Thursday, July 31, 2014

Cancer biomarkers: Written in blood

http://www.nature.com/news/cancer-biomarkers-written-in-blood-1.15624

DNA circulating in the bloodstream could guide cancer treatment — if researchers can work out how best to use it.

But researchers have found ways to get a richer view of a patient's cancer, and even track it over time. When cancer cells rupture and die, they release their contents, including circulating tumour DNA (ctDNA): genome fragments that float freely through the bloodstream. Debris from normal cells is normally mopped up and destroyed by 'cleaning cells' such as macrophages, but tumours are so large and their cells multiply so quickly that the cleaners cannot cope completely.

The first practical use of circulating DNA came in another field. Dennis Lo, a chemical pathologist now at the Chinese University of Hong Kong, reasoned that if tumours could flood the blood with DNA, surely fetuses could, too. In 1997, he successfully showed that pregnant women carrying male babies had fetal Y chromosomes in their blood6. That discovery allowed doctors to check a baby's sex early in gestation without disturbing the fetus, and ultimately to screen for developmental disorders such as Down's syndrome without resorting to invasive testing. It has revolutionized the field of prenatal diagnostics (see Nature 507, 19; 2014).

Despite its promise, ctDNA is not yet ready for a starring role in the clinic. For one thing, the most sensitive techniques for detecting it, such as BEAMing, rely on some knowledge of which mutations to look for. This knowledge can be provided by taking a biopsy, sequencing its mutations, designing patient-specific molecular probes that target them, and using those probes to analyse later blood samples — a laborious approach that must be repeated for each patient. The alternative is to use exome sequencing, as Rosenfeld's team did. This requires no previous knowledge about the cancer, but it is prohibitively expensive to sequence and analyse every sample at the depth required to detect rare mutant fragments.

Monday, July 28, 2014

Experts question Google’s new ‘moonshot’ project: mapping human genome biomarkers

Canadian experts have concerns about a report that Google Inc. is planning to create a map of the biomarkers in the “healthy” human genome.

Researchers have told The Globe and Mail they would welcome the search giant to this area of study, which they say is underfunded, but they questioned how useful Google’s project would be based on the relatively small number of people it would involve (just 175 initially).

Friday, July 25, 2014

Frequentists vs Bayesian

http://oikosjournal.wordpress.com/2011/10/11/frequentist-vs-bayesian-statistics-resources-to-help-you-choose/

Most ecologists use the frequentist approach. This approach focuses on P(D|H), the probability of the data, given the hypothesis. That is, this approach treats data as random (if you repeated the study, the data might come out differently), and hypotheses as fixed (the hypothesis is either true or false, and so has a probability of either 1 or 0, you just don’t know for sure which it is). This approach is called frequentist because it’s concerned with the frequency with which one expects to observe the data, given some hypothesis about the world. The P values you see in the “Results” sections of most empirical ecology papers are values of P(D|H), where H is usually some “null” hypothesis.

Bayesian statistical approaches are increasingly common in ecology. Bayesian statistics focuses on P(H|D), the probability of the hypothesis, given the data. That is, this approach treats the data as fixed (these are the only data you have) and hypotheses as random (the hypothesis might be true or false, with some probability between 0 and 1). This approach is called Bayesian because you need to use Bayes’ Theorem to calculate P(H|D).


I guess I lean more towards Bayesian statistics! There's probably life on Mars =)


Thursday, July 24, 2014

Biological insights from 108 schizophrenia-associated genetic loci

Biological insights from 108 schizophrenia-associated genetic loci 
Abstract: Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.

Subject terms: Genome-wide association studies
http://www.nature.com/nature/journal/v511/n7510/full/nature13595.html

Genomic inflation factors under polygenic inheritance 
Abstract:  Population structure, including population stratification and cryptic relatedness, can cause spurious associations in genome-wide association studies (GWAS). Usually, the scaled median or mean test statistic for association calculated from multiple single-nucleotide-polymorphisms across the genome is used to assess such effects, and ‘genomic control' can be applied subsequently to adjust test statistics at individual loci by a genomic inflation factor. Published GWAS have clearly shown that there are many loci underlying genetic variation for a wide range of complex diseases and traits, implying that a substantial proportion of the genome should show inflation of the test statistic. Here, we show by theory, simulation and analysis of data that in the absence of population structure and other technical artefacts, but in the presence of polygenic inheritance, substantial genomic inflation is expected. Its magnitude depends on sample size, heritability, linkage disequilibrium structure and the number of causal variants. Our predictions are consistent with empirical observations on height in independent samples of ~4000 and ~133 000 individuals.

Keywords: genome-wide association study, genomic inflation factor, polygenic inheritance
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3137506/

In population genetics, linkage disequilibrium is the non-random association of alleles at two or more loci, that descend from single, ancestral chromosomes
linkage equilibrium D = 0, is when PA * PB = PAB (ie. A is found and B is found)

http://en.wikipedia.org/wiki/Linkage_disequilibrium

Linkage disequilibrium makes tightly linked 
variants strongly correlated producing cost 
savings for association studies



http://www.sph.umich.edu/csg/abecasis/class/666.03.pdf

 Population stratification is the presence of a systematic difference in allele frequencies between subpopulations in a population possibly due to different ancestry, especially in the context of association studies.

The two most widely used approaches to this problem include genomic control, which is a relatively nonparametric method for controlling the inflation of test statistics,[2] and structured association methods,[3] which use genetic information to estimate and control for population structure.

Genomic Control works by using markers that are not linked with the trait in question to correct for any inflation of the statistic caused by population stratification
http://en.wikipedia.org/wiki/Population_stratification 

The Hardy–Weinberg principle states that allele and genotype frequencies in a population will remain constant from generation to generation in the absence of other evolutionary influences.

Thursday, July 17, 2014

STAP Papers Retracted

http://www.genomeweb.com//node/1411071?utm_source=SilverpopMailing&utm_medium=email&utm_campaign=Daily%20Scan%20Blog:%20STAP%20Papers%20Retracted,%20This%20Week%20in%20Cell,%20Women%20in%20Elite%20Labs,%20more%20-%2007/02/2014%2001:05:00%20PM

The pair of Nature papers published in January that purported to show how to generate embryonic stem cell-like cells using stimuli like low pH has been retracted by the journal.

The retraction notice from Riken's Haruko Obokata and her colleagues says that "[s]everal critical errors have been found in our Article and Letter" and that a subsequent investigation of those errors by Riken found evidence of research misconduct.

Plasma proteins predict conversion to dementia from prodromal disease

http://www.sciencedirect.com/science/article/pii/S1552526014024546

Abstract
Background
The study aimed to validate previously discovered plasma biomarkers associated with AD, using a design based on imaging measures as surrogate for disease severity and assess their prognostic value in predicting conversion to dementia.

Methods
Three multicenter cohorts of cognitively healthy elderly, mild cognitive impairment (MCI), and AD participants with standardized clinical assessments and structural neuroimaging measures were used. Twenty-six candidate proteins were quantified in 1148 subjects using multiplex (xMAP) assays.

Results
Sixteen proteins correlated with disease severity and cognitive decline. Strongest associations were in the MCI group with a panel of 10 proteins predicting progression to AD (accuracy 87%, sensitivity 85%, and specificity 88%).

Conclusions
We have identified 10 plasma proteins strongly associated with disease severity and disease progression. Such markers may be useful for patient selection for clinical trials and assessment of patients with predisease subjective memory complaints.

Keywords
Plasma; Mild cognitive impairment; Pathology; Alzheimer's disease; Biomarker; Prediction and magnetic resonance imaging

Monday, July 14, 2014

UBC Pharmaceutical Sequencing Centre - HiSeq 2500 and MiSeq

http://psas.pharmacy.ubc.ca/equipment/illumina-hiseq-2500-and-miseq/

Pricing

HiSeq Rapid Run 2×100: 375-425k clusters/mm2, 50-60 Gb data, 600 million reads – $2,400
HiSeq High Output 2×100: 375k-425k clusters/mm2, 33-40 Gb data, 37.5 million reads – $2,400

Thursday, July 10, 2014

Get credited for TELUS spam text messages (SMS)

TELUS offers this service that if you forward your text messages to 7726 and add the word SPAM in the text body, they will credit you back. 

http://mobility.telus.com/search/?search_cat=Support&search_q=spam

In Android, to forward, just go to the text message, press and hold on the text message and voila, select "Forward" from the popup

Friday, July 4, 2014

reCAPTCHA AJAX API

https://developers.google.com/recaptcha/docs/display?hl=es-ES

Note if the widget is not showing up, it might be because the public key only works with the domain and sub-domains that it was generated from!

To verify, you will need to setup a controller on the server side to validate the challenge and response fields.

UBC Reading Group Mailing lists

https://www.cs.ubc.ca/~csgsa/pmwiki.php/Main/ReadingGroupListing