BOL: Related items

NCBI to assist in Virus Hunting Data Science Hackathon

BioStar — Thu, 15 Nov 2018 12:55:01 -0600

NCBI Hackathon are pleased to announce the second installment of the SoCal Bioinformatics Hackathon. From January 9-11, 2019, the NCBI will help run a bioinformatics hackathon in Southern California hosted by the Computational Sciences Research Center at San Diego State University!

NCBI Hackathon specifically looking for folks who have experience in computational virus hunting or adjacent fields to identify known, taxonomically-definable and novel viruses from a few hundred thousand metagenomic datasets that we’ll put on cloud infrastructure. This event is for researchers, including students and postdocs, who are already engaged in the use of bioinformatics data or in the development of pipelines for virological analyses from high-throughput experiments. If this describes you, please apply! The event is open to anyone selected for the hackathon and willing to travel to SDSU (see below).

https://ncbiinsights.ncbi.nlm.nih.gov/2018/11/09/ncbi-sdsu-virus-hunting-data-science-hackathon-january-2019/

Genome in a Bottle (GIAB) Consortium

Jit — Sat, 25 Jan 2020 13:50:52 -0600

The Genome in a Bottle (GIAB) Consortium is a public-private-academic consortium hosted by NIST to develop the technical infrastructure (reference standards, reference methods, and reference data) to enable translation of whole human genome sequencing to clinical practice.

https://www.nist.gov/news-events/news/2016/09/nist-releases-new-family-standardized-genomes

Address of the bookmark: https://jimb.stanford.edu/giab/

AutoGluon: AutoML for Text, Image, and Tabular Data

Jit — Thu, 07 Jan 2021 05:33:17 -0600

AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models on text, image, and tabular data.

Address of the bookmark: https://github.com/awslabs/autogluon

NASA Open Science Data Repository

Abhi — Wed, 18 Dec 2024 11:54:47 -0600

The NASA Open Science Data Repository (OSDR) enables access to space-related data from experiments and missions that investigate biological and health responses of terrestrial life to spaceflight. The goal of OSDR is to enable multi-modal and multi-hierarchical fundamental space life science data be reused toward basic science, applied science, and operational outcomes for space exploration and knowledge discovery. These data include ‘omics, phenotypic, physiological, behavioral, hardware, environmental telemetry; raw, processed; tabular, text, code, bioimaging, and video.

https://www.nasa.gov/reference/osdr-data-processing/

Address of the bookmark: https://www.nasa.gov/osdr/

Translational Bioinformatics: Transforming 300 Billion Points of Data

Tue, 20 Aug 2013 19:03:47 -0500

Translational Bioinformatics: Transforming 300 Billion Points of Data into Diagnostics, Therapeutics, and New Insights into Disease Air date: Wednesday, June 20, 2012, 3:00:00 PM Time displayed is Eastern Time, Washington DC Local Description: There is an urgent need to translate genome-era discoveries into clinical utility, but the difficulties in making bench-to-bedside translations haven't been well described. The nascent field of translational bioinformatics may help. Dr. Butte's lab at Stanford University builds and applies tools that convert more than 300 billion points of molecular, clinical, and epidemiological data (measured by researchers and clinicians over the past decade) into diagnostics, therapeutics, and new insights into disease. Dr. Butte, a bioinformatician and pediatric endocrinologist, will highlight his lab's work on using publicly available molecular measurements to find new uses for drugs, discovering new treatable mechanisms of disease in type 2 diabetes, and evaluating patients presenting with whole genomes sequenced. The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. For more information, visit: The NIH Director's Wednesday Afternoon Lecture Series Author: Atul Butte, M.D., Ph.D., Stanford University Runtime: 01:07:42 Permanent link: http://videocast.nih.gov/launch.asp?17321

ANGES: reconstructing ANcestral GEnomeS maps

Abhimanyu Singh — Thu, 18 May 2017 05:27:08 -0500

This page contains the software ANGES 1.01, that aims at reconstucting ancestral genome maps from homologous markers in extant related genomes.

Download

Program, version 1.01 (July 10, 2012, documentation updated in August 2014)
Examples with results (featured ancestors: boreoeutherian, amniote, yeasts, Burkholderia, monocots); please refer to the documentation of the distribution above.

Address of the bookmark: http://paleogenomics.irmacs.sfu.ca/ANGES/

Understanding liftOver !

Rahul Nayak — Wed, 06 Jun 2018 10:00:20 -0500

LiftOver is a necesary step to bring all genetical analysis to the same reference build. LiftOver can have three use cases:

(1) Convert genome position from one genome assembly to another genome assembly

In most scenarios, we have known genome positions in NCBI build 36 (UCSC hg 18) and hope to lift them over to NCBI build 37 (UCSC hg19).

(2) Convert dbSNP rs number from one build to another

(3) Convert both genome position and dbSNP rs number over different versions

Run:

liftOver input.bed hg18ToHg19.over.chain.gz output.bed unlifted.bed

The outformat is as follow:

Deleted in new:
    Sequence intersects no chains
Partially deleted in new:
    Sequence insufficiently intersects one chain
Split in new:
    Sequence insufficiently intersects multiple chains
Duplicated in new:
    Sequence sufficiently intersects multiple chains
Boundary problem:
    Missing start or end base in an exon

For example:

If you liftOver chr4:6497-6497 from hg19 to GRch38 and it return "deleted in new".

It means chr4:6497-6497 is part of a genomic contig on hg19 that is not anymore mapped on GRch38 because the new assembly is now better built without including this contig.

DeCoSTAR: Reconstructing the Ancestral Organization of Genes or Genomes Using Reconciled Phylogenies

Shruti Paniwala — Fri, 03 Jan 2020 13:28:19 -0600

DeCoSTAR computes adjacency evolutionary scenarios using a scoring scheme based on a weighted sum of adjacency gains and breakages. Solutions, both optimal and near-optimal, are sampled according to the Boltzmann–Gibbs distribution centered around parsimonious solutions, and statistical supports on ancestral and extant adjacencies are provided. DeCoSTAR supports the features of previously contributed tools that reconstruct ancestral adjacencies, namely DeCo, DeCoLT, ART-DeCo, and DeClone. In a few minutes, DeCoSTAR can reconstruct the evolutionary history of domains inside genes, of gene fusion and fission events, or of gene order along chromosomes, for large data sets including dozens of whole genomes from all kingdoms of life.

Address of the bookmark: https://github.com/YoannAnselmetti/DeCoSTAR_pipeline

shovill: Assemble bacterial isolate genomes from Illumina paired-end reads

BioStar — Sat, 02 Jan 2021 07:05:36 -0600

Shovill is a pipeline which uses SPAdes at its core, but alters the steps before and after the primary assembly step to get similar results in less time. Shovill also supports other assemblers like SKESA, Velvet and Megahit, so you can take advantage of the pre- and post-processing the Shovill provides with those too.

Address of the bookmark: https://github.com/tseemann/shovill

kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome

Jit — Fri, 08 Dec 2017 16:48:40 -0600

Sept. 20, 2017 Version 3.1 released. Major upgrade. Version 3.1 fixes the problems with SNP annotation that arose when NCBI discontinued use of GI numbers. Please read carefully the Preface (page 3) and the File of annotated genomes section (pages 9-10) in the version 3.1 User Guide. Thanks to Tom Slezak for revsing the get_genbank_file3 script and to Tod Stuber (USDA) for testing version 3.1 even though he doesn't need the annotation feature. All users are encouraged to upgrade to version 3.1.

Address of the bookmark: https://sourceforge.net/projects/ksnp/files/