BOL: Related items

Chemical Elements of Bioinformatics

Rahul Agarwal — Tue, 03 Sep 2013 16:35:39 -0500

You must be familiar with periodic table and colour pattern, but this time you are going to amaze by new elements table by Eagle genomics. Just check it out and have fun :)

http://elements.eaglegenomics.com/

Mulan: MUltiple sequence Local AligNment and conservation visualization tool

Rahul Nayak — Thu, 20 Jul 2017 08:02:32 -0500

Mulan performs multiple (2 or more) sequence alignments with an efficient and rapid "full local" alignment strategy that ensures a recapitulation of evolutionary sequence rearrangements (such as inversions and reshuffling) in any of the species. It combines refine and tba tools to align either "draft" or "finished" quality sequences. Mulan provides a dynamic graphical interface to align and visualize conservation profiles for evolutionarily distant and closely related species.

Input formats, automated data upload from the UCSC Genome Browser, gene annotation, annotation of repetitive elements, and progress report were previously described in the zPicture instructions and we refer the users to these materials for more details. This introduction is mainly focused on some novel features unique to the Mulan.

Address of the bookmark: https://mulan.dcode.org/mulanInstructions.php

Circoletto: visualizing sequence similarity with Circos

Jit — Fri, 09 Feb 2018 10:23:40 -0600

Circoletto, an online visualization tool based on Circos, which provides a fast, aesthetically pleasing and informative overview of sequence similarity search results.

Online version and downloadable software package for offline use (source code in PERL) freely available at http://bat.ina.certh.gr/tools/circoletto/

Contact:ndarz@certh.gr

Address of the bookmark: http://tools.bat.infspire.org/circoletto/

SeqMonk:A tool to visualise and analyse high throughput mapped sequence data

Jit — Tue, 11 Sep 2018 04:39:38 -0500

SeqMonk is a program to enable the visualisation and analysis of mapped sequence data. It was written for use with mapped next generation sequence data but can in theory be used for any dataset which can be expressed as a series of genomic positions. It's main features are:

Import of mapped data from mapped data (BAM/SAM/bowtie etc)
Creation of data groups for visualisation and analysis
Visualisation of mapped regions against an annotated genome.
Flexible quantitation of the mapped data to allow comparisons between data sets
Statistical analysis of data to find regions of interest
Creation of reports containing data and genome annotation

Address of the bookmark: http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/

Genome sequence-based (sub-)species delineation.

Abhimanyu Singh — Wed, 12 Dec 2018 08:31:14 -0600

The GGDC web service reports digital DDH for a universal and accurate delineation of prokaryotic (sub-)species without inheriting the pitfalls of classic DDH, and also calculates differences in genomic G+C content.

http://ggdc.dsmz.de/ggdc_background.php#

Genome-to-Genome Distance Calculator 2.1

http://ggdc.dsmz.de/ggdc.php

Address of the bookmark: http://ggdc.dsmz.de/

TRITEX sequence assembly pipeline for Triticeae genomes

Jit — Tue, 20 Aug 2019 09:47:14 -0500

The pipeline is open-source and hosted in a public Bitbucket repository.

TRITEX has been run on highly inbred genotypes of barley (Hordeum vulgare), tetraploid wheat (Triticum turgidum) and hexaploid wheat (T. aestivum) with reasonable results: super-scaffold N50 values in the range of dozens of Mb and pseudomolecules with better gene space representation than a BAC-by-BAC assembly. It has never been tested and is not expected to work on heterozygous or autopolyploid genomes.

A protocol for generating chromosome-conformation capture sequencing (Hi-C) data suitable for use with the pipeline is described in Himmelbach et al. 2018. Refer to the technical notes of 10X Genomics on how to generate Chromium data.

Address of the bookmark: https://tritexassembly.bitbucket.io/

Shouji: a fast and efficient pre-alignment filter for sequence alignment

Jit — Mon, 04 Nov 2019 07:09:45 -0600

The ability to generate massive amounts of sequencing data continues to overwhelm the processing capacity of existing algorithms and compute infrastructures. In this work, we explore the use of hardware/software co-design and hardware acceleration to significantly reduce the execution time of short sequence alignment, a crucial step in analyzing sequenced genomes.

We introduce Shouji, a highly parallel and accurate pre-alignment filter that remarkably reduces the need for computationally-costly dynamic programming algorithms. The first key idea of our proposed pre-alignment filter is to provide high filtering accuracy by correctly detecting all common subsequences shared between two given sequences. The second key idea is to design a hardware accelerator design that adopts modern FPGA (field-programmable gate array) architectures to further boost the performance of our algorithm.

More at https://github.com/CMU-SAFARI/Shouji

Address of the bookmark: https://github.com/CMU-SAFARI/Shouji

AccessSyRI: finding genomic rearrangements and local sequence differences from whole-genome assemblies

Jit — Sat, 01 Feb 2020 13:38:49 -0600

AccessSyRI: finding genomic rearrangements andlocal sequence differences from whole-genome assemblies

SyRI, a pairwise whole-genome comparison tool for chromosome-level assemblies. SyRI starts by finding rearranged regions and then searches for differences in the sequences, which are distinguished for residing in syntenic or rearranged regions. This distinction is important as rearranged regions are inherited differently compared to syntenic regions.

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1911-0

Address of the bookmark: https://github.com/schneebergerlab/syri

Submit your SARS-CoV-2 sequence data to GenBank

Neel — Thu, 09 Apr 2020 18:28:25 -0500

Submit your SARS-CoV-2 sequence data to GenBank and SRA with our new submission landing page. Submission is simple and streamlined *and* there’s a rapid turnaround. https://submit.ncbi.nlm.nih.gov/sarscov2/

Quickly and easily add your SARS-CoV-2 sequence data to the growing public archive with new, special features and support from NCBI. new SARS-CoV-2 sequence submission landing page will help you get started. GenBank submissions are accessioned and released in approximately 1-2 working days, and Sequence Read Archive (SRA) submissions typically processed and released within hours. Submission is simple!

More information is available on NCBI Insights. https://ncbiinsights.ncbi.nlm.nih.gov/2020/04/09/sars-cov2-data-streamlined-submission-rapid-turnaround/

MMseqs2: ultra fast and sensitive sequence search and clustering suite

Manisha Mishra — Mon, 18 Jan 2021 10:47:56 -0600

MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein and nucleotide sequence sets. MMseqs2 is open source GPL-licensed software implemented in C++ for Linux, MacOS, and (as beta version, via cygwin) Windows. The software is designed to run on multiple cores and servers and exhibits very good scalability. MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it achieves almost the same sensitivity. It can perform profile searches with the same sensitivity as PSI-BLAST at over 400 times its speed.

Address of the bookmark: https://github.com/soedinglab/MMseqs2