Biostatistics Data Visualization with Zero Coding

Name: Biostatistics Data Visualization with Zero Coding
Rating: 4.9 (9 reviews)

Biostatistics Data Visualization for Biomedical, Agricultural & Biological Research — No Coding Needed

Created byAsif Ali

Last updated 8/2025

English

English [Auto],

What you'll learn

Identify the most effective graph types for different datasets.
Use web-based tools to create high-quality graphs without coding.
Introduction to multiple online webtools used for data visualizations
Customize figure design for scientific publications.

Course content

4 sections • 22 lectures • 2h 59m total length

Introduction to Chi Plot ( a Web-based tool for data visualization)7:28
Learn to use a web-based chi plot tool for data visualization, creating circular gene ontology maps and heat maps via Excel uploads and export options.
How to draw colorful phylogenetic trees?26:40
Learn to draw colorful phylogenetic trees using a free ggplot website, uploading Newick data, and styling layouts, colors, and symbols with metadata for clear visualization.
How to draw circular gene ontology?5:27
Learn to draw circular gene ontology maps using the ggplot web tool by uploading data, customizing axes, background, fonts, and exporting as pdf, png, or eps.
How to draw a Saneky Plot?4:50
Learn to draw Sankey plots for energy flow with a ggplot website, visualize energy sources and magnitudes, upload CSV data, and export PNGs for research.

Introduction ot SR plot9:50
Learn to avoid common errors when using the SR plot website to generate heatmaps, including data formatting, unique IDs, and proper input and header rules.
How to draw heatmap with zero coding?5:10
Learn to create heat maps without coding using the SR plot online tool, visualizing wild type and mutant transcriptomic data with replicates, and export in multiple formats.
How to perform Gene Enrichment analysis with SR plot6:27
Learn to perform gene ontology and KEGG pathway enrichment with the SR plot website in one click, producing GO and KEGG results, plots, and downloadable folders.
How to create ballon chart?4:26
How to create box plot with jitters5:26
Learn to create a box plot with jitters using the SR plot website, input gene data with groups, customize appearance, and apply t tests, Wilcoxon, or Kruskal-Wallis for multiple groups.
How to draw Violin plot with statistics5:46
Draw violin plots with statistics using a free online bio-informatics plotting tool, prepare your data, customize groups and supplementary data, and apply appropriate statistical tests.
How to draw a correlation plot?8:47
Learn to draw a correlation coefficient plot with the SRW plot website, choosing upper or lower triangles, showing p-values, and using Pearson or Spearman methods.
How to performe GO (Gene enrichment) analysis with all folders5:25
Learn to perform gene ontology enrichment analysis using cluster profiler and path view, download GO and pathway results in organized folders, and prepare input with gene IDs and logfc values.
How to draw a KEGG pathway Summary?3:29
Create KEGG pathway summary plots from a two-column gene-count file on the SRX plot website, customize colors and fonts, and export as pdf, png, svg, or tiff.
How to draw a PCA plot?7:41
learn to draw principal component analysis (PCA) plots using the SR plot website, including data preparation, input formats, and options like transpose, ellipse, and legend settings.
How to draw a GO chord plot?3:56
Design a GO code plot by preparing data with gene IDs, GO terms, and logFC; input on the SR plot site, order by logFC, customize colors, and download the PNG.
How to draw a circos plot?4:26
Learn to draw a circos plot for genomics without coding, using the SR plot website with two tracks, preparing data in Excel, and exporting png or svg.
How to draw an alluvial plot?3:31
Learn to draw alluvial plots without coding using the SRW plot website, preparing data in Excel and visualizing circular RNAs, microRNAs, and messenger RNAs over time for research articles.

Introduction to iDEP26:33
Learn to use iDEP for RNA-seq analysis without coding. Upload counts or FPKM data, preprocess and filter, and explore heat maps, PCA, DESeq2, GO and pathway networks.
Introduction to GO shiny tool4:21
Learn how to resolve id recognition in the shiny go tool by converting gene IDs to accepted formats and selecting the species glycine max for gene enrichment analysis.
How to perform WGCNA?12:00
Explore how to perform WGCNA using an online tool without coding, from preparing gene counts and design csv files to building networks and identifying modules and hub genes.

Introduction to Hiplot10:20
Explore hiplot, a web-based tool for visualizing statistics and bioinformatics data with one-click pipelines for RNA-seq and single-cell RNA-seq, offering versatile plots and data upload options.
Introduction to NewMer web based tool7:36
Explore the NMR database, a powerful web-based tool for data mining, statistical analyses, gene annotation, RNA/DNA processing, and diverse bioinformatics workflows.

Requirements

No prior coding experience is required — the course is designed for beginners
Access to a computer with an internet connection to use web-based tools.

Description

In this course i have introduced multiple web-based tools used for data visualization, each chosen for its ability to create professional, publication-ready figures without coding. In research, the quality of your data visualization can define the impact of your work. Whether you’re in biomedical engineering, agriculture, or biology, creating clear, accurate, and visually appealing graphs is essential for theses, manuscripts, grant proposals, and presentations.

This course is designed to eliminate the biggest challenge researchers face — coding barriers. While tools like R and Python are powerful, they require weeks or months to learn. Here, you’ll learn to use various online platforms for generating publication-quality visualizations quickly and efficiently, allowing you to focus more on your research instead of programming syntax.

Through step-by-step demonstrations, you will:

Create bar charts, boxplots, scatter plots, correlation matrices, survival curves, and heatmaps.
Graphs used in advanced analyses of Transcriptomics, metabolomics and proteomics.
Customize visual elements for publication requirements.
Interpret results accurately to avoid misleading conclusions.
Apply these figures effectively in your research, thesis, and publications.

By the end of this course, you’ll have the skills and confidence to transform your raw data into visually compelling, scientifically accurate figures that enhance the clarity and impact of your research.

Who this course is for:

Students and researchers in biomedical engineering, agriculture, and biology.
Early-career scientists preparing thesis, dissertations, and manuscripts.
Anyone with research data who needs professional graphs without coding.
Professionals looking to quickly learn modern, web-based visualization tools.

Biostatistics Data Visualization with Zero Coding

What you'll learn

Explore related topics

Course content

Introduction to Chiplot- A web based tool for data visualization4 lectures • 44min

Introduction to a SR plot web-based tool13 lectures • 1hr 14min

Introduction to RNA seq web based data tools3 lectures • 43min

Introduction to latest released web based tools2 lectures • 18min

Requirements

Description

Who this course is for: