Introduction

In my previous post, I trained an XGBoost machine-learning model with single-cell RNA-Seq (scRNA-Seq) data to differentiate cell identity (parental cells versus paclitaxel-resistant cells) based on transcriptomic patterns.

As an exercise, I decided to use the same input data to experiment with other machine-learning models. In this post …

Introduction

ClinVar is one of the USA’s National Center for Biotechnology Information (NCBI) databases. ClinVar archives reports of relationships among human genetic variants and phenotypes (usually genetic disorders). Any organization, such as a laboratory, hospital, clinic etc can submit data to ClinVar. The core idea of ClinVar is aggregate …

Introduction

Dealing with big files is a routine for everyone working in genomics. FASTQ, VCF, BAM, and GTF/GFF3 files, to name a few, can range from some hundreds of megabytes to several gigabytes in size. Usually, we can use cloud services to configure computing instances with a lot of …

Introduction

Hello, long time no see! Since I lasted posted, many things happened. Since March I have been working as Post-Doc Researcher, hired by the Hospital Israelita Albert Einstein (HIAE, São Paulo, Brazil) to work for the Projeto Genomas Raros (“Rare Genomes Project”, GRAR from here on), a public-private partnership …

Introduction

Recently, me and my colleagues wrote a manuscript involving meta-analysis of RNA-Seq studies. One of my tasks of this project was to perform a Gene Ontology (GO) enrichment analysis: “[G]iven a set of genes that are up-regulated under certain conditions, an enrichment analysis will find which GO …

Introduction

In a previous post, I showed how to retrieve The Cancer Genome Atlas (TCGA) data from the Cancer Genomics Cloud (CGC) platform. I downloaded gene expression quantification data, created a relational database with PostgreSQL, and created a dataset uniting the raw quantification data for 675 differentially expressed genes identified …

Introduction

In a previous post, I showed how to retrieve The Cancer Genome Atlas (TCGA) data from the Cancer Genomics Cloud (CGC) platform. I downloaded gene expression quantification data, created a relational database with PostgreSQL, and created a dataset uniting the raw quantification data for 675 differentially expressed genes identified …