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12

This is a very subtle question and I encourage you to read the Wikipedia articles on these different subjects (t-test, chi-squared test, p-value, etc) because the authors worked hard to combat common misconceptions about these commonly used statistical tests. Here is a rather oversimplified rule-of-thumb for these different tests: t-test: Used when you are ...


5

The NCBI Taxonomy statistics page displays the following information: There are currently 73540 genera, 331418 species, and 23127 taxa of higher order. Since the number of taxa decreases with the genericity of the taxon, there are probably around 20000 families, give or take a few thousand.


5

(This isn't an answer, but hopefully it will help get it past the experimental design into just solving the equation.) Where did you get that α0 was not determined from their data? On p. 10 (256), they state, "The prevailing direction of effective pollen dispersal within neighbourhoods (a0) that gave the best fit of the model was 91 degrees from north (...


3

The paper by Graczyk (2007) is probably relevant for you. It says that the Gini index is a measure of reactive selectivity of kinases, with values close to zero indicating no selectivity and values close to one indicating high selectivity, and it is created in direct parallel to the Gini index in economics, which is used to describe economic inequality. In ...


3

If the values on the branches indeed represent bootstrap supports, they indicate the percentage of times a clade has been obtained in a set of trees computed from resamplings of a starting data matrix. This is irrespective of the topology within the clade or outside it, because this is merely a count of bipartitions (a branch corresponds to a bipartition of ...


3

In your 5 points you basically cover several concepts of evolutionary biology. 1) The number of mutations depend on mutation rate. The mutation rate varies along genome sequences, species and individuals. According to the recent DECODE study (Kong et al., 2012) a human mother transmit on average 15 mutations to her offspring and a human father transmit on ...


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

Usually if something is not expected to behave according to some scheme then the measured values for such a parameter are assumed to be normal. It is not just with gene expression but with all types of measurements like dimensions of an object, luminosity of an electric bulb, range of a bullet etc. In any measurement, the random error is modeled using ...


3

Additional Info T-test As A.Kennard said t-test is applied when the random variable is normally distributed. How to know what is normally distributed is a relevant question. Regular measures which suffer some random error of measurement are normally distributed. The mean values estimated from different samples (the experiment that generates that sample may ...


3

The Plant List has 642 families listed: http://www.theplantlist.org/1.1/about/#changes. For a quick comparison, Wikipedia lists 522 fish families: en.wikipedia.org/wiki/List_of_fish_families 136 mammal families: en.wikipedia.org/wiki/Mammal_classification 61 amphibian families: en.wikipedia.org/wiki/List_of_amphibians 57 reptile families: en.wikipedia....


2

I don't know about other groups, but about plants, number of families depends on the system you follow. Recent version of The Plant List (1.1) estimates about 352 000 species of Angiosperms and lists over 400 families. See http://www.theplantlist.org/1.1/browse/A/ It is very good and reliable source of information. Second very good source about plant ...


2

I am not sure I'm answering your question but I hope this will help. There are two main models of genetic drift in biology: Moran model and Wright-Fisher model. The Wright-Fisher model implies picking $N$ beads (where $N$ is the population size) with replacement in order to form the new population. Therefore, the change in allele frequency (due to genetic ...


2

Define a "Hit" (based on some cutoff- evalue, score etc) Get output in the tabular format Count number of hits per query — it is usually given in the header; if you want to look for some selected hits (based on some cutoff, then you can parse the file and find out) Example file (header): # BLASTN 2.2.27+ # Query: TCONS_00036712 gene=XLOC_017996 # Database:...


2

Remi.b's answer is great, but here's something less technical if that's what you're looking for: Genetic mutations happen ALL THE TIME. Every time a cell divides, there is an error rate of about one per billion. That's a very low error rate per division, but when you multiply it by the number of divisions, times the number of cells, times the number of ...


2

You can use ordinal multinomial regression (also known as ordered logit) if the response is ordered. These methods are basically extensions of logistic regressions, but using e.g. a cumulative logit instead of the logit. However, there are a number of different assumptions you need to consider. For instance, are you going to use a proportional-odds ...


2

The advice is to not generally use ERCC spike-ins at all because of variations introduced by pipetting at the volumes they recommend. The thread also explains how to use DESeq and EdgeR with spike-in normalisation, with the process being easier significantly with DESeq, where you can use the calcSizeFactors on a count matrix of spike-in reads alone. With ...


2

Normalization of expression data is a big topic with new methods being published regularly. When approaching something like this you generally want look at people who have done similar things to what you've done, and then once you understand why they did what they did, you can ask what you need to do to answer your questions. Always keep your biological ...


1

Generally speaking for RNA-seq data, you don't want to correct for GC content or other gene level effects (e.g. length) because you compare expression values between conditions WITHIN a gene. For this reason, it is recommended to use raw counts and not normalized values such as FPKM. See Section 2.7 of the edgeR user manual. This recent benchmark comparing ...


1

Don't think about mutagenized animals, think about mutagenized genomes. Depending on when the mutagenesis is carried out, and how efficient it is, a very small number of males could give rise to thousands of mutagenized F1 progeny, each carrying a uniquely mutagenized genome. That is the number to focus on. Typically, in fruit flies and soil nematodes the ...


1

One trivial situation in which this can happen is when the tissue used for expression studies is heterogeneous. Different cells express different levels of the gene. Bimodality can be observed when the system can actually occupy two stable states; i.e. a gene can either have a high expression or a low expression. When you sample the population you would ...


1

The testing of an ordinal scale requires non-parametric statistical tests. Mean and standard deviation are invalid parameters for descriptive statistics whenever data are on ordinal scales, as are any parametric analyses based on the normal distribution. The report of Allen & Seaman, 2007 describes a number of possible tests: Nonparametric procedures—...


1

Someone else can probably elaborate on how "peripheral lymphocyte culture" works, but this is what the statistical results suggest to me: The results suggested that the SCE in occupational workers was significantly higher than that in controls (11.31 vs 6.37, P < 0.001). This is a two-sample t-test. Occupational workers were pooled into one group ...


1

I can see why you might be confused! The authors chose bad notation, since the way they wrote it $w_i$ clearly depends not just on the choice of anenomefish species $i$ but also on the choice of anenome species $j$. And it is not clear how exactly they are performing their sum in the definition of SSR: sum over all possible anenome-anenomefish species pairs ...


1

I'm not a statistician, but I think the comments have got it right. There is never a reason to omit P values, statistical power or some other measure that you have done something that is not a random outcome. For the sake of reference lets define the terms you reference: Eta squared is a ratio of the variances of two sets of measurements Cohen's d is a ...


1

It has been associated with polymorphisms with the CD4 gene, which is usually implicated in type I diabetes. The wikipedia article for vitiligo also mentions studies for the NALP1 gene. NALP1 is expressed at high levels in T cells and Langerhan cells, white blood cells that are involved in skin autoimmunity.



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