Parsing and analyzing BAM files
SAMtools for manipulation of BAM files
Posts by Category
- Bioinformatics 22
- Statistics 16
- Python 11
- Machine learning 9
- Pandas 3
- High-throughput sequence analysis 3
- Genomic visualization 2
- Dimensionality reduction 2
- Artificial intelligence 1
- Deep learning 1
- Genotyping 1
- Variant Annotation 1
- Variant analysis 1
Bioinformatics
Entrez programming utilities for downloading the nucleotide and protein sequences from NCBI
NCBI E-utilities for downloading the single or large number of sequences from the NCBI sequence database
A guide to understanding the variant information fields in variant call format (VCF) file
VCF fields information
Gene expression units explained: RPM, RPKM, FPKM, TPM, DESeq, TMM, SCnorm, GeTMM, and ComBat-Seq
bulk and single-cell RNA-seq expression units, count normalization, formula, examples in Python, gene quantification, batch effects, and between-sample and w...
How to use NCBI SRA Toolkit effectively?
Downloading FASTQ files from NCBI SRA database
t-SNE in Python [single cell RNA-seq example and hyperparameter optimization]
t-SNE using sklearn package. This article explains the basics of t-SNE, differences between t-SNE and PCA, example using scRNA-seq data, and results interpre...
Sequencing coverage and breadth of coverage
High-through sequencing coverage calculation and coverage recommendations
Heatmap in Python
Heatmap and hierarchical clustering visualization in Python
Performing and visualizing the Principal component analysis (PCA) from PCA function and scratch in Python
PCA using sklearn package. This article explains the basics of PCA, sample size requirement, data standardization, and interpretation of the PCA results
Volcano plot in Python
Volcano plot using bioinfokit package. This article explains the visualization of volcano plots for gene expression data
Multiple hypothesis testing problem in Bioinformatics
Multiple hypothesis testing and corrections, type I and II errors, false discovery rate, Bonferroni correction, and Benjamini/Hochberg correction
Bioinformatics file readers and processing (FASTA, FASTQ, and VCF)
Biological data handling and processing using Python codes
Manhattan plot
Introduction, analysis, and visualization of Manhattan plot in Python
MA plot to visualize gene expression data using Python
MA plot basics, analysis, and visualization
FASTQ Sequence Quality Format
FASTQ sequence example, quality formats, and quality format detection
Convert GFF3 to GTF file format
Introduction to GFF3 and GTF files, and their interconversions using Python code
Annotation of genetic variants (SNPs/InDels) in VCF file
Genetic variant annotation for variant location in the genome, associated genes, and their gene functions
Venn diagrams in Python and R
Create two and three-way Venn diagrams in Python and R
Reverse complementary
Reverse complementary of DNA sequences
Concatenate and split VCF files
What is VCF file? VCF stands for variant call format It is a text file (file extension as .vcf) storing meta-information, marker and genotype data of ge...
Correlation analysis in Python
Correlation analysis using Python code
Advanced Bioinformatics Workshop
Title: Advanced Bioinformatics Workshop
Statistics
Multiple hypothesis testing problem in Bioinformatics
Multiple hypothesis testing and corrections, type I and II errors, false discovery rate, Bonferroni correction, and Benjamini/Hochberg correction
Statistical hypothesis testing, types of errors, and interpretation of p values
Learn how to propose null and alternate hypotheses, perform the statistical analysis, and interpret the results
Find probabilities using discrete and continuous probability distributions
Learn how to use probability distributions, probability mass function (PMF), cumulative distribution function (CDF), and probability density function (PDF)
Logistic regression in Python (feature selection, model fitting, and prediction)
Logistic regression for prediction of breast cancer, assumptions, feature selection, model fitting, model accuracy, and interpretation
Multicollinearity and variance inflation factor (VIF) in the regression model
Multicollinearity refers to the significant correlation among the independent variables in the regression model. Variance Inflation Factor (VIF) helps to dia...
Multiple linear regression (MLR)
Multiple regression analysis using statsmodels. Learn how to define regression model, assumptions, metrics evaluation, and interpretation
Linear Regression Using Neural Networks (PyTorch)
Linear regression using PyTorch
Linear regression basics and implementation in Python
Linear regression using statsmodels. Learn how to define, analyze and interpret the regression model.
Chi-square (χ2) test in Python (Pearson Chi-square test)
Pearson Chi-square test, chi-square goodness of fit test, formula, assumptions, example in Python, and interpretation
Perform three types of t-test in Python
Learn when to use t-test, types of t-test, assumptions, hypothesis, and formula for each type of test, and t-test calculation in Python
Mann-Whitney U test (Wilcoxon rank sum test) in Python
Learn when to use Mann-Whitney U test, assumptions, hypothesis, and formula, and test calculation in Python
Perform t-test from scratch in Python
Calculate three types of t-test from scratch
Correlation analysis in Python
Correlation analysis using Python code
Repeated Measures ANOVA using Python and R (with examples)
Repeated Measure ANOVA in Python and R. This article explains repeated Measure ANOVA model, multiple pairwise comparisons, and results interpretation
ANOVA using Python (with examples)
One and two-way ANOVA in Python. This article explains ANOVA model, formula, calculation, multiple pairwise comparisons, and results interpretation
Variable types
Variable types Flowchart for types of variables used for collecting and analyzing the data
Python
Import small and large data using pandas (CSV, Excel, Tab, JSON, SQL, and Parquet files)
learn how to import CSV, Excel, Tab, JSON, and SQL files in pandas for data analysis and visualization
Checking and handling missing values (NaN) in pandas
Analyse and handle null or missing values in pandas series and dataframe
Left, right, outer and inner joins on pandas dataframes
learn to join pandas dataframes in multiple ways
New good features in Python 3.9
Merge and update dictionaries, string methods, math functions, and readlink() function
Multiple ways to select rows, columns, and subsets from pandas DataFrame
This article explains how to select rows, columns, and a subset of pandas DataFrame using various indexing operations and pandas functions
Data handling and manipulation with Pandas
What is pandas?
Pandas groupby function to group column values into list
Group dataframe rows into a list based on a common element from one column
Python enumerate to simplify the looping
Python enumerate built-in function allows iterating over list and dictionary and helps to access its items along with index values
Python tuples
Python tuples initialization and operations
%in% and %notin% operators in R
Learn how to use %in% operator in R
Install and upgrade Python packages using pip on Windows, Linux, and Mac
Learn how to install and upgrade pip and Python packages
Machine learning
t-SNE in Python [single cell RNA-seq example and hyperparameter optimization]
t-SNE using sklearn package. This article explains the basics of t-SNE, differences between t-SNE and PCA, example using scRNA-seq data, and results interpre...
Performing and visualizing the Principal component analysis (PCA) from PCA function and scratch in Python
PCA using sklearn package. This article explains the basics of PCA, sample size requirement, data standardization, and interpretation of the PCA results
Logistic regression in Python (feature selection, model fitting, and prediction)
Logistic regression for prediction of breast cancer, assumptions, feature selection, model fitting, model accuracy, and interpretation
Support Vector Machine (SVM) basics and implementation in Python
Support vector machine (SVM) for prediction of heart disease. Learn SVM basics, model fitting, model accuracy, and interpretation
Multicollinearity and variance inflation factor (VIF) in the regression model
Multicollinearity refers to the significant correlation among the independent variables in the regression model. Variance Inflation Factor (VIF) helps to dia...
Multiple linear regression (MLR)
Multiple regression analysis using statsmodels. Learn how to define regression model, assumptions, metrics evaluation, and interpretation
Linear Regression Using Neural Networks (PyTorch)
Linear regression using PyTorch
Linear regression basics and implementation in Python
Linear regression using statsmodels. Learn how to define, analyze and interpret the regression model.
Variable types
Variable types Flowchart for types of variables used for collecting and analyzing the data
Pandas
Import small and large data using pandas (CSV, Excel, Tab, JSON, SQL, and Parquet files)
learn how to import CSV, Excel, Tab, JSON, and SQL files in pandas for data analysis and visualization
Checking and handling missing values (NaN) in pandas
Analyse and handle null or missing values in pandas series and dataframe
Left, right, outer and inner joins on pandas dataframes
learn to join pandas dataframes in multiple ways
High-throughput sequence analysis
Bioinformatics file readers and processing (FASTA, FASTQ, and VCF)
Biological data handling and processing using Python codes
FASTQ Sequence Quality Format
FASTQ sequence example, quality formats, and quality format detection
Convert GFF3 to GTF file format
Introduction to GFF3 and GTF files, and their interconversions using Python code
Genomic visualization
Volcano plot in Python
Volcano plot using bioinfokit package. This article explains the visualization of volcano plots for gene expression data
Convert GFF3 to GTF file format
Introduction to GFF3 and GTF files, and their interconversions using Python code
Dimensionality reduction
t-SNE in Python [single cell RNA-seq example and hyperparameter optimization]
t-SNE using sklearn package. This article explains the basics of t-SNE, differences between t-SNE and PCA, example using scRNA-seq data, and results interpre...
Performing and visualizing the Principal component analysis (PCA) from PCA function and scratch in Python
PCA using sklearn package. This article explains the basics of PCA, sample size requirement, data standardization, and interpretation of the PCA results
Artificial intelligence
Linear Regression Using Neural Networks (PyTorch)
Linear regression using PyTorch
Deep learning
Linear Regression Using Neural Networks (PyTorch)
Linear regression using PyTorch
Genotyping
Annotation of genetic variants (SNPs/InDels) in VCF file
Genetic variant annotation for variant location in the genome, associated genes, and their gene functions
Variant Annotation
Annotation of genetic variants (SNPs/InDels) in VCF file
Genetic variant annotation for variant location in the genome, associated genes, and their gene functions
Variant analysis
Manhattan plot
Introduction, analysis, and visualization of Manhattan plot in Python