R is heritability
Publish: 2021-05-20 23:33:20
1. There are two methods. One is to use the genetic algorithm toolbox of MATLAB; Another is to write their own genetic algorithm to solve the problem. The second method, you can find a lot of genetic algorithm matlab code on the Internet, I can also provide. In the first case, there are certain limitations.
2. Suppose you want to calculate the linear correlation coefficient of two groups of values, there are two methods: the first method: type the function: = correl (data column or row 1, data column or row 2). The function is to calculate the linear correlation coefficient of data column or row 1 and data column or row 2. For example, there is a column of data A1: A20
3. 1. Crossover before mutation or mutation before crossover? 2. Is the number of parents selected for crossover 2n? N is the population size 3, crossover probability + mutation probability = 100%? Or it doesn't matter? It can be understood in this way. Generally, indivials are selected in order and random numbers are generated one by one. From the point of view of selection operation, there is no order among indivials in the population
4. Calculation of 16S high-throughput sequencing data using R software vegan package α Biodiversity index
here is the method of calculating biodiversity index with Vegan package in R software:
please search for R software installation by yourself
Step 1: make data matrix
the second step is to read the data into R
named variable divdata
divdata = read. CSV & quot; diverdata.csv", The third step is diversity analysis
calling vegen package
the fourth step is data saving
here is the method of calculating biodiversity index with Vegan package in R software:
please search for R software installation by yourself
Step 1: make data matrix
the second step is to read the data into R
named variable divdata
divdata = read. CSV & quot; diverdata.csv", The third step is diversity analysis
calling vegen package
the fourth step is data saving
5. 90% probability, the calculated chi square value will be less than 4.6, so that the chi square value greater than the threshold indicates that the attributes and classes are not independent and cannot be merged. If the threshold is large, interval merging will be carried out many times, and the number of discrete intervals is small and the interval is large. In this case, the user can consider these two parameters: the maximum number of cells and the maximum number of intervals. The user specifies the upper and lower limits of the number of intervals, at most several intervals and at least several intervals. 11. Chimerge algorithm is recommended to use. 90,. 95,. 99 confidence level, and the maximum interval number is between 10 and 15. For example, iris data set is taken as the data set to be discretized, and chimerge algorithm is used to analyze the four numerical attributes
6. Occurrence ratio is used to determine the category of dependent variable. In this paper, we introce the concept of probability, define the occurrence of an event as y = 1, and the non occurrence of an event as y = 0, then the probability of occurrence of an event is p, and the probability of non occurrence of an event is 1-p. we regard P as a linear function of X;
7. Function, you can calculate some important things through some functions.
8. The difference between gene chip and SNP Technology:
1 gene chip
the basic principle of gene chip is to hybridize the known nucleotide sequence with the labeled target nucleotide sequence, and carry out qualitative and quantitative analysis through signal detection. Gene chip can integrate a large number of molecular recognition probes on the surface of a tiny substrate (silicon, glass, etc.), which can analyze a large number of genes in parallel at the same time and carry out large amount of information detection and analysis
gene chips are widely used, which can be divided into cDNA microarray (or cDNA microarray chip) and oligonucleotide array (or chip) according to the types of probes used. Special chips are prepared according to different application fields, such as toxicology chip, virus detection chip (such as hepatitis virus detection chip), p53 gene detection chip, etc. According to its function, it can be divided into microarray for detecting gene quality and quantity. Quantity detection includes: detection of mRNA level, presence or absence of pathogens and comparative genomic gene number, which can be completed by both oligonucleotide chip and cDNA chip, but cDNA chip has more advantages. Qualitative detection includes: DNA sequencing and re sequencing, gene mutation and SNP detection, mainly using oligonucleotide chip< Single nucleotide polymorphism (SNP) refers to the variation of a single nucleotide in the genome, including substitution, transversion, deletion and insertion. Theoretically, each SNP site can have four different forms of variation, but in fact, there are only two, namely transformation and transversion, with the ratio of 2:1. SNPs appear most frequently in CG sequences, and most of them are converted from C to T. the reason is that C in CG is often methylated and becomes thymine after spontaneous deamination. Generally speaking, SNP refers to the single nucleotide variation with variation frequency more than 1%. There is about one SNP per 1000 bases in the human genome, and the total number of SNPs in the human genome is about 3 × 106
the occurrence of most diseases is related to the combined effects of environmental factors and genetic factors. It is generally believed that the diseases are caused by environmental harmful factors on the basis of indivial genetic susceptibility. Different populations and indivials have different susceptibility to diseases, resistance and other biological characteristics (such as drug responsiveness). The genetic basis is the variability of human genome DNA sequence, the most common of which is SNP. The characteristic of susceptibility gene is that gene variation itself does not directly lead to the occurrence of disease, but only increases the potential risk of disease. Once the external harmful factors intervene, it can lead to the occurrence of disease. In addition, in drug therapy, the variation of susceptibility gene results in different efficacy and side effects
with the development of human genome project, more and more people believe that SNPs in the genome can help to explain indivial phenotypic differences, susceptibility of different groups and indivials to diseases, especially complex diseases, tolerance to various drugs and response to environmental factors. Therefore, the search and study of SNP has become one of the contents and goals of human genome project.
1 gene chip
the basic principle of gene chip is to hybridize the known nucleotide sequence with the labeled target nucleotide sequence, and carry out qualitative and quantitative analysis through signal detection. Gene chip can integrate a large number of molecular recognition probes on the surface of a tiny substrate (silicon, glass, etc.), which can analyze a large number of genes in parallel at the same time and carry out large amount of information detection and analysis
gene chips are widely used, which can be divided into cDNA microarray (or cDNA microarray chip) and oligonucleotide array (or chip) according to the types of probes used. Special chips are prepared according to different application fields, such as toxicology chip, virus detection chip (such as hepatitis virus detection chip), p53 gene detection chip, etc. According to its function, it can be divided into microarray for detecting gene quality and quantity. Quantity detection includes: detection of mRNA level, presence or absence of pathogens and comparative genomic gene number, which can be completed by both oligonucleotide chip and cDNA chip, but cDNA chip has more advantages. Qualitative detection includes: DNA sequencing and re sequencing, gene mutation and SNP detection, mainly using oligonucleotide chip< Single nucleotide polymorphism (SNP) refers to the variation of a single nucleotide in the genome, including substitution, transversion, deletion and insertion. Theoretically, each SNP site can have four different forms of variation, but in fact, there are only two, namely transformation and transversion, with the ratio of 2:1. SNPs appear most frequently in CG sequences, and most of them are converted from C to T. the reason is that C in CG is often methylated and becomes thymine after spontaneous deamination. Generally speaking, SNP refers to the single nucleotide variation with variation frequency more than 1%. There is about one SNP per 1000 bases in the human genome, and the total number of SNPs in the human genome is about 3 × 106
the occurrence of most diseases is related to the combined effects of environmental factors and genetic factors. It is generally believed that the diseases are caused by environmental harmful factors on the basis of indivial genetic susceptibility. Different populations and indivials have different susceptibility to diseases, resistance and other biological characteristics (such as drug responsiveness). The genetic basis is the variability of human genome DNA sequence, the most common of which is SNP. The characteristic of susceptibility gene is that gene variation itself does not directly lead to the occurrence of disease, but only increases the potential risk of disease. Once the external harmful factors intervene, it can lead to the occurrence of disease. In addition, in drug therapy, the variation of susceptibility gene results in different efficacy and side effects
with the development of human genome project, more and more people believe that SNPs in the genome can help to explain indivial phenotypic differences, susceptibility of different groups and indivials to diseases, especially complex diseases, tolerance to various drugs and response to environmental factors. Therefore, the search and study of SNP has become one of the contents and goals of human genome project.
9. First of all, I don't know much about it, because undergraates are not engaged in this kind of work, but I think if you want to get a more accurate answer, you should consult professionals for such questions. I believe the other party will be very honored and happy to answer for you.
10. The logistic growth function can be used to fit the population model, which takes into account the initial exponential growth and the total resource constraints. The function form is as follows. First, load the car package to read the data, then use the NLS function to model, where theta1, theta2 and theta3 represent the three parameters to be estimated, and start sets the initial value of the parameters
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