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17

There’s an XKCD comic which explains the problem. Unfortunately, that comic is too big to post here. Briefly, a p-value of 0.1 says (roughly) that there’s a 10% chance (0.1) of the observed result being as extreme1 as it is simply due to chance (sampling variation from a population), assuming the null hypothesis is true. Often, 5% is more or less ...


15

You've already gotten a decent answer to this, but I'll provide my own thoughts on the subject. Yes It's necessary. It is absolutely something you should do before beginning an experiment, and preferably something you should do in collaboration with the person who is going to be helping you analyze your data. To address a couple points: You'll see all ...


11

For very small systems like the worm c.elegans it must be possible to record from all neurons at the same time, at least optically. While it is true that whole organism optical recording is technically possible in C. elegans, I'm not aware of any published work where all neurons were identified and recorded from simultaneously and then combined with ...


10

In order to calculate power, you need to know the variance of the data being collected. You can only estimate this prior to actually gathering the data itself, so any a priori power calculation is itself just an estimate. This is why sometimes you will see small studies being conducted as pilot studies (for example, see (1)), which enable variance to be ...


9

One thing that's certain is that the activity of bees varies according to time of day, so more important than how long you record for is probably at what time you record. If you always record at the same time of day, this should allow a reasonable comparison between results of different days. For example, recording from time 14:30 to 14:35 every day could be ...


8

To answer this question in its entirety we have to split it into two questions: What are the underlying mechanisms of carcinogenity? One of the main mechanism behind carcinogenity is the mutagenity of the cancerogens, i.e. the ability to cause mutations, that are abberations of the cell DNA leading to uncontrolled proliferation. This classical paper ...


8

Epidemiological studies analyze human observational cohort data to try to statistically link disease risk and biomarkers. For instance, it is know a well know fact that smoking increases the risk of lung cancer, yet before the 1950s it was widely considered otherwise until observational evidence proved irrefutable (Levin, 1950). Confounding However, ...


7

I understand this in the following way: For each probe you have two sets of measurements, one for ER+ and one for ER-. What you do is a T-test (to my understanding is that the "parametric" just emphasizes that T-test is a parametric test) on these two sets, testing if their mean is significantly different (they refer to this as "separated"). You repeat this ...


7

Assumptions: Blonde hair is Homozygous Recessive and that the traits are strictly Mendelian. The parental generation must be both heterozygotes as at least one child is Blonde (bb). So your cross is Bb x Bb. Your square is going to look like this: _B_ _b_ _B_ BB Bb _b_ bB bb So of the ...


6

if you are using NMR structures you might be making the mistake of using several superimposed structures - it would be nice to develop with x-ray structures at less than 2.0 A resolution for starters. Some of the models at low resolution can be sloppy, but submitted after 1994 or so will not have any center to center distances as that's when the x-ray ...


5

I'm not an expert on Shannon-Weaver Index, but according to wikipedia it is the same as exponentially transformed Renyi entropy. If it is the case, you can compare them since they are scale invariant summary statistics. If you want error bars, you can always try resampling methods such as bootstrapping. Hypothesis testing can also be done with bootstrapping, ...


5

I guess you meant the population size stability. It is considered that the biosystems will increase their capacity of adaptation when evolving in very fluctuating environments. I believe the population stability is embedded in the adaptability of individuals. There is a measurement about it, evolvability, when the environment changes, the faster the ...


5

here I found an answer. Not sure how accurate is is, though. Data seems to be from the US Here is a rewrite of parts of that article: 266 days before birth, all we have is a fertilized egg. (~33% chance of living birth). The odds are calculated using data from in-vitro fertilization, and the next stage is 66%. In in-vitro, some 50% of the eggs cannot ...


4

Due to my own woeful ignorance on the subject, I have been reading up on statistical methods recently. From what (little) I understand, the real answer to this question is: Yes, but only if you are doing Neyman-Pearson hypothesis testing and Absolutely not, if you are using Fisher p-values That is, the question isn't formulated correctly, because power ...


4

In GWA studies you tend to analyze your "lead" SNPs in regions where genotypes are correlated (known as linkage disequilibrium). If you find an association between another SNP with the outcome, and this SNP is correlated with the original variant, you can perform a conditional analysis where you adjust for the original SNP in the model. This is to test if ...


4

Just adding a little bit here. Estimating changes in connectivity based on STDP is hard http://klab.smpp.northwestern.edu/wiki/images/2/2b/Stevenson_Inferring_Plasticity_2011.pdf but yes - these questions are enough to keep a big field busy for a long time.


4

Ideally, you would gather preliminary statistics to design the experiment. If you have a high variability, and your observation window is short, then small effects will be swamped by the variability. However, if what you are looking for has a big effect in the number of bees, then counting for a shorter time is going to be fine. A rule of thumb would be to ...


3

About diseases in general, that would concern the health dept. of the respective country government, and the govt. is the most probable source for such numbers. However, orpha.net has two reports with numbers concerning hereditary diseases, have a look at http://www.orpha.net/consor/cgi-bin/Education_Home.php?lng=EN#REPORT_RARE_DISEASES


3

q-value is the corrected p-value to account for multiple testing (i.e. you are testing thousands of genes). Those with q-value <0.05 are significant experiment-wise. Cuffdiff uses Benjamini-Hochberg correction to compute FDR (i.e. q-value). The calculation does not depend on the number of replicates it's based on the distribution of p-values those, yes, ...


3

A good place to start would be Statistical Methods for Microarray Data Analysis. I'd also suggest papers from the labs of Terry Speed, Gary Churchill, John Quackenbush, and Gordon Smyth. Also, I found some papers that specifically reflect on your exact issue: how to apply the methods developed for DNA microarrays to analyze protein arrays. Eckel-Passow et ...


3

TL;DR: A sixth order probability curve of cancer does not mean six steps. The order of the curve has nothing to do with the number or sequence of mutations. Causes why ABCD could be more likely than DABC exist and have been extensively studied Repair and control ("defence") mechanisms are what does the 'ordering' of steps by selecting for mutations which ...


3

I would caution you against using phrases such as "completely cured" or even "cured". This goes beyond our technical ability to detect the presence of tumor cells within someone's body. All we can conclude is progression-free survival (i.e. living with cancer that does not get worse) or disease-free survival (i.e. or no signs or symptoms of the tumor). Many ...


3

In cancer research, we never talk about "curing" cancer because, as others have pointed out, there is no way of being sure that all of the cancer has been eradicated. You may be interested to consider "Recurrence" statistics which describe the amount of time from when a cancer was treated to when it was detected to have returned. If you are willing to do ...


3

I'm one of the STRING maintainers, so I hope I can clear things up a bit. Gene co-occurrence: genomic context methods are very useful for bacterial genomes, but not so much for eukaryotes. However, they are actually the most unbiased data we have, since there's no human influence (beyond selecting species for sequencing). Benchmarking: Interactions ...


3

This is directly following the advice of Lande & Arnold (1983), saying: Linear multiple regression can be used first to estimate the forces of directional selection, $\beta$, and their standard errors. Then a quadratic multiple regression (16) or (Al), can be used to estimate the forces of stabilizing selection, $\gamma$, with their standard ...


2

I'd argue this actually belongs on CrossValidated. Essentially, the problem is one of how a GWAS study is conducted. By looking over an entire genome for associations, you're actually conducting thousands or millions of experiments, not the single experiment most statistics were designed to handle. As such, you're going to find many results that meet the ...


2

This isn't the answer you're probably looking for, but I'd recommend not bothering with what they mean about their test in particular ... maybe they were really using a mann-whitney but their software (SPLUS) labeled it as a "non-parametric t test" for the non-formally-trained-statistical-end-user [update]: I misread the text and thought you (and the ...


2

Pianka's index of niche overlap is defined in his papers from 1973 and 1974, as: $O_{kl}=\dfrac{\sum_i^n{p_{il} p_{ik}}}{\sqrt{\sum_i^n{p_{il}^2} \sum_i^n{p_{ik}^2}}}$ where $O_{kl}$ is the resource overlap between species $k$ and $l$, and since the index is symmetric $O_{kj} = O_{lk}$. $p_{ib}$ represents the proportion of resource $i$ that is used by ...


2

There are lots of statistical algorithms that allow you to evaluate the similarity between two given sequences. For instance, blast allows you a rapid comparison between your sequence and other sequences in a database; while Clustal, with a similar functioning, allows you to compare a set of given sequences between them. They are very simple algorithms, but ...


2

To choose the right statistical method (it is more than just saying "use the t-test") you need to think about your experiment. A good starting point is this figure from Bitesizebio: There are two relevant articles on that website: Let’s Talk About Stats: Comparing Two Sets of Data Let’s Talk About Stats: Comparing Multiple Datasets Probably also ...



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