An Enrichr pathway analysis package within the Python wrapper — We have used volcano plots, identified the differentially expressed genes (DEGs) and plotted in clustergrams to show the relative expression of these DEGs. The next logical step now will be to query the function of these DEGs. There are a myraid of web tools, such as Database for Annotation, Visualization…

Gene expression (or transcriptomics) profiling is the most common type of omics data. The identification of differentially expressed genes (DEGs) from transcriptomics data is critical to understanding the molecular driving forces or identifying the molecular biomarkers behind biological phenotypes. The comparison is usually performed with respect to controls or baseline…

Systems biology adopts and integrates multi-omics approaches to understand human biology. …

Scatterplots are great visualisation tools to assess relationships and associations between numeric or continuous variables. However, using data points to evaluate categorical variables may not be as straightforward. Consider a common scenario where a researcher wants to find out in a microarray (containing ~20,000 transcripts) whether experimental condition A elicits…

Characterising the transcriptomic profile of individuals given the self-amplifying mRNA vaccine — The self-amplifying mRNA (sa-mRNA) vaccine, which encodes an alphavirus replicase that self-amplifies the full-length mRNA and SARS-CoV-2 spike (S) transgene has been developed by Arcturus Therapeutics, but the potential for such vaccines have not been fully explored. …

The advantage of plotting scatterplots in R and the best way to represent multi-dimensional data — Scatterplots are a great way to present relationships between 2 numeric variables. In many circumstances, especially in biology, the relationship between variables may be non-linear, so solely relying on Pearson or Spearman coefficients and p-values may be insufficient to fully understand relationship between variables.

A web tool, Gene Updater, made by Streamlit to help preserve scientific data integrity and reproducibility — When gene expression data is opened in Excel, some of the gene symbols will be autoconverted into date terms. For instance, “SEPT1” (Septin 1) becomes “SEP-01” in Excel, which can affect downstream pathway analysis as many of these databases rely on gene symbols to detect for pathway enrichment. To circumvent…

Summarising the interesting aspects of the book and why being billingual can be useful — Data scientists may often wonder whether it is useful to learn both Python and R for data analysis. Is being bilingual useful? Is there a way to integrate both programming languages to harness the best of both worlds? …

Evaluating the distribution of your data variables with Python in just a few lines of codes — Descriptive statistics can provide a good sensing of the data. For instance, if the median of your data differs by the mean by a lot, you can infer that your data is skewed. On the hand, if you detect that your dataset has high variance or standard deviation, you can…