BOL: Related items

Panacus : A Counting Tool for Pangenome Graphs

Neel — Fri, 14 Jun 2024 14:42:28 -0500

panacus is a tool for calculating statistics for GFA files. It supports GFA files with P and W lines, but requires that the graph is blunt, i.e., nodes do not overlap and consequently, each link (L) points from the end of one segment (S) to the start of another.

panacus supports the following calculations:

coverage histogram
pangenome growth statistics
path-/group-resolved coverage table

Address of the bookmark: https://github.com/marschall-lab/panacus

When DNA Data Tells the Wrong Story - CrossFit assist to resolve !

BioStar — Fri, 04 Sep 2026 03:41:38 -0500

Imagine comparing humans and chimpanzees to discover which genes make us different. You have millions of RNA-sequencing reads—but there is a catch: the computer may align these reads more easily to one species' genome than the other.

Suddenly, a technical error can look like a biological difference.

This is the problem Kenneth A. Barr and Yoav Gilad tackle with CrossFilt, a new computational tool introduced in Genome Biology journal.

CrossFilt acts like a careful referee. It keeps only sequencing reads that can be reliably compared across species, filtering out reads that could create alignment bias.

When tested on human, chimpanzee, and rhesus macaque data, CrossFilt reduced false discoveries and produced more reliable cross-species comparisons.

The message is simple: before asking what makes species different, we need to make sure our methods aren't creating those differences.

In genomics, sometimes the most important discovery is finding—and removing—the bias hiding in the data.

Read more at https://link.springer.com/article/10.1186/s13059-026-04082-2?

TelomereHunter

Jit — Fri, 02 Feb 2018 04:23:59 -0600

TelomereHunter is a tool for estimating telomere content from human whole-genome sequencing data. It is designed to take BAM files from a tumor and a matching control sample as input. However, it is also possible to run TelomereHunter with one input file. TelomereHunter extracts and sorts telomeric reads from the input sample(s). For the estimation of telomere content, GC biases are taken into account. Finally, the results of TelomereHunter are visualized in several diagrams.

TelomereHunter is available for download at the following address: https://pypi.python.org/pypi/telomerehunter/

Address of the bookmark: http://www.dkfz.de/en/applied-bioinformatics/telomerehunter/telomerehunter.html

CHSMiner: a GUI tool to identify chromosomal homologous segments

Jit — Sat, 18 Nov 2017 16:55:49 -0600

Background

The identification of chromosomal homologous segments (CHS) within and between genomes is essential for comparative genomics. Various processes including insertion/deletion and inversion could cause the degeneration of CHSs.

Results

Here we present a Java software CHSMiner that detects CHSs based on shared gene content alone. It implements fast greedy search algorithm and rigorous statistical validation, and its friendly graphical interface allows interactive visualization of the results. We tested the software on both simulated and biological realistic data and compared its performance with similar existing software and data source.

Conclusion

CHSMiner is characterized by its integrated workflow, fast speed and convenient usage. It will be useful for both experimentalists and bioinformaticians interested in the structure and evolution of genomes.

https://github.com/zhenwang100/CHSMiner

Address of the bookmark: https://almob.biomedcentral.com/articles/10.1186/1748-7188-4-2

CAMSA :: a tool for Comparative Analysis and Merging of Scaffold Assemblies

Rahul Nayak — Thu, 28 Dec 2017 09:10:26 -0600

CAMSA – is a tool for Comparative Analysis and Merging of Scaffold Assemblies, distributed both as a standalone software package and as Python library under the MIT license.

Main features:

works with any number of scaffold assemblies in de-novo non-progressive fashion
allows to simultaneously work with scaffold assemblies obtained from any in silico and in vitro techniques, supporting multiple existing formats via built-in converters
creates an extensive report with several comparative quality metrics (both on assembly level and on the level of individual assembly points)
constructs a merged combined scaffold assembly
provides an interactive framework for a visual comparative analysis of the given assemblies

Address of the bookmark: https://cblab.org/camsa/

Porechop: tool for finding and removing adapters from Oxford Nanopore reads

Rahul Nayak — Tue, 29 May 2018 07:33:44 -0500

Porechop is a tool for finding and removing adapters from Oxford Nanopore reads. Adapters on the ends of reads are trimmed off, and when a read has an adapter in its middle, it is treated as chimeric and chopped into separate reads. Porechop performs thorough alignments to effectively find adapters, even at low sequence identity.

Porechop also supports demultiplexing of Nanopore reads that were barcoded with the Native Barcoding Kit, PCR Barcoding Kit or Rapid Barcoding Kit.

Address of the bookmark: https://github.com/rrwick/Porechop

HiGlass: a tool for exploring genomic contact matrices and tracks.

Jit — Mon, 11 Jun 2018 09:44:49 -0500

HiGlass is a tool for exploring genomic contact matrices and tracks. Please take a look at the examples and documentation for a description of the ways that it can be configured to explore and compare contact matrices. To load private data, HiGlass can be run locally within a Docker container. The HiC data in the examples below is from Rao et al. (2014) http://higlass.io/

Address of the bookmark: http://higlass.io/

LSC :a long read error correction tool

Jit — Thu, 02 Aug 2018 07:39:46 -0500

Getting Started

These simple steps will help you integrate LSC into your transcriptomics analysis pipeline.

Read the LSC_requirements for running LSC.
Download and set-up the LSC package.
Follow the tutorial to see how LSC works on some example data.
Read the manual if anything is unclear.
You're ready, Happy LSCing!

Latest publication

Kin Fai Au, Jason Underwood, Lawrence Lee and Wing Hung Wong
Improving PacBio Long Read Accuracy by Short Read Alignment [Manuscript]
PLoS ONE 2012. 7(10): e46679. doi:10.1371/journal.pone.0046679

Address of the bookmark: https://www.healthcare.uiowa.edu/labs/au/LSC/

LoRMA: A tool for correcting sequencing errors in long reads

Abhimanyu Singh — Thu, 06 Sep 2018 16:21:01 -0500

An error correction method that uses long reads only. The method consists of two phases: first, we use an iterative alignment-free correction method based on de Bruijn graphs with increasing length of k-mers, and second, the corrected reads are further polished using long-distance dependencies that are found using multiple alignments. According to our experiments, the proposed method is the most accurate one relying on long reads only for read sets with high coverage. Furthermore, when the coverage of the read set is at least 75×, the throughput of the new method is at least 20% higher.

conda install -c atgc-montpellier lorma

Address of the bookmark: https://gite.lirmm.fr/lorma/lorma-releases/wikis/home

Synima: a Synteny imaging tool for annotated genome assemblies

Abhimanyu Singh — Tue, 30 Oct 2018 10:49:13 -0500

Synima written in Perl, which uses the graphical features of R. Synima takes orthologues computed from reciprocal best BLAST hits or OrthoMCL, and DAGchainer, and outputs an overview of genome-wide synteny in PDF. Each of these programs are included with the Synima package, and a pipeline for their use. Synima has a range of graphical parameters including size, colours, order, and labels, which are specified in a config file generated by the first run of Synima – and can be subsequently edited. Synima runs quickly on a command line to generate informative and publication quality figures. Synima is open source and freely available from https://github.com/rhysf/Synima under the MIT License.

Address of the bookmark: https://github.com/rhysf/Synima