How Statistical Analysis Services Support Researchers Throughout Studies ?

Importance of Appropriate Statistical Procedures in Analyzing Data for Research Reporting:

Since it concludes the entire research process through interpretation and inference drawn from refined data, statistical analysis remains one of the most essential components of any scholarly investigation. Whether in a dissertation, thesis, or journal article, the need to process data systematically and evaluate it with precision cannot be overstated.

At the same time, the procedures involved are often intricate, as statistical reasoning entails complex logical processes that demand a well-structured and comprehensive framework.

In this blog, I will explain good statistical analysis in 6 easy steps. This guide is intended for researchers who want to become clearer and more confident on how to analyze data, so that if done appropriately, one can be assured that the statistical analysis of the research is done accordingly and accurately.

Importance of Appropriate Statistical Procedures in Analyzing Data for Research Reporting:

Before moving on to the steps, let’s understand why statistical analysis in research is so important. Large datasets can be statistically analyses and relationships, patterns and theories can be validated. Here are some reasons why statistical analysis is great:

Step 1: Specify the Research Problem Along with Its Hypotheses:

As the first and most important step in research work after identifying the research problem is data collection, it is necessary to think the problem in detail. In the definition of a research problem, the objectives are specific and it is accurate. The problems to be investigated were not well defined.

What should you consider and do?

Frame An Appropriate Research Question:

Begin with questions you want placed in very precise, measurable and researchable forms. What is it that you want to learn or to solve? Please make sure that the question is directed sufficiently narrowly so that it can be answered using statistical methods.

Formulate Hypotheses: Your research hypothesis should address the question that you have come up with. Write two hypotheses: ​

​There are two types of hypothesis:

• Null Hypothesis (H₀): It States that it has no effect or that there is no link between the variables of interest.
• Alternative Hypothesis (H₁): It posits that there is effect or that there are.

Identify Variables:

• Independent Variables: These are the factors that are within your control (e.g., treatment or age groups).
• Dependent Variables: These are the factors that you are trying to determine (e.g. blood pressure or test performance statistically).

Clearly defining all these elements will facilitate your data collection as well as your choice of statistical techniques and result interpretation.

Why This Step Matters?

A well-defined problem and carefully considered hypotheses are the basis for what you should analyze. If done correctly, your research then contributes to the answer to a single central question. Without such a foundation, the focus of the research effort can be lost and spurious conclusions drawn.

Step 2: Collect and Prepare Your Data:

1.Importance of Data Collection:

The effectiveness index of the data, which is the quality of the information that you collect, will yield a direct effect on the standard of your analysis. On the other hand, poorly done data collection will yield results that will be erroneous, while data that is well collected and prepared will yield more accurate results.

What You Need to Do?

• Choose Your Data Collection Method: This step involves selecting any of the following methods depending on the research design.
• Surveys
• Experiments
• Observational studies
• Secondary data from databases or research archives

2. Clean Your Data: Since raw data comes in its original environment, it is oftentimes common that it requires extensive cleaning. Some data cleaning tasks that are rather common include:

• Removing or handling missing data (i.e., imputing or deleting).
• Correcting errors (i.e., outlier fixing or consistency).
• Standardizing formats (e.g., ensuring that all dates are in one format or units of measurement are normalized).

3. Transform the Data if Necessary: Some data may be useful as a raw product, but some may require extra effort in order to be useful. Such processes may include:

• Normalizing data.
• Creating new variables (e.g. an index or composite score).
• Categorizing continuous data (e.g., observing age in terms of groups).

Why This Step Matters?

Despite the fact that the data collection, cleaning, and preparation steps may take up the longest period of time, they are essential in order to reduce the chances of ending up with unreliable and dirty datasets which otherwise could cause invalid analysis results. Without this preparation, the analysis results validity will be at risk.

Step 3: Selecting the best statistical approach:

The Importance of Applying Decision Analytics Appropriately:

The choice of the statistical method is probably one of the paramount decisions you will make in the course of your analysis. The statistical tool that you select must correspond to the data type and the research problem posed. Failure to select the correct test entails making incorrect statements.

Actions to Take:

Classification of the data: whether it is categorical (like gender or education level) or quantitative, such as age or income.

• Categorical data: Are those that have been grouped in particular classes or groups.
• Numerical data: Quantities or measurements.

The Principle Statistical Test: In relation to the data type and hypothesis developed, then the following methods are commonly applied:

• Descriptive Statistics: These in a brief summary describe the central tendency and dispersion of the dataset (mean, median, mode, and standard deviation).
• Inferential statistics: Are used to reach or test hypotheses about a population based on information obtained from some members of that population (t-test, ANOVA, regression).
• Chi-Square Tests: These tests are applicable to categorical variables and relate to testing relationships or differences.
• Regression Analysis: This technique is said to be applicable in determining the relational aspect of the dependent and independent variables.
• Certify on Assumptions: Each test ever employed has assumptions or conditions (normality and homogeneity of variance for example). Take for instance, make it clear that every statistical test that you choose has been fulfilled.

Why This Step Matters?

It is clear that unless the appropriate statistical method is chosen, the analysis may not be correct.

If the wrong statistical method is chosen, the results may be different, and

as such, any conclusions based on them would be wrong, thus making the research irrelevant.

Step 4: Guide to Conducting Statistical Analysis:

• Enter Data into Software: R, SPSS, SAS, and Python are the most common software to run most statistical analyses today. It involves starting the analyses by entering cleaned data into the software.
• Conduct a Statistical Test: Depending on your hypothesis and data set, you will determine which test to run. For instance, t-tests, regression and chi-square could be run.
• Discuss the Output: The output generated by software could include test statistics, p-values, t-values, confidence intervals of some other measures. Hence, it should not be done carelessly and the output should be examined carefully to assess the usefulness of the results.

Why This Step Is Vital?

Correct execution and analysis of all the statistical tests performed on the acquired data improves the analytical process and makes it more sophisticated. Even though software systems assist in the computation process, it is crucial to appreciate the results and their relevance to the posed hypotheses.

Step 5: The Outcomes and Settle:

After you have identified the outcomes, the next step is to make sense of them in the light of the purpose of your research, which is to interpret. It is during this stage that they come to conclusions about their hypotheses and reasons for their conclusions. What Needs to be Done:

• Evaluate the P-Value: The p-value is a measure of the validity of the results obtained. On the other hand, if the p-value is found to be less than the predetermined cutoff (usually 0.05), the null hypothesis can be rejected as the results from the study indicate that an effect or relationship exists.
• Review Confidence Intervals: Confidence intervals give an upper and lower limit or range within which the true value of a quantity being estimated is expected to lie. When testing a hypothesis by regression, for instance, if the interval contains zero it may be said that the end result may not matter.
• Communicate Results with Graphs/Pictures: Graphs and charts are important in explaining the results of the research. Use the bar charts, scatter plots or histograms to illustrate how the trends, distributions and relations appear.
• Provide a Comment or Summary: Write a comment on your overall research argument based on the statistical results. Discuss how your data supports or contradicts your hypothesis and what implications it has had for the research you have carried out.

Significance Of This Step:

The interpretation of research and the following analytical process is key to arriving at valuable conclusions. This step is relevant in that it returns us to the research problem and explains what the findings mean.

Step 6: Give a Report on Your Findings Restrained Finds effective communication as important:

The final step of statistical analysis is the communication of results. Whether it is a research paper, a presentation or a report, you need to be able to communicate what you have found out in your research so that others can understand.

What Is Required Of You?

• Prepare a Thorough Report: The report should be clear about the design of the research, the statistical methods used, and the results. Describe the tests conducted, the prerequisites, the purpose, and the use of the tests as applied to the covered data.
• Aids In Your Findings Presentation: Charts, graphs, and tables simplify the complex underlying data and trends and relationships that you as the researcher have pinpointed, making the information easier for your audience.
• Explain the Relevance of Your Research: Make sure to show how your findings contribute to the already existing scientific base and the new animal studies that may emerge.

Importance of This Step:

This step helps researchers connect their conclusions to the body of work. This makes it easier for the listeners to understand your thesis, and acceptance of your work increases.

GENETIC STUDY OF EXAN 3 AND 4 OF INSULIN LIKE GROWTH FACTOR-2 GENE (IGF2) AND ITS EFFECT ON GROWTH TRAITS IN JAPANESE QUAIL

Abstract 

The pituitary gland releases insulin-like growth hormone (IGF) to promote cell division and stimulate the proliferation of myoblasts, which subsequently enhances skeletal muscle growth in an individual. Among the genes involved in this growth process, IGF1 and IGF2 play pivotal roles.

As the activity of these IGFs increases, so does the overall growth of the organism. The mechanism underlying this process is complex, as IGF1 and IGF2 interact with various receptors, including the insulin-like growth factor 2 receptor (IGF2R), as well as binding proteins.

Photorealistic illustration of Japanese quails in a modern research laboratory

For the study of the IGF2 gene’s effects, the Japanese quail (Coturnix japonica) was selected as the model organism. In this experiment, measurements were taken from 50 quails, including their length, width, weight, wing span, drumstick length and circumference, as well as shank length and diameter.

Blood samples of 1 ml were collected from each quail and stored for analysis. For DNA extraction, 200 µl of blood from each sample was processed using an adapted version of the conventional organic extraction method. The third coding sequence of the IGF2 gene revealed four transition mutations, while the fourth coding sequence exhibited ten transition mutations and two transversion mutations. This research contributes to advancing our understanding of quail genomics and provides valuable insights into the genetic underpinnings of growth.

The poultry industry is the one that is expanding the quickest of all livestock. Due to the fact that it is the human body’s primary source of protein, it was estimated that one billion people are employed in that field. Because its manure enriches the soil with nutrients, it is essential to plant growth.

The demand for Gallus Gallus (chicken) was estimated to have increased over the past few years. According to Bingham (2006), the chicken does not contain the trans-fats that are linked to heart disease and only has about 5 grams of fat per 100 grams. According to Sparks (2006), the hen’s egg plays a significant role in balancing human nutrition. Because per capita demand for chicken is steadily rising, researchers have begun looking into other birds to alleviate this burden. Quail birds will therefore be an excellent choice (Fig. 1.1).

The skeletal muscles are made up of fibers from muscles, connective tissues, and adipose tissues. Important parameters that were observed included technological, nutritional, and sensory aspects of meat from various livestock and fish species.

The color, tenderness, juiciness, flavor, and other characteristics of meat depend heavily on the amount and composition of intramuscular fat. These parameters, which can be controlled by genetics or environmental factors to increase meat production efficiency (List rat et al., 2016).

Breeding of Japanese Quail

Japanese quail selective breeding began in the 1900s, and in 1940, the quail’s eggs sparked a significant industry shift. Similar to chicken, Japanese quail eggs contain nutrients and benefits. The Japanese quail’s eggs average 10 grams (Fig. 1.3).According to (Hubrecht & Kirkwood, 2010) the majority of the Japanese quail breeds were eradicated during World War II, leaving only a few surviving lines that are currently flourishing.

In 1957, biomedical research on Japanese quail was taken up by Auburn University and the University of California. The Japanese quail’s genetic work in genetics, nutrition, physiology, pathology, embryology, cancer, behavior, and the toxicity of pesticides was then initiated (Ainsworth, Stanley, & Evans, 2010).

Systematics

A genetic test revealed that, with the exception of B30 and tRNA, the majority of Gallus gallus and Coturnix japonica have the same fundamental set of gene family members. The genetics of the NK gene clearly showed that both species have been closely related in the past (Shiina, 2004). Because it takes only 114 to 120 days for the eggs to hatch, Bangladesh, like many other Asian nations, is an excellent location for quail farming.

According to (Kabir2013), a blood sample was analyzed and it’s hematological and biochemical contents, such as calcium and glucose, indicated that quail eggs and quail meat were found to be very nutritious and healthy for humans.

Game Bird

In Bangladesh, the quail was introduced as a hobby bird as a game bird in 1980 (Fig. 1.4).The importance of quail poultry grew, and people started to be very interested in commercial quail production. Eggs and meat were first produced commercially in Japan and Europe, respectively. According to F. Minvielle, E. Hirigoyen, and M. Boulay (1999), quail became a popular meat and egg source in Bangladesh.

Role of insulin like growth factors-2 (IGF2)

Somatomedin is another name for insulin-like growth hormone. When a person needs to grow, the pituitary growth hormone uses IGFs to start cell division. IGF1 and IGF2 are two molecules that play a significant role in the growth pf cartilage (Salmon & Daughaday, 1957). Insulin-like growth factors are made up of the IGF1 and IGF2 genes. As the activity of IGFs rises, so does the organism’s growth. Because of its structural similarity to insulin, it was given the name “insulin-like growth factors” (Rinderknecht & Humbel, 1978a, 1978b).

It significantly increases cell division for the purposes of living organism growth, migration, and differentiation. Because IGF1 and IGF2 cooperate with a variety of receptors, such as the insulin-like factor 2 Receptor (IGF2R), as well as binding proteins, the mechanism is intricate. IGF2R shares structural similarities with mannose-6-phosphate (M6P). Plasma can be traced for both IGF1 and IGF2. It was also anticipated that IGF1 would have high activity from birth through puberty, whereas IGF2 would have high activity during prenatal development (Sara et al., 1983).

By stimulating myoblast proliferation, muscle fiber differentiation, and increase in size, insulin-like growth factors play an important role in skeletal muscle growth. According to Bass, Oldham, Sharma, & Kambadur (1999), the size of the muscle mass increases in hypertrophied muscle cattle breeds due to differences in the myostatin mutation and MyoD expression in the muscle. IGF2 plays a crucial role in the growth of the birds.

Methodological steps include sample collection, DNA extraction, primer design, polymerase chain reaction (PCR), and IGF2 gene sequencing to compare the genetic makeup of quail birds with higher body weight to those with lower body weight. IGF2, which has only recently been characterized and is controlled by differential expression of IGF-binding proteins and receptors, is the most significant regulated factor. According to Chao & D’Amore (2008), the over expression of the IGF2 gene has been linked to a variety of diseases.

Two alleles, one from each parent, are carried by organisms. Studies on genomic imprinting suggested that an organism inherits traits from both parents, but in the case of human IGF-II, only the paternal allelic copy of the gene is active and the maternal copy does not. The mutation in the IGF2 gene was linked to a wide variety of cancers (Eggermann, 2009). The IGF-II gene provides the instructions for the synthesis of insulin-like growth factor-II protein.

According to Bergman, Halje, Nordin, & Engstrom (2013), the activity of the IGF-II gene was found to be extremely high during the fetus’s development and to decrease after birth. According to Florini, Ewton, & Coolican (1996), growth hormone (GH) is responsible for activating the liver to initiate the production of insulin-like growth factors (IGFs) and insulin-like growth factor protein 3 (IGFBP3), which play a significant role in regulating the growth and differentiation of skeletal muscles.

Although IGF1 and IGF2 play identical roles in the metabolic activities and growth of living organisms, numerous distinct differences were also observed when the research was carried out in vivo (Engstrom et al., 1998).

Insulin-like growth factor binding proteins, or IGFBPs, are made up of about six distinct designs found in living things. Because they were required to perform a particular function during development, these proteins were active. According to Clemmons et al. (1997), in vitro research revealed that when biologically active IGFs were unavailable, IGFBPs lost their ability to function (Clemmons, 1997). During the cross between parent chicken stock and four Thai breeds, the roles of chicken growth hormone and insulin-like growth factor (IGF) were investigated.

According to Anh, Kunhareang, & Duangjinda (2015), allele G plays a significant role in the average daily weight gain of chickens, and IGF also plays a significant role in increasing body mass by promoting the growth of breast muscles and wings. F-Statistics (FST), which is used to evaluate studies of SNP-wise genetic differentiation between chicken populations, is the most useful fixation index.

Three 600K SNP-chips were used to genotype 96 individuals from 14 non-commercial fancy breeds and three commercial layer breeds. POMC, PRKAB2, SSP1, IGF2, CAPN1, TGFb2, and IGFBP2 were the genes involved in the breeds’ growth (Gholami et al.,) which are important for reproductive traits.2014).IGF2 plays a crucial role in the birds’ growth.

The 50 quail will be measured for their length, width, weight, expanded wings, drum stick length and circumference, shank length, and diameter. The samples were divided into two groups: Japanese quail of lower weight and higher weight. Each sample’s 1 ml of blood will be taken and stored in the refrigerator. According to Sambrook & Russell (2006), the conventional organic method would be used for the DNA extraction, with some modifications, from the 200 l of blood from the 50 samples.

The IGF system’s pleiotropic effects on mammalian growth and development were investigated. The class aves’ IGF system’s physiology is identical to that of other species. The free form of the IGF system was found to be abundant in chicken, and its biological metabolic responses differed from those of humans. The etiological study of diseases and the factors that promote poultry growth are more important than ever (McMurtry & Brocht, 1997).

Growth regulators

The growth and development of skeletal muscles are coordinated by insulin-like growth factors (IGFs), but their determination is crucial due to the fact that IGFs are produced by multiple tissues. According to Barton et al., deletion of GRP94 resulted in a 30% decrease in body and muscle growth.2012).When chicken males and quail males were crossed in an experiment to create hybrids, it was found that only 5.4% of the eggs produced were fertile and that there was no hatching (Mitsumoto & Nishida, 1958).

Growth hormone and growth hormone receptor research contributed significantly to our understanding of sex-linked dwarfism in chicken. According to Luo, Lin, Li, Nie, & Zhang (2016), the molecular mechanism has opened up a new era for identifying the various genes, such as those involved in the MAPK, P13K-Akt, Wnt, and Insulin signaling pathways, as well as the miRNA, that cause chickens to develop dwarfism from the embryonic stage to seven weeks of age.

Growth inhibitors

The growth hormone receptor gene mutation was the cause of the sex-linked dwarf chicken’s lower body weight, smaller muscle fiber diameter, and fewer muscle fibers. According to Lin et al., lower-body-weight chickens had elevated levels of let-7b, which resulted in decreased production of insulin-like factor 2 mRNA binding protein 3 (IGF2BP3) and decreased growth.2017).In the avian species, growth regulators like insulin-like growth factors I and II were essential for muscle development.

The growth of the skeleton may be slowed down by inhibitors like myostatin. It was discovered that the translational mechanisms of IGF1 and IGF2 increased muscle growth when myostatin expression was altered. The growth of skeletal muscles is aided by insulin-like growth factors (IGFs), but their selection is crucial due to the fact that IGFs are produced by a variety of tissues. GPR94 (glucose-regulated protein 94) was examined for normal muscle growth in murine striated muscles. According to Barton et al., deletion of GRP94 resulted in a 30% decrease in body and muscle growth.2012).

GENETIC STUDY OF EXON 3 AND 4 OF INSULIN-LIKE GROWTH FACTOR-2 GENE (IGF2) AND ITS EFFECT ON GROWTH TRAITS IN JAPANESE QUAIL

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