Reproducible scripts for (P. Carella et al) manuscript
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Updated
Sep 15, 2017 - R
Reproducible scripts for (P. Carella et al) manuscript
MIT UROP Fall 2018, IAP 2019, Spring 2019. Predicting Intracellular protein localization from homopolymeric amino acid tracts.
Single cell transcriptomic data from Tasic, et al. (2016)
AskoR pipeline: analysis of gene expression data, using edgeR.
Bioinformatic data mining pipeline used in my college research project. https://www.mdpi.com/2223-7747/10/8/1647/htm#
LaTeX sources for my PhD thesis RNA Sequencing for Molecular Diagnostics in Breast Cancer at the Lund University Faculty of Medicine (published December 2020).
Nextcast: a software suite to analyse and model toxicogenomics data
Graphical User Interface using Shiny for RNA-seq analysis
Re-analysis of RNA seq data from Andrade et al
Code and data associated with the paper 'The Soybean Expression Atlas v2: a comprehensive database of over 5000 RNA-seq samples'
Data and code associated with the paper "HybridExpress: an R/Bioconductor package for comparative transcriptomic analyses of hybrids and their progenitors"
How to run transcriptome analysis on SAGA
Explore spatial organization of a mouse brain coronal section with Scanpy and Squidpy in this GitHub repository. Analyze cell interactions, visualize distributions, and uncover patterns using various data exploration and spatial analysis techniques.
Expectation-Maximization-based clustering algorithm to identify groups defined by biological variates as clusters in single-cell transcriptomic data.
Genotype to phenotype prediction using transcriptomics and proteomics data.
Computational biology functions I made to help in my analyses.
Deep learning model to predict chemotherapeutic sensitivity based on transcriptomic data.
R scripts used to analyze single-nucleus RNA-seq data generated from in vitro differentiated pancreatic organoids, described in Huang, L. et al. 2021 (in press).
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