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    Education: Training in Metagenomics Data Analysis @ NIH
    Submitted by Vijayaraj Nagarajan; posted on Monday, May 21, 2018

    June 12-15, 2018
    National Institutes of Health
    9000 Rockville Pike
    Building 60, Room 162
    Bethesda, MD 20892, USA[...]85aba


    Metagenomics is gaining importance due to low cost next generation sequencing technologies.This training will introduce participants to the end-to-endsolutions for analyzing metagenomicdata, starting from data quality analysis, alignment, community profiling, taxonomic comparison and novel taxa discovery.

    Hands-on Skills/Tools Taught:
    • Processing and Analysis mothur, FLASh
    • Analysis Permanova
    • Analysis ANOSIM
    • Marker analysis LEfSe
    • Marker analysis QIIME
    • Functional analysis PICRUSt
    • Metagenomics analysis A5miseq
    • Contig annotation MEGAN
    • Functional analysis bioBakery
    • Advanced visualizations phyloseq
    • Network analysis Cytoscape



    The Nuffield Council on Bioethics has released a briefing note asking what it sees as the big ethical questions on the use of artificial intelligence in healthcare. The note acknowledges the huge potential of AI in making healthcare more efficient and friendly, as well as making faster and more accurate diagnoses, but its focus is on the serious questions about the use of AI that the healthcare industry needs to tackle head on if public trust in AI in healthcare is to be gained.
    Software: New Atlas: Web tool squeezes more info out of DNA samples
    Submitted by J.W. Bizzaro; posted on Wednesday, May 16, 2018



    When it comes to determining a person's eye, hair and skin color based on a DNA sample, scientists typically need to compare that evidence sample to an existing reference sample. That's reportedly no longer the case, however, if they're using the new HIrisPlex-S DNA test system.


    Monday, August 13 – Friday, August 17, 2018
    University of Washington Campus, Seattle, WA, USA


    The University of Washington Center for Mendelian Genomics (UW-CMG) is offering a weeklong course on the analysis of next generation sequence data that will focus on strategies and tools for solving Mendelian disorders. The course is intended for data analysts/researchers who analyze next generation sequence data. Application available here:

    This is our 6th consecutive year running this workshop!


    The course will consist of lectures and hands-on exercises designed to help reinforce the lecture content.

    Monday: IT infrastructure; pipeline overview, CMG data, VCF files and Unix basics
    Tuesday: Sample/project level QC, study design & modes of analysis
    Wednesday: Annotation, interpreting CNV results, introduction to Gemini, and analysis using Gemini for autosomal recessive and de novo models
    Thursday: Analysis using Gemini for autosomal dominant models, candidate genes and variants, data sharing, and hands-on exercises
    Friday: Team projects, presentations, wrap up, additional questions, and feedback


    Space is limited and applications will be accepted until all spaces are filled. The cost to attend the Workshop is $300 (US). Attendees are responsible for costs associated with attending the workshop (i.e., airfare, housing, and incidentals).

    Lunch and snacks provided each day. Campus housing is available. A laptop and specific software are required for participation.

    Frustrated that their discovery scientists spend more time looking for and preparing relevant omics data than analysing it, Genestack's pharmaceutical clients challenged the company to solve this industry problem. The result is two new modules for its biodata platform, which will both be previewed at Bio-IT World Conference 2018. The omics data manager module allows biologists to interrogate and visualise transcriptomics data at scale, and the expression data miner module supports users to collaborate on omics studies to speed up research and enable data re-use and meta-analysis.

    The expression data miner module accelerates not only the workflow, but also new target discovery, by enabling biologists to look across multiple sources of transcriptomic data to better understand gene function. A custom interface enables biologists to interrogate and visualise data without support of a bioinformatician, for example viewing the highest expressed gene or most specific gene for any organ or organ system. The module also makes it easier to work with multiple genes and tissues/cell lines/cell types in one flexible, super-fast interface.

    The omics data manager module provides a collaborative environment for capturing and organising study and sample-level metadata along with required sequencing procedures, produced raw data and secondary analyses. The result is a single point of truth for all omics metadata, including sequencing and analysis requirements. Metadata is cleaned up with validation rules and ontologies. Results are easy to find and use in meta-analyses.

    Genestack CEO, Dr Misha Kapushesky, will be discussing how creating a collaborative ecosystem of multi-vendor systems can offer the best solution for discovery science, in the Pharmaceutical R&D Informatics Track of the Bio-IT World Conference and Expo 2018 on Wednesday 16 May at 2.55pm.

    Genestack is also at booth 436, and the new modules will be available to trial in Summer 2018.

    More information about the two modules is available here:
    Omics Data Manager:[...]ager/
    Expression Data Manager:[...]iner/

    June 5-8, 2018
    National Institutes of Health
    9000 Rockville Pike
    Building 60, Room 162
    Bethesda, MD 20892, USA[...]6b852


    R is the industry standard for creating scientific graphs and plots. There are several different R packages available for creating impressive plots, graphs and maps including plotly, ggplot2, ggvis, diagrammer – for diagrams, dygraphs – for time series data, leaflet – for plotting maps, graphviz – for graphs. This training will walk through participants in creating awesome, interactive, static, shareable plots using the popular R packages.


    Participants will get a brief hands-on introduction to the R platform, followed by hands-on walkthrough for creating several different popular plots, graphs and maps like scatter plots, density plots, correlation plots, pca plots, surface plots, dot plots, star plots, circular plots, trees, heatmaps, panel graphs, 3D graphs, network graphs. We will start from formatting data and go all the way to loading data, setting parameters, creating the images and saving the outputs.


    • Participants will work with RStudio
    • A copy of all the scripts used in the class to create plots, graphs and maps would be provided to the participants at the end of the training
    • Participants will also receive a cookbook style manual for all the hands-on exercises
    • After training support is also provided through exclusive members only forum



    A University of Kansas anthropological geneticist is part of an international research team working to shed light upon one of the unanswered questions concerning the peopling of the New World: Namely, what was the size of the original founding population of the Americas?

    Despite numerous genetic studies that have helped contribute to knowledge about how ancient groups populated the Americas, scientists have not reached a consensus about how many Native Americans made up the original population. This analysis of DNA sequences suggests the Native American founding population that migrated from Siberia consisted of approximately 250 people.



    Previous research on lifeforms that are closely related to animals – single-celled organisms such as choanoflagellates, filastereans and ichthyosporeans – has shown they share many genes with their animal cousins. This means that these genes are older than animals themselves and date back to some common ancestor of all these creatures. So the recycling of old genes into new functions, a kind of genome tinkering, must have been an important force in the origin of animals.

    But Professor Peter Holland and I wanted to find out which new genes emerged when animals evolved. We used sophisticated computer programs to compare 1.5m proteins (the molecules that genes contain the instructions for) across 62 living genomes, making a total of 2.25 trillion comparisons to find out which genes are shared between different organisms today.


    J. Paps and P.W.H. Holland. 2018. Reconstruction of the ancestral metazoan genome reveals an increase in genomic novelty. Nature Communications 9: 1730.[...]136-5



    Launched in 2016 with the sprawling ambition to build large genomes, the synthetic biology initiative known as Genome Project-write (GP-write) is now, slowly, getting down to specifics. Ahead of a meeting today in Boston, GP-write's leadership announced a plan to organize its international group of collaborators around a "community-wide project": engineering cells to resist viral infection.

    GP-write's original proposal to design and assemble an entire human genome from scratch seems to have receded from view since the project's rocky launch, when a private meeting of its founders sparked accusations of secrecy and speculations about lab-100made humans. A proposal published weeks later in Science described GP-write as a decade-long effort to reduce by more than 1000-fold the cost of engineering and testing large genomes consisting of hundreds of millions of DNA letters.



    A massive precision medicine initiative that has been years in the making from the National Institutes of Health is being rolled out at last.

    The All of Us initiative, which will be launched on May 6, aims to compile detailed health profiles of 1 million Americans, with a special focus on communities historically underrepresented in biomedical research.
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