196,141 research outputs found
Analysis of HiChIP Data
No full textHiChIP is a novel method for the analysis of chromatin interactions based on in situ Hi-C that adds an immuno-precipitation (ChIP) step for the investigation of chromatin structures driven by specific proteins. This approach has been shown to be very efficient as it reliably reproduces Hi-C results and displays a higher rate of informative reads with a required lower amount of input cells when compared with other ChIP-based techniques (as ChIA-PET). Although HiChIP data preprocessing can be performed with the same methods developed for other Hi-C techniques, the identification of chromatin interactions needs to take into account specific biases introduced by the ChIP step. In this chapter we describe a computational pipeline for the analysis of HiChIP data obtained with the immuno-precipitation of Rad21 (part of the cohesin complex) in human embryonic stem cells before and after heat-shock treatment. We provide a detailed description of the preprocessing of raw data, the identification of chromatin interactions, the evaluation of the alterations induced by treatment, and, finally, the visualization of differential loops
Computational analysis of hi-c data
No full textThe chromatin organization in the 3D nuclear space is essential for genome functionality. This spatial organization encompasses different topologies at diverse scale lengths with chromosomes occupying distinct volumes and individual chromosomes folding into compartments, inside which the chromatin fiber is packed in large domains (as the topologically associating domains, TADs) and forms short-range interactions (as enhancer-promoter loops). The widespread adoption of high-throughput techniques derived from chromosome conformation capture (3C) has been instrumental in investigating the nuclear organization of chromatin. In particular, Hi-C has the potential to achieve the most comprehensive characterization of chromatin 3D structures, as in principle it can detect any pair of restriction fragments connected as a result of ligation by proximity. However, the analysis of the enormous amount of genomic data produced by Hi-C techniques requires the application of complex, multistep computational procedures that may constitute a difficult task also for expert computational biologists. In this chapter, we describe the computational analysis of Hi-C data obtained from the lymphoblastoid cell line GM12878, detailing the processing of raw data, the generation and normalization of the Hi-C contact map, the detection of TADs and chromatin interactions, and their visualization and annotation
Circr, a Computational Tool to Identify miRNA:circRNA Associations
No full textCircular RNAs (circRNAs) are known to act as important regulators of the microRNA (miRNA) activity. Yet, computational resources to identify miRNA:circRNA interactions are mostly limited to already annotated circRNAs or affected by high rates of false positive predictions. To overcome these limitations, we developed Circr, a computational tool for the prediction of associations between circRNAs and miRNAs. Circr combines three publicly available algorithms for de novo prediction of miRNA binding sites on target sequences (miRanda, RNAhybrid, and TargetScan) and annotates each identified miRNA:target pairs with experimentally validated miRNA:RNA interactions and binding sites for Argonaute proteins derived from either ChIPseq or CLIPseq data. The combination of multiple tools for the identification of a single miRNA recognition site with experimental data allows to efficiently prioritize candidate miRNA:circRNA interactions for functional studies in different organisms. Circr can use its internal annotation database or custom annotation tables to enhance the identification of novel and not previously annotated miRNA:circRNA sites in virtually any species. Circr is written in Python 3.6 and is released under the GNU GPL3.0 License at https://github.com/bicciatolab/Circr
APTANI2: Update of aptamer selection through sequence-structure analysis
No full textSummary: Here we present APTANI2, an expanded and optimized version of APTANI, a computational tool for selecting target-specific aptamers from high-throughput-Systematic Evolution of Ligands by Exponential Enrichment data through sequence-structure analysis. As compared to its original implementation, APTANI2 ranks aptamers and identifies relevant structural motifs through the calculation of a score that combines frequency and structural stability of each secondary structure predicted in any aptamer sequence. In addition, APTANI2 comprises modules for a deeper investigation of sequence motifs and secondary structures, a graphical user interface that enhances its usability, and coding solutions that improve performances
Computational methods for the integrative analysis of single-cell data
No full textRecent advances in single-cell technologies are providing exciting opportunities for dissecting tissue heterogeneity and investigating cell identity, fate and function. This is a pristine, exploding field that is flooding biologists with a new wave of data, each with its own specificities in terms of complexity and information content. The integrative analysis of genomic data, collected at different molecular layers from diverse cell populations, holds promise to address the full-scale complexity of biological systems. However, the combination of different single-cell genomic signals is computationally challenging, as these data are intrinsically heterogeneous for experimental, technical and biological reasons. Here, we describe the computational methods for the integrative analysis of single-cell genomic data, with a focus on the integration of single-cell RNA sequencing datasets and on the joint analysis of multimodal signals from individual cells
A 'waterproof' catalyst for the oxidation of secondary amines to nitrones with alkyl hydroperoxides
No full textCatalytic oxidation of secondary amines to nitrones using alkyl hydroperoxides as primary oxidant has been demonstrated for the first time. The titanium alkoxide catalyst is protected from co-product water by the combined use of a tightly binding trialkanolamine ligand and molecular sieves. Nitrones can be obtained in high yield (up to 98%) under homogeneous, anhydrous conditions and even in the absence of solvent. The reactions are fast (2–7 h) and good selectivity can be achieved with as little as 1% catalys
Effective Oxidation of Secondary Amines to Nitrones with Alkyl Hydroperoxides Catalysed by (Trialkanolaminato)titanium(IV) Complexes
No full textThe effective catalytic oxidation of secondary amines to nitrones with alkyl hydroperoxides as the primary oxidants is described. The titanium alkoxide catalysts are protected from the water co-product by the combined use of a tightly binding trialkanolamine ligand and molecular sieves. Nitrones can be obtained in high yields (up to 98%) under homogeneous, anhydrous conditions and even in the absence of solvent. The reactions are fast (2-7 h) and good selectivity and complete conversion can be achieved with as little as 1% catalys
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