Thursday, 19 November 2015

AIA-Konica Minolta Digital Health Hackathon

- AIA Group Limited and Konica Minolta, Inc. today jointly launched the 'AIA - Konica Minolta Digital Health Accelerator' in Singapore. The 12 week programme supports entrepreneurs and businesses to deliver innovative solutions through integrating data to healthcare delivery.
The Singaporean Government's spend on Healthcare in Singapore is expected to double to SG$8 billion by the end of 2015, from SG$4 billion in 2011. 'Digital Health' solutions present one of the most promising growth segments in the healthcare sector, as innovative solutions empower people to better manage and improve their health and provide better diagnostics and treatment options using sensors, data and imaging that are now within the consumer ecosystem.

 To learn about the accelerator program see here 

Monday, 9 November 2015

JDs : what's Product Content Projects and Illumina Concierge Service projects?

Looking at job descriptions again ... the question that is circling in my head is ....

what's Product Content Projects and Illumina Concierge Service projects?
Sounds POSH ....

All About You 

Position Summary: 

As a Bioinformatics Scientist in the Product Content group of the Life Science and Applied Markets Business Unit, you will play an integral role in enabling custom genomics solutions for Illumina customers. Primary responsibilities will include providing bioinformatics support to commercial teams, customers, and within the Product Content group.

Tasks and Responsibilities: 
  • Support sales and marketing teams by providing bioinformatics analysis of sequencing and array content for pre-sale activities.
  • Provide bioinformatics support to Product Content Project managers to assist with Illumina Concierge Service projects
  • Create and maintain an internal bioinformatics tools repository with documentation
  • Generate summary statistics for new custom panels for use by sales and marketing teams
  • Create workflows to perform routine analyses

We seek demonstrated accomplishment in some or all of the following skills:
  • Familiarity with linux and command line driven analysis tools
  • Ability to create workflows using bash scripting, perl, python, C++ or R
  • Experience with HPC Linux clusters and similar large systems
  • Next Gen sequencing technology, tool usage, and data analysis
  • Microarray technology, tool usage, and data analysis
  • Understanding & familiarity with public genetic databases and methods to find and extract data from the databases (NCBI, UCSC, ENSEMBL, ENCODE, 1000genomes, NHGRI)
  • Familiarity with linkage disequilibrium and imputation analyses
  • Ability to manage changing priorities and multi-task
  • Strong initiative and desire to tackle difficult problems
  • Critical problem solving and data analysis
  • Superior written and verbal communication skills
  • Ability to travel on occasion 1-3 times per year 

  • PhD (preferred) in computer science, mathematics, statistics, bioinformatics, or equivalent.
  • Genomics experience strongly preferred 

Thursday, 29 October 2015

New publication on tumour organoids using SOLiD sequencing

I am surprised to see the SOLiD machine still churning out sequence data, I had assumed that it's reached it's EOL.
but good to see that it's still serving the scientific community under the good hands of Edwin Cuppen.

Preserved genetic diversity in organoids cultured from biopsies of human colorectal cancer metastases

  1. Emile E. Voesta,c,d,i,1
  1. Contributed by Hans Clevers, August 24, 2015 (sent for review April 23, 2015; reviewed by Walter F. Bodmer and Calvin Kuo)


    Chemotherapy has been proven in clinical studies to improve overall survival significantly. Unfortunately, there is a significant degree of heterogeneity in tumor chemosensitivity, often resulting in unnecessary treatment and needless exposure to toxic side-effects. A platform is needed that can identify preemptively which patients will or will not benefit from treatment. Tumor organoids, 3D cultures of cancer cells, present such an individualized platform. In this study we demonstrate that organoid cultures can be established from metastatic biopsy specimens with a high success rate and genetically represent the metastasis they were derived from. These data support the translation of this innovative technology to the clinic as an ex vivo screening platform for tailoring treatment.


    Tumor organoids are 3D cultures of cancer cells. They can be derived from the tumor of each individual patient, thereby providing an attractive ex vivo assay to tailor treatment. Using patient-derived tumor organoids for this purpose requires that organoids derived from biopsies maintain the genetic diversity of the in vivo tumor. In this study tumor biopsies were obtained from 14 patients with metastatic colorectal cancer (i) to test the feasibility of organoid culture from metastatic biopsy specimens and (ii) to compare the genetic diversity of patient-derived tumor organoids and the original tumor biopsy. Genetic analysis was performed using SOLiD sequencing for 1,977 cancer-relevant genes. Copy number profiles were generated from sequencing data using CopywriteR. Here we demonstrate that organoid cultures can be established from tumor biopsies of patients with metastatic colorectal cancer with a success rate of 71%. Genetic analysis showed that organoids reflect the metastasis from which they were derived. Ninety percent of somatic mutations were shared between organoids and biopsies from the same patient, and the DNA copy number profiles of organoids and the corresponding original tumor show a correlation of 0.89. Most importantly, none of the mutations that were found exclusively in either the tumor or organoid culture are in driver genes or genes amenable for drug targeting. These findings support further exploration of patient-derived organoids as an ex vivo platform to personalize anticancer treatment.

    Inconsistency in Microbiome Studies due to Variable Approaches to DNA Sequencing and Data Analysis

    Article Summary:
    Human Longevity, Inc. and Venter Institute Scientists Publish Paper Demonstrating Inconsistency in Microbiome Studies due to Variable Approaches to DNA Sequencing and Data Analysis —SAN DIEGOOct. 27, 2015 /PRNewswire/ -- Human Longevity, Inc. (HLI), the genomics-based, technology-driven company, announced today that its researchers along with those from the J. Craig Venter Institute and theUniversity of California, San Diego, have published a paper in the journal, Proceedings of the National Academy of Sciences (PNAS), outlining the confusing and conflicting microbiome results generated by a variety of next generation sequencing technology. They also outline recommendations for new research community standards in the microbiome research field given these differences. The paper is being published this week in the early online edition of PNAS.

    The two methods that did not require PCR resulted in lower error rates and higher-quality reads for the mock community compared with the PCR-based methods. Moreover, the four different libraries showed significant variation in the relative abundance of microbial members of the mock community and the stool samples.

    Thursday, 22 October 2015


    Tina Graves-Lindsay, Leader of the Reference Genomes Group at the McDonnell Genome Institute (MGI) at Washington University St. Louis, kicked off the session talking about the research involved in achieving the best human whole genome assembly. As a member of the Genome Reference Consortium, Tina’s team has been working to improve the current reference, GRCh38, and fixing a few genes that are not optimally represented for all individuals or ancestries.

    The sequence plan starts with generating 60x coverage of PacBio long read data for a de novo assembly. From there, MGI incorporates BioNano or Dovetail data to create scaffolds that in some cases nearly cover entire chromosome arms. Since MGI is targeting difficult to assemble regions of the genome, they sequence bacterial artificial chromosomes (BACs) to fill the targeted regions and then incorporate all this data together to generate a very high quality whole genome assembly labeled the “Gold Genome”.

    Slides for the 1000 Genomes Project tutorial at ASHG 2015

    The 1000 Genomes project is holding a tutorial at ASHG 2015.

    This tutorial will cover and overview of the 1000 Genomes Data, how to access it and how it can be used.
    1. 7:15 – 7:30 pm Overview of the data set Hyun Min Kang - University of Michigan
    2. 7:30 – 7:45 pm How to access the data Holly Zheng Bradley - European Bioinformatics Institute
    3. 7:45 – 8:00 pm Structural variants Eugene Gardener - University of Maryland
    4. 8:00 – 8:15 pm Functional variation Stephen Montgomery - Stanford University
    5. 8:15 – 8:30 pm Admixture Alicia Martin - Broad Institute
    6. 8:30 – 8:45 pm Using LDLink Mitch Machiela - National Cancer Institute7. 8:45 – 9:00 pm Q&A
    No registration is needed for this meeting. Slides will be posted after the meeting is finished.
    Source link:

    Friday, 9 October 2015

    What is personal genomics?

    Wikipedia calls it as

    "Personal genomics is the branch of genomics concerned with the sequencing and analysis of the genome of an individual. The genotyping stage employs different techniques, including single-nucleotide polymorphism (SNP) analysis chips (typically 0.02% of the genome), or partial or full genome sequencing. Once the genotypes are known, the individual's genotype can be compared with the published literature to determine likelihood of trait expression and disease risk."

    the irony of the matter is that no one man is an island. 

    The allure of personal genomics is invariably the ability to use something like a tricorder or minION to collect data about your personal genome and suggest an action for you, specific to your genome, so that you may act on the full potential of your GATTACA

    you might have been told how special you are. One in a billion. To make sense of what your genes are saying, you actually need to find rare individuals in sufficient quantities to make a statistical inference that the bunch of you who share this variant in your DNA that predisposes you to a XX% risk of being an XX person. 

    the (100% - XX% ) chance of you being otherwise is often not explained well enough. Where would you find this missing variability? 

    There's epigenetics which i would argue is more PERSONAL genomics than the PG offerings out there. These variations account for the environmental impact that is quantifiable by genetic testing. Most tests are research use only I presume. 
    There's structural variations which potentially affects the genome more than SNPs, and trying to predict the phenotypic effects of SVs will probably plague the next generation of bioinformaticians and geneticists.
    There's also the rare variants which may explain the missing heritability 
    Then there's the very intimate microbiome which consists of microbes that may hold an entirely different genome from you but affects your health in such a strong way that I think personal genomics should include this category.

     So while cheaper sequencing technologies has enabled projects like The Personal Genome Project (PGP) or there's still a lot more to YOU than what your genes say about you through SNPs. 

    That said, I am happy to genotype my SNPs with 23andMe kits or a kit from Xcode Life Sciences  to make an informed decision on maximising my exercise potential (and minimising the harm), but I need to be mindful to not ignore there's stuff that I may not carry personally but can make me into a roadkill statistic (1 in the 6426 ) or suffer an heart attack as a result of a stupid co-worker ... 

    Live long and prosper , don't sweat the small stuff. (unless they are rare and have a combinatorial effect greater than its sum)

    Datanami, Woe be me