BOL: Related items

DAVI: Deep learning-based tool for alignment and single nucleotide variant identification

Jit — Tue, 16 Mar 2021 05:41:33 -0500

DAVI consists of models for both global and local alignment and for variant calling. We have evaluated the performance of DAVI against existing state-of-the-art tool sets and found that its accuracy and performance is comparable to existing tools used for bench-marking. We further demonstrate that while existing tools are based on data generated from a specific sequencing technology, the models proposed in DAVI are generic and can be used across different NGS technologies as well as across different species

https://iopscience.iop.org/article/10.1088/2632-2153/ab7e19/pdf

Address of the bookmark: https://github.com/gguptaiitd/NEAT

Circleator

Jit — Sun, 25 Jun 2017 18:04:32 -0500

The Charm City Circleator--or Circleator for short--is a Perl-based visualization tool developed at the Institute for Genome Sciences in the University of Maryland's School of Medicine. Circleator produces circular plots of genome-associated data, like this one:

Common uses of the tool include:

Displaying the sequence and/or genes in a GenBank flat file.
Highlighting differences and/or similarities in gene content between related organisms.
Comparing SNPs and indels between closely-related strains or serovars.
Comparing gene expression values across multiple samples or timepoints.
Visualizing coverage plots of RNA-Seq read alignments.

Key Features

Circleator...

Builds on BioPerl and the input file formats that it supports, including:
- GenBank flat files, GFF, FASTA
Accepts a number of other commonly-used datatypes and file formats:
- BSR and TRF output, SAM/BAM files, VCF-encoded SNPs, tab-delimited files
Outputs publication-ready figures in the SVG (Scalable Vector Graphics) format.
Requires only a single configuration file whose layout mirrors that of the figure itself.
- Predefined configuration files and "track" types are supplied for common datasets.
- Advanced features allow limited analyses to be performed as a figure is drawn.
Includes an extensive set of regression tests.
Offers a prototype web-based GUI (under the "Ringmaster" project.)

https://github.com/jonathancrabtree/Circleator

Address of the bookmark: https://github.com/jonathancrabtree/Circleator

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

jobTree based python wrapper to run the genome simulation tool suite Evolver

Jit — Fri, 08 Dec 2017 16:26:32 -0600

evolverSimControl (eSC) can be used to simulate multi-chromosome genome evolution on an arbitrary phylogeny (Newick format). In addition to simply running evolver, eSC also automatically creates statistical summaries of the simulation as it runs including text and image files. Also included are convenience scripts to: check on a running simulation and see detailed status and logging information; extract fasta sequence files from the leaf nodes of a completed simulation; extract pairwise multiple alignment files (.maf) from leaf and branch nodes from a completed simulation and with the help of mafJoin, join them together into a single maf covering the entire simulation.

Address of the bookmark: https://github.com/dentearl/evolverSimControl

GPOPSIM: a simulation tool for whole-genome genetic data

Jit — Wed, 17 Jan 2018 03:47:46 -0600

GPOPSIM is a simulation tool for pedigree, phenotypes, and genomic data, with a variety of population and genome structures and trait genetic architectures. It provides flexible parameter settings for a wide discipline of users, especially can simulate multiple genetically correlated traits with desired genetic parameters and underlying genetic architectures.

Address of the bookmark: https://github.com/SCAU-AnimalGenetics/GPOPSIM

%MinMax: A versatile tool for calculating and comparing synonymous codon usage and its impact on protein folding.

Surabhi Chaudhary — Thu, 24 May 2018 02:53:31 -0500

%MM calculates whether a given gene sequence encodes amino acids using the most common codons possible, the least common codons possible, or (most typically) some combination of these extremes. See our PLoS ONE paper for more details on how the %MinMax algorithm works. %MinMax results are averaged over an 18-codon sliding window; hence the result for "codon window = 1" is the average codon usage for codons 1-18, codon window 2 = codons 2-19, etc.

Address of the bookmark: http://www.codons.org/

“One code to find them all”: a perl tool to conveniently parse RepeatMasker output files

Poonam Mahapatra — Mon, 04 Jun 2018 03:45:15 -0500

One code to find them all is a set of perl scripts to extract useful information from RepeatMasker about transposable elements, retrieve their sequences and get some quantitative information. Assemble RepeatMasker hits into complete TE copies, including LTR-retrotransposon Retrieve corresponding TE sequences, and flanking sequences, from the local fasta files Compute summary statistics for each TE family (number of TE copies, genome coverage...) Ambiguous cases such as nested TE can be assembled into copies automatically or manually Allow for working with a TE user-defined library Allow for working with only a user-chosen set of TE families http://doua.prabi.fr/software/one-code-to-find-them-all

Address of the bookmark: http://doua.prabi.fr/software/one-code-to-find-them-all

SALSA: A tool to scaffold long read assemblies with Hi-C

Jit — Fri, 15 Jun 2018 04:01:15 -0500

This code is used to scaffold your assemblies using Hi-C data. This version implements some improvements in the original SALSA algorithm. If you want to use the old version, it can be found in the old_salsa branch. To use the latest version, first run the following commands: cd SALSA make To run the code, you will need Python 2.7, BOOST libraries and Networkx(version lower than 1.2). If you consider using this tool, please cite our publication which describes the methods used for scaffolding. Ghurye, J., Pop, M., Koren, S., Bickhart, D., & Chin, C. S. (2017). Scaffolding of long read assemblies using long range contact information. BMC genomics, 18(1), 527. Link Ghurye, J., Rhie, A., Walenz, B.P., Schmitt, A., Selvaraj, S., Pop, M., Phillippy, A.M. and Koren, S., 2018. Integrating Hi-C links with assembly graphs for chromosome-scale assembly. bioRxiv, p.261149 Link For any queries, please either ask on github issue page or send an email to Jay Ghurye (jayg@cs.umd.edu).

Address of the bookmark: https://github.com/machinegun/SALSA

gSearch: a fast and flexible general search tool for whole-genome sequencing

Jit — Mon, 06 Aug 2018 17:19:15 -0500

gSearch compares sequence variants in the Genome Variation Format (GVF) or Variant Call Format (VCF) with a pre-compiled annotation or with variants in other genomes. Its search algorithms are subsequently optimized and implemented in a multi-threaded manner.

Address of the bookmark: http://ml.ssu.ac.kr/gSearch/index.html

LRCstats: a tool for evaluating long reads correction methods

Aaryan Lokwani — Wed, 22 Aug 2018 11:05:04 -0500

LRCstats is an open-source pipeline for benchmarking DNA long read correction algorithms for long reads outputted by third generation sequencing technology such as machines produced by Pacific Biosciences. The reads produced by third generation sequencing technology, as the name suggests, are longer in length than reads produced by next generation sequencing technologies, such as those produced by Illumina. However, long reads are plagued by high error rates, which can cause issues in downstream analysis. Long read correction algorithms reduce the error rate of long reads either through self-correcting methods or using accurate, short reads outputted by next generation sequencing technologies to correct long reads.

Address of the bookmark: https://github.com/cchauve/lrcstats