translation which is insensitive to aperiodic noise and provides a statistically robust measure of translation. In addition to accounting for complex loci with overlapping ORFs, ORFquant is also able to use Ribo-seq as a tool for distinguishing actively translated transcripts from non-translated ones, within a given gene locus. less
Gene coexpression networks (GCNs) are useful tools for inferring gene functions and understanding biological processes when properly constructed. Traditional microarray analysis is being more frequently replaced by bu...
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Gene coexpression networks (GCNs) are useful tools for inferring gene functions and understanding biological processes when properly constructed. Traditional microarray analysis is being more frequently replaced by bulk-based RNA-sequencing as a method for quantifying gene expression. This new technology requires improved statistical methods for generating GCNs. This chapter explores several popular methods for constructing GCNs using bulk-based RNA-Seq data, such as distribution-based methods and normalization techniques, implemented using the statistical programming language R. less
Analysis using mass spectrometry enables the characterization of metaproteomes in their native environments and overcomes the limitation of proteomics of pure cultures. Metaproteomics is a promising approach to link f...
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Analysis using mass spectrometry enables the characterization of metaproteomes in their native environments and overcomes the limitation of proteomics of pure cultures. Metaproteomics is a promising approach to link functions of currently actively expressed genes to the phylogenetic composition of the microbiome in their habitat. In this chapter, we describe the preparation of saliva samples and tongue swabs for nLC-MS/MSNLC-MS/MS measurements and their bioinformatic analysis based on the Trans-Proteomic Pipeline and Prophane to study the oral microbiome. less
Fluorescence in situ hybridization (FISH) allows researchers to visualize the spatial position and quantity of nucleic acids in fixed samples. Recently, considerable progress has been made in developing oligonucleotid...
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Fluorescence in situ hybridization (FISH) allows researchers to visualize the spatial position and quantity of nucleic acids in fixed samples. Recently, considerable progress has been made in developing oligonucleotide (oligo)-based FISH methods that have enabled researchers to study the three-dimensional organization of the genome at super-resolution and visualize the spatial patterns of gene expression for thousands of genes in individual cells. However, there are few existing computational tools to support the bioinformatics workflows necessary to carry out these experiments using oligo FISH probes. Here, we introduce paint server and homology optimization pipeline (PaintSHOP), an interactive platform for the design of oligo FISH experiments. PaintSHOP enables researchers to identify probes for their experimental targets efficiently, to incorporate additional necessary sequences such as primer pairs and to easily generate files documenting library design. PaintSHOP democratizes and standardizes the process of designing complex probe sets for the oligo FISH community. less
In this chapter, we introduce the application of R, a statistical programming language in the analysis of antibody array data. We start from a brief introduction of R itself and then cover data filtration and transfor...
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In this chapter, we introduce the application of R, a statistical programming language in the analysis of antibody array data. We start from a brief introduction of R itself and then cover data filtration and transformation, data visualization, differential expression analysis with/without variance correction, co-expression network, functional enrichment analysis, and statistical modeling. less
Network analysis facilitates examination of the interactions between different populations in a community. It can provide a range of metrics describing the social characteristics of each population and emergent struct...
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Network analysis facilitates examination of the interactions between different populations in a community. It can provide a range of metrics describing the social characteristics of each population and emergent structural properties of the community, which may be used to address novel ecological questions. Using a publicly available dataset, this chapter provides point-by-point code and instructions to infer and analyze a SPIEC-EASI (SParse InversE Covariance Estimation for Ecological Association Inference) network using free, open source software (R and Gephi). less
Next generation sequencing (NGS) is routinely used to study crucial aspects of biological systems, including differentially expressed genes identification, microbiome taxonomic composition and structure, enrichment of...
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Next generation sequencing (NGS) is routinely used to study crucial aspects of biological systems, including differentially expressed genes identification, microbiome taxonomic composition and structure, enrichment of specific cellular functions in a given environment, and so on. Current research laboratories are facing a serious lack in the availability of properly trained researchers capable of carrying out basic NGS analysis computational pipelines. This reflects a gap in most academic curricula concerning the basics of NGS data management, analysis, and interpretation. Indeed, most of the times, the knowledge necessary to undertake these tasks is acquired through the use of one-shot tutorial, without a thorough explanation of the concepts behind the practical steps. With this protocol we aim to fill this gap by providing teachers with a hands-on protocol to guide bachelor and master students in a more focused analysis of NGS data, from basic and standard operations on sequencing reads (e.g., quality check and trimming) to more advanced analysis techniques (e.g., data normalization). less
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