Syllabus

January 15: Introduction lecture[ ]

January 18: MLK day

January 20: Let's get started moving into the terminal and tools we will need.

First we will install the following tools.

Terminals:

Mac:

• preferred: iterm2
• alternate: Mac Terminal

PC:

• preferred: Windows Subsystem for Linux -- Ubuntu 18.04
• alternate: Git Bash

SSH Client:

Mac:

• iterm will work for this!

PC:

• preferred: putty

FTP Client:

Mac:

• preferred: FileZilla
• alternate: Cyberduck

PC:

• preferred: FileZilla

Text Editor:

• preferred: Atom
• alternate: Sublime

Github:

• Sign up for an account at github.com
• You can get lots of deals with the GitHub student pack

Slack:

• Download here
• Sign up for the class slack here

January 22: Welcome to FIJI lecture by Jon and Matt [ lecture ]

January 25: Data Reproducibility [lecture]

• Exploring all the data in ENCODE -*- 01_encode.Rmd

January 27: #!bin/bashing data

-*- 02_bashing_data.Rmd

January 29: Git, got it good!

-*- 03_git.Rmd

February 1: Zhiping ENCODE guest lecture

February 3: Fiji-viz R Studio

-*- 04_R-eading_in_files.Rmd

February 5: Creating a design file -- bashing R.

-*- 05_design_file.Rmd

February 8: Flowing forward with Nextflow [ lecture ]

-install nextflow

February 10: Nextflow set up, slurm and run!

-*- 06_nextflow.Rmd

February 12: Looking under the hood of Nextflow [ lecture ]

• debugging nextflow run

February 15: Visualization of Data

• Igv, UCSC file formats.

February 17: Wellness Day

February 19: Student presentations of data

February 22: Explore larger pre-cooked data set

February 24: Iranges and Granges

-*- 07_Granges.Rmd

February 26: From DNA protein structure to meta-analyses [ Lecture ]

-brainstorm analyses students are interested in performing.

March 1: ExploRing Data in R part I (Defining Consensus Peaks)

-*- 08_consensus_peaks.Rmd

March 3: ExploRing Data in R part II

-*- 09_intersecting_features_peak_characteristics

March 5: Intuitive statistical principles [ Lecture ]

March 8: Applying statistics to our data set part I (global clustering, promter_feature_profile_plots)

-*- 10_statistical_significance_of_feature_overlaps -read Class, Mele and Kelley papers

March 10: Applying statistics to our data set part II (lncRNA -vs- mRNA promoters).

-*- 11_permuations_fisher_exact.

March 12: Class Paper discussion and outline.

-Class, Mele and Kelley et al paper discussion.

March 15: ExploRing Repeat Features

-*- 12_repeats

March 17

March 19

March 22

March 24: wellness day 2 (for this class)

March 26:

March 29:

March 31

April 2

April 5

April 7

April 9

April 12

April 14

April 16

April 19

April 21

April 23

April 26

April 28

END