BOL: Related items

Metassembler: merging and optimizing de novo genome assemblies

Rahul Nayak — Tue, 08 May 2018 04:52:33 -0500

Metassembler combines multiple whole genome de novo assemblies into a combined consensus assembly using the best segments of the individual assemblies.

Genome assembly projects typically run multiple algorithms in an attempt to find the single best assembly, although those assemblies often have complementary, if untapped, strengths and weaknesses. We present our metassembler algorithm that merges multiple assemblies of a genome into a single superior sequence.

Address of the bookmark: https://sourceforge.net/projects/metassembler/?source=directory

RapClust: Accurate, Lightweight Clustering of de novo Transcriptomes using Fragment Equivalence Classes

Rahul Nayak — Thu, 04 Oct 2018 17:57:10 -0500

RapClust is a tool for clustering contigs from de novo transcriptome assemblies. RapClust is designed to be run downstream of the Sailfish or Salmon tools for rapid transcript-level quantification. Specifically, RapClust relies on the fragment equivalence classes computed by these tools in order to determine how seqeunce is shared across the transcriptome, and how reads map to potentially-related contigs across different conditions.

Address of the bookmark: https://github.com/COMBINE-lab/RapClust

NovoGraph: building whole genome graphs from long-read-based de novo assemblies

Jit — Thu, 15 Nov 2018 12:48:30 -0600

NovoGraph: building whole genome graphs from long-read-based de novo assemblies

An algorithmically novel approach to construct a genome graph representation of long-read-based de novo sequence assemblies. We then provide a proof of principle by creating a genome graph of seven ethnically-diverse human genomes.

https://f1000research.com/articles/7-1391/v1

Address of the bookmark: https://github.com/NCBI-Hackathons/NovoGraph

RNA-Bloom: a fast and memory-efficient de novo transcript sequence assembler

LEGE — Thu, 09 Jul 2020 03:13:06 -0500

RNA-Bloom is a fast and memory-efficient de novo transcript sequence assembler. It is designed for the following sequencing data types:

single-end/paired-end bulk RNA-seq (strand-specific/agnostic)
paired-end single-cell RNA-seq (strand-specific/agnostic)
nanopore RNA-seq (PCR cDNA/direct cDNA/direct RNA)

Written by Ka Ming Nip ✉️

Address of the bookmark: https://github.com/bcgsc/RNA-Bloom

Cancer's origins revealed

Jitendra Narayan — Thu, 15 Aug 2013 13:06:56 -0500

Researchers have provided the first comprehensive compendium of mutational processes that drive tumour development. Together, these mutational processes explain most mutations found in 30 of the most common cancer types. This new understanding of cancer development could help to treat and prevent a wide-range of cancers.

More at >> http://www.sanger.ac.uk/about/press/2013/130814.html

The Human Genome Project Video 3D Animation Introduction Low)

Sat, 24 Aug 2013 19:01:19 -0500

How DNA is Packaged (Advanced)

Mon, 23 Sep 2013 18:08:34 -0500

Each chromosome consists of one continuous thread-like molecule of DNA coiled tightly around proteins, and contains a portion of the 6,400,000,000 basepairs (DNA building blocks) that make up your DNA. Originally created for DNA Interactive ( http://www.dnai.org ). TRANSCRIPT: In this animation we'll see the remarkable way our DNA is tightly packed up to fit into the nucleus of every cell. The process starts with assembly of a nucleosome, which is formed when eight separate histone protein subunits attach to the DNA molecule. The combined tight loop of DNA and protein is the nucleosome. Six nucleosomes are coiled together and these then stack on top of each other. The end result is a fiber of packed nucleosomes known as chromatin. This structure, is then looped and further packaged using other proteins (which are not shown here) to give the final "chromosomal" shapes. It is this remarkable multiple folding which allows six feet of DNA to fit into the nucleus of each cell in our body. And a typical cell nucleus is so small that ten thousand could fit on the tip of a needle. It is important to realize that chromosomes are not always present, they form only when cells are dividing. At other times, as we can see here at the end of cell division, our DNA becomes less highly organized.)

Nucl2Vec: Local alignment of DNA sequences using Distributed Vector Representation

Jit — Tue, 16 Mar 2021 05:45:44 -0500

We demonstrate a novel approach forlocal alignment of DNA reads with respect to reference genome.For this process we have used Skip-gram model for creatingencoding(Nucl2Vec) and k-nearest neighbor for the alignment.With our new approach we have reduced computation cost forlocal alignment , while achieving accuracy comparable to existingdefacto standard BWA-MEM tool.

https://prakharg24.github.io/papers/401851.full.pdf

Address of the bookmark: https://prakharg24.github.io/papers/401851.full.pdf

Scripted DNA !!!

Jit — Mon, 17 Aug 2015 17:44:04 -0500

As per bioinformatician DNA is partially scripted ;) You dont believe in it. Please have a look at image carefully:)

DnaSP v5: a software for comprehensive analysis of DNA polymorphism data

Jit — Mon, 06 Feb 2017 04:45:37 -0600

DnaSP is a software package for a comprehensive analysis of DNA polymorphism data. Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets. Among other features, the newly implemented methods allow for: (i) analyses on multiple data files; (ii) haplotype phasing; (iii) analyses on insertion/deletion polymorphism data; (iv) visualizing sliding window results integrated with available genome annotations in the UCSC browser.

Address of the bookmark: http://www.ub.edu/dnasp/