Supporting Trainers to Improve Bioinformatics Education Globally
Speaker: Dr. Michelle Brazas
A needs assessment isn’t necessary to realize that across the globe, there is a high demand for quality bioinformatics training in all domains of life science. Delivering on this demand however is not...

Online Gaming in Bioinformatics: The ‘Fun’ Model to Online Bioinformatics Education
Benjamin Good, Senior Staff Scientist, Department of Molecular and Experimental Medicine, The Scripps Research Institute.
Dr. Good’s research focuses on games with a purpose in crowdsourcing biological knowledge....

Self-directed Learning: Does online learning in bioinformatics work?
Proposed Speaker: (CONFIRMED) David Searls, Adjunct Associate Professor, Perleman School of Medicine, University of Pennsylvania.
Dr. Searls is an independent consultant in bioinformatics and former Senior VP of Bioinformatics...

MOOCs in Bioinformatics: The Online Course Model to Online Bioinformatics Education
Dr. Michael Love, edX Faculty and post-doctoral fellow in Dept. Biostatistics, Dana Farber Cancer Institute and Harvard School of Public Health.
Dr. Love teaches the Data Analysis for Genomics course offered...

This is a PDF of the GOBLET poster presentation at ISMB 2014 in Boston.

Explore use of Cufflinks in reference annotation based transcript (RABT) assembly mode and ‘de novo’ assembly mode. Both modes require a reference genome sequence.
 

Get FPKM style expression estimates using Cufflinks

        Perform differential expression analysis with Cuffdiff

        Perform summary analysis with CummeRbund

        Downstream interpretation of expression analysis (multiple testing, clustering, heatmaps, classification, pathway analysis, etc.)

Use of Bowtie/TopHat

        ‘Regular mode’ vs. ‘Fusion mode’

        Introduction to the BAM format

        Basic manipulation of BAMs with samtools, etc.

        Visualization of RNA-seq alignments - IGV

        BAM read counting and determination of variant allele expression status
 

Basic introduction to biology of RNA-seq

        Experimental design considerations

        Commonly asked questions

        Data visualization using IGV

Functional association networks and gene function prediction

    Homology based prediction

    Guilt-by-association: GeneMANIA

Introduction to network visualization

    Visualizing omics data on a network or pathway

    Active modules in Cytoscape

Introduction to pathway and network analysis

    Basic network concepts

    Types of pathway and network information

    Pathway Databases: Reactome, KEGG, etc.

    Pathway analysis of large scale genomics data sets, including cancer genomics

Overview of transcription

    Data sources for regulatory data - Chromatin IP, DNA hypersensitivity, other chip data

    Basics of processing data

    Pattern discovery

Over-representation analysis (ORA)

    Statistics for detecting over-representation e.g. hypergeometric test, GSEA

    Multiple testing correction: Bonferroni, Benjamini-Hochberg FDR

    Filtering Gene Ontology e.g. using evidence codes

Gene list analysis overview: Workflow of concepts and tools from gene list to pathway analysis

    Where do gene lists come from?

    Working with gene function information

How to create a constant gate for the whole data set for one channel by first creating a sample representative of the whole data set

    How to apply a static gate to all samples and count the proportions of cells lying on either side of the gate

    Visualizing the proportions using a density...

Lecture on FlowCAP (Flow Cytometry: Critical Assessment of Population Identification Methods) project

    K-means explained

    flowMeans: smart k-means for FCM data

    flowClust3.0, SPADE, flowBin, flowFP, SamSPECTRAL clustering

    Biomarker discovery: flowType and RchyOptimyx, advanced tools used...

Using quantiles to set a gate based on a negative control

    Using median and standard deviation to set a gate based on a negative control

    Exploring rangeGate: an automated way to set a 1D gate for each sample individually

    Recording proportions of cells in subpopulations of interest by...

Preprocessing

            Removing margin events

            Data transformation: log vs. biexponential

            Data normalization


    Quality Assurance

            Overview of quality assurance concepts: total raw/viable cell count, margin event count, outlier detection based on density of common...

Loading a single or groups of FCS files into R

    flowFrame and flowSet objects and their attributes

    Exploring sample annotation and keywords stored within the FCS file format, searching for specic samples (such as controls) using grep, highlighting the importance of correct sample annotation...

Lecture on how tools to be demonstrated have been used in research and clinical applications

    Description of data and underlying biological problem

    Summary of a typical work flow to be covered in the workshop: transformation, margin event removal, quality assurance, gating, recording and...