
GANs (Generative Adversarial Networks) are based on making two neural networks compete with each other. The first network, the generator, creates synthetic data from random noise (e.g. a sample normal…

Once we create the transcript abundance data using Stringtie, we can now perform the differential expression analysis. With Strigtie, we had created the estimated transcript abundance data which is compatible…
In this post we will see how to use HISAT2 and Stringtie to align raw RNA-Seq reads to annotated genome and estimate transcript abundances.
In this series of posts, we will see how we can perform RNA-Seq analysis in Windows operating system using linux tools in WSL. Also, the part of analysis which require…
Let’s say we have two pandas dataframes. Each of them contain two columns, the gene name and their expression value. There may be other columns with more details of each…
The simplest way I found for performing OneHot encoding is using pandas.get_dummies method. In just one line of code you can OneHot encode selected columns in a pandas dataframe. Also,…
I had a few deep learning models saved. From a test data, I wanted to make subsets in specific way and evaluate them. Each subset was a combination of few…

The deep learning model has model weights which start from a random state wen the model object is created. As we expose the model with the training data, the weights…
Often times you would want to save python objects for later use. For example, a dataset you constructed which could be used for several projects, or a transformer object with…

Data distribution plots help visualize how quantitative data points are spread over the range of their values. Distribution of quantitative data can be shown in various ways such as box-plots,…
Let’s say we want to convert multiple categorical variables into binary variables by selecting one category as “0” and the rest as “1”. Or we want to change the values…
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