Tag: Basic Bioinformatics Tools

Introduction to BLAST Searching

This workshop will introduce the basics of sequence similarity searching using the NCBI Basic Local Alignment Search Tool (BLAST). Participants will conduct BLAST searches and examine the type of information retrieved.

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Differential Expression Analysis of RNAseq Data

RNAseq provides a snapshot of the transcription state of the cells from which RNA was harvested. One of the most common applications of this sequencing data is to look at changes in the transcriptome state between two or more conditions the cells were exposed to. We will discuss the various considerations in analyzing RNAseq data and run through a practical example using DESeq2.

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BBTools: A Toolbox for High Throughput Sequencing Data Analysis

The BBTools suite contains tools that assist with multiple types of high throughput (HT) -sequencing data analysis. After an overview of tools included in BBTools toolbox, we will learn how to use “bbduk” (decontamination using k-mers) for scanning/trimming data to remove adapter contamination. This will be followed by “bbmap” (sequence data aligner) which we are going to use to align the test sequence data.

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Introduction to Next Generation Sequencing Data and Quality Control

Genome wide analysis of gene expression has been a popular technique since the advent of microarrays. Next Generation Sequencing (NGS) technology was applied for this purpose early in the life cycle and has since become one of the most popular uses of NGS. We will start with a general overview of NGS technologies and consider commonly used data formats.

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Introduction to NCBI Biomolecular Database Searching

This 90 minute workshop will provide an overview on how to use NCBI databases, and introduce strategies for using Entrez to conduct text searches. For details and to register, visit http://guides.lib.unc.edu/bioinformatics/bbtworkshopdescriptions#6

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Differential Expression Analysis of RNAseq Data

RNAseq provides a snapshot of the transcription state of the cells from which RNA was harvested. One of the most common applications of this sequencing data is to look at changes in the transcriptome state between two or more conditions

Tagged with: ,