Biology subjects

Vitzthum, C.

Publications and source records attributed to Vitzthum, C..

4 recordsLinked to original sources

bioRxiv2021

The 4D Nucleome Data Portal: a resource for searching and visualizing curated nucleomics data

The 4D Nucleome (4DN) Network aims to elucidate the complex structure and organization of chromosomes in the nucleus and the impact of their disruption in disease biology. We present the 4DN Data Portal (https://data.4dnucleome.org/), a repository for datasets generated in the 4DN network and relevant external datasets. Datasets were generated with a wide range of experiments, including chromosome conformation capture assays such as Hi-C and other innovative sequencing and microscopy-based assays probing chromosome architecture. All together, the 4DN data portal hosts more than 1800 experiment sets and 34000 files. Results of sequencing-based assays from different laboratories are uniformly processed and quality-controlled. The portal interface allows easy browsing, filtering, and bulk downloads, and the integrated HiGlass genome browser allows interactive visualization and comparison of multiple datasets. The 4DN data portal represents a primary resource for chromosome contact and other nuclear architecture data for the scientific community.

genomics↗

bioRxiv2021

Pairs and Pairix: a file format and a tool for efficient storage and retrieval for Hi-C read pairs

SummaryAs the amount of three-dimensional chromosomal interaction data continues to increase, storing and accessing such data efficiently becomes paramount. We introduce Pairs, a block-compressed text file format for storing paired genomic coordinates from Hi-C data, and Pairix, an open-source C application to index and query Pairs files. Pairix (also available in Python and R) extends the functionalities of Tabix to paired coordinates data. We have also developed PairsQC, a collapsible HTML quality control report generator for Pairs files. AvailabilityThe format specification and source code are available at https://github.com/4dn-dcic/pairix, https://github.com/4dn-dcic/Rpairix and https://github.com/4dn-dcic/pairsqc. Contactpeter_park@hms.harvard.edu or burak_alver@hms.harvard.edu

bioinformatics↗

bioRxiv2018

Tibanna: software for scalable execution of portable pipelines on the cloud

SummaryWe introduce Tibanna, an open-source software tool for automated execution of bioinformatics pipelines on Amazon Web Services (AWS). Tibanna accepts reproducible and portable pipeline standards including Common Workflow Language (CWL), Workflow Description Language (WDL) and Docker. It adopts a strategy of isolation and optimization of individual executions, combined with a serverless scheduling approach. Pipelines are executed and monitored using local commands or the Python Application Programming Interface (API) and cloud configuration is automatically handled. Tibanna is well suited for projects with a range of computational requirements, including those with large and widely fluctuating loads. Notably, it has been used to process terabytes of data for the 4D Nucleome (4DN) Network.\n\nAvailabilitySource code is available on GitHub at https://github.com/4dn-dcic/tibanna.

bioinformatics↗

bioRxiv2017

PaSD-qc: Quality control for single cell whole-genome sequencing data using power spectral density estimation

Single cell whole-genome sequencing (scWGS) is providing novel insights into the nature of genetic heterogeneity in normal and diseased cells. However, scWGS introduces DNA amplification-related biases that can confound downstream analysis. Here we present a statistical method, with an accompanying package PaSD-qc (Power Spectral Density-qc), that evaluates the quality of single cell libraries. It uses a modified power spectral density to assess amplification uniformity, amplicon size distribution, autocovariance, and inter-sample consistency as well as identifies aberrantly amplified chromosomes. We demonstrate the usefulness of this tool in evaluating scWGS protocols and in selecting high-quality libraries from low-coverage data for deep sequencing.

bioinformatics↗