Kavya Banerjee (KavyaBanerj)

KavyaBanerj

User data from Github https://github.com/KavyaBanerj

Company:Johns Hopkins University

GitHub:@KavyaBanerj

Kavya Banerjee's repositories

biostatistics

Biostatistics resources : reading list, RMarkdown notebooks, and more!

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JHU-Applied-ML

ML assignments from JHU EP.705.601: Applied Machine Learning

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Work-Samples

This repository has a collection of bioinformatics assessments and analyses demonstrating proficiency in ML and next-generation sequencing (NGS) data analysis.

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ChIP-Seq-Nexflow-Pipeline

Nextflow DSL2 ChIP-Seq analysis pipeline including quality control, alignment, peak calling, blacklist filtering, annotation, motif analysis, and visualization.

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WES-Variant-Calling

Shell workflow designed to process Whole Exome Sequencing (WES) data following GATK4 best practices for variant calling.

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Glioma-ML-Classifier-with-ANOVA-Feature-Selection

Pipeline using TCGA data to classify glioma subtypes using machine learning models. The pipeline includes data preprocessing, ANOVA-based feature selection, and model training using Logistic Regression, Random Forest and XGBoost classifiers. Also contains a survival analysis exploration on glioma subtypes.

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RNASeq-Nexflow-Pipeline

Nextflow pipeline for RNA-Seq QC and quantification on paired-end reads. Includes quality control, read trimming, alignment, and quantification steps.

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aws-for-bioinformatics

AWS for Bioinformatics Researchers

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scRNASeq-cancer-cell-line

Analysis of scRNA-seq data from cancer cell lines using Python (Scanpy) to explore the potential application of antibody therapies such as Trastuzumab and Bevacizumab in additional cancers.

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Microarray-RNASeq-Workflow

Repo for analyzing gene expression profiles in early-onset pediatric atopic dermatitis (AD) from blood samples from GEO dataset.

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DNA-seq-analysis

DNA sequencing analysis notes from Ming Tang

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