scholarly journals FAN-C: a feature-rich framework for the analysis and visualisation of chromosome conformation capture data

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Kai Kruse ◽  
Clemens B. Hug ◽  
Juan M. Vaquerizas

AbstractChromosome conformation capture data, particularly from high-throughput approaches such as Hi-C, are typically very complex to analyse. Existing analysis tools are often single-purpose, or limited in compatibility to a small number of data formats, frequently making Hi-C analyses tedious and time-consuming. Here, we present FAN-C, an easy-to-use command-line tool and powerful Python API with a broad feature set covering matrix generation, analysis, and visualisation for C-like data (https://github.com/vaquerizaslab/fanc). Due to its compatibility with the most prevalent Hi-C storage formats, FAN-C can be used in combination with a large number of existing analysis tools, thus greatly simplifying Hi-C matrix analysis.

Author(s):  
Kai Kruse ◽  
Clemens B. Hug ◽  
Juan M. Vaquerizas

Chromosome conformation capture data, particularly from high-throughput approaches such as Hi-C and its derivatives, are typically very complex to analyse. Existing analysis tools are often single-purpose, or limited in compatibility to a small number of data formats, frequently making Hi-C analyses tedious and time-consuming. Here, we present FAN-C, an easy-to-use command-line tool and powerful Python API with a broad feature set covering matrix generation, analysis, and visualisation for C-like data (https://github.com/vaquerizaslab/fanc). Due to its comprehensiveness and compatibility with the most prevalent Hi-C storage formats, FAN-C can be used in combination with a large number of existing analysis tools, thus greatly simplifying Hi-C matrix analysis.


2015 ◽  
Vol 14 ◽  
pp. CIN.S26470 ◽  
Author(s):  
Richard P. Finney ◽  
Qing-Rong Chen ◽  
Cu V. Nguyen ◽  
Chih Hao Hsu ◽  
Chunhua Yan ◽  
...  

The name Alview is a contraction of the term Alignment Viewer. Alview is a compiled to native architecture software tool for visualizing the alignment of sequencing data. Inputs are files of short-read sequences aligned to a reference genome in the SAM/BAM format and files containing reference genome data. Outputs are visualizations of these aligned short reads. Alview is written in portable C with optional graphical user interface (GUI) code written in C, C++, and Objective-C. The application can run in three different ways: as a web server, as a command line tool, or as a native, GUI program. Alview is compatible with Microsoft Windows, Linux, and Apple OS X. It is available as a web demo at https://cgwb.nci.nih.gov/cgi-bin/alview . The source code and Windows/Mac/Linux executables are available via https://github.com/NCIP/alview .


2021 ◽  
Vol 10 (17) ◽  
Author(s):  
Quentin Lamy-Besnier ◽  
Romain Koszul ◽  
Laurent Debarbieux ◽  
Martial Marbouty

ABSTRACT The Oligo-Mouse-Microbiota (OMM12) gnotobiotic murine model is an increasingly popular model in microbiota studies. However, following Illumina and PacBio sequencing, the genomes of the 12 strains could not be closed. Here, we used genomic chromosome conformation capture (Hi-C) data to reorganize, close, and improve the quality of these 12 genomes.


2020 ◽  
Author(s):  
Marlies E. Oomen ◽  
Adam K. Hedger ◽  
Jonathan K. Watts ◽  
Job Dekker

Abstract Current chromosome conformation capture techniques are not able to distinguish sister chromatids. Here we describe the protocol of SisterC1: a novel Hi-C technique that leverages BrdU incorporation and UV/Hoechst-induced single strand breaks to identify interactions along and between sister chromatids. By synchronizing cells, BrdU is incorporated only on the newly replicated strand, which distinguishes the two sister chromatids2,3. This is followed by Hi-C4 of cells that can be arrested in different stages of the cell cycle, e.g. in mitosis. Before final amplification of the Hi-C library, strands containing BrdU are specifically depleted by UV/Hoechst treatment. SisterC libraries are then sequenced using 50bp paired end reads, followed by mapping using standard Hi-C processing tools. Interactions can then be assigned as inter- or intra-sister interactions based on read orientation.


BMC Genomics ◽  
2016 ◽  
Vol 17 (1) ◽  
Author(s):  
Idan Gabdank ◽  
Sreejith Ramakrishnan ◽  
Anne M. Villeneuve ◽  
Andrew Z. Fire

2020 ◽  
Vol 36 (12) ◽  
pp. 3930-3931 ◽  
Author(s):  
Oliver B Scott ◽  
A W Edith Chan

Abstract Summary ScaffoldGraph (SG) is an open-source Python library and command-line tool for the generation and analysis of molecular scaffold networks and trees, with the capability of processing large sets of input molecules. With the increase in high-throughput screening data, scaffold graphs have proven useful for the navigation and analysis of chemical space, being used for visualization, clustering, scaffold-diversity analysis and active-series identification. Built on RDKit and NetworkX, SG integrates scaffold graph analysis into the growing scientific/cheminformatics Python stack, increasing the flexibility and extendibility of the tool compared to existing software. Availability and implementation SG is freely available and released under the MIT licence at https://github.com/UCLCheminformatics/ScaffoldGraph.


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