Dr. M. Shamshad

Sugarcane Breeder && Computational Biology Researcher

Recent posts

Latin Square Design (LSD): Theory & Complete R Analysis

17 minute read

Updated:

The Latin Square Design (LSD) extends blocking to two simultaneous directions of environmental variation. By controlling both a row gradient and a column gradient, it achieves greater error reduction than RCBD while using the same number of experimental units. It is the design of choice when two orthogonal sources of heterogeneity are known in advance — such as row (fertility) and column (irrigation) gradients in a field, or row (day) and column (technician) effects in a laboratory.

Randomized Complete Block Design (RCBD): Theory & Complete R Analysis

14 minute read

Updated:

The Randomized Complete Block Design (RCBD) is the most widely used experimental design in agricultural, biological, and environmental research. It extends the CRD by introducing blocks — groups of homogeneous experimental units — to account for a single known source of environmental variation (soil fertility gradient, slope, irrigation, temperature, etc.). Every treatment appears exactly once in every block, making blocks complete.

Completely Randomized Design (CRD): Theory & Complete R Analysis

11 minute read

Updated:

The Completely Randomized Design (CRD) is the simplest experimental design. Treatments are assigned to experimental units purely at random, with no restrictions. It is the starting point for understanding all other designs (RCBD, Latin Square, Alpha-lattice) and remains widely used in controlled laboratory and greenhouse experiments.

F-Test: Theory, Variants & Complete R Analysis

11 minute read

Updated:

The F-test is a family of statistical tests built on the F-distribution — the ratio of two independent chi-squared variables divided by their degrees of freedom. It answers three fundamental questions in applied statistics:

  1. Are two population variances equal? (Variance ratio test)
  2. Do several group means differ? (One-way ANOVA)
  3. Does a regression model explain significant variation? (Overall F in regression)

Z-Test and t-Test: Theory, Hypotheses & Complete R Analysis

10 minute read

Updated:

Hypothesis testing is the formal procedure for deciding whether sample data provide sufficient evidence to reject a claim about a population parameter. The Z-test and t-test are the two workhorses for testing means. This post covers the theory, assumptions, null (H0) / alternative hypotheses (H1), test statistics, and full R walkthroughs with real-style datasets.

GWAS in TASSEL: Step-by-Step Tutorial for Beginners

4 minute read

Updated:

Genome-wide association studies (GWAS) increase their popularity among medical, biological, and social sciences to identify the association between single nucleotide polymorphisms and phenotypic traits. This tutorial aims to provide a guidelines for conducing genome wide analysis in Tassel.

Investigate genetic admixture using STRUCTURE software

3 minute read

Updated:

Structure Software is a freely available software package that one may use for rigorous investigation of admixed individuals; identification of point of hybridization and migrants; and estimate over all structure of a population using commonly used genetic markers such as single nucleotide polymorphism (SNPs) and simple sequence repeat (SSRs).

Plot Genetic Linkage Maps using MapChart software

5 minute read

Updated:

MapChart is a freely available software package designed for drawing high-quality genetic linkage maps and displaying quantitative trait loci (QTLs). It helps researchers convert mapping data into clear, publication-ready diagrams, making it especially useful in genetics, genomics, and plant breeding studies.