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Command Line Tools for Genomic Data Science

With genomics sparks a revolution in medical discoveries, it becomes imperative to be able to better understand the genome, and be able to leverage the data and information from genomic datasets. Genomic Data Science is the field that applies statistics and data science to the genome.This Specialization covers the concepts and tools to understand, analyze, and interpret data from next generation sequencing experiments. It teaches the most common tools used in genomic data science including how to use the command line, along with a variety of software implementation tools like Python, R, Biocon

Created by: Liliana Florea

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Course Description

Introduces to the commands that you need to manage and analyze directories, files, and large sets of genomic data. This is the fourth course in the Genomic Big Data Science Specialization from Johns Hopkins University.

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Instructor Details

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Dr. Liliana Florea is an Assistant Professor of Medicine in the McKusick-Nathans Institute of Genetic Medicine, where she develops computational methods for analyzing large scale sequencing data to help characterize molecular mechanisms of diseases. Her research interests include comparing and analyzing genomes, characterizing genes and alternative splicing variations, and predicting non-coding RNA elements in human-virus interactions. Before joining the Johns Hopkins faculty in 2011, Dr. Florea served on the faculty at the George Washington University. Previously, she was a member of the team of scientists at Celera Genomics that produced the first sequence of the human genome. Her work has been recognized with a Sloan Research Fellowship in Computational and Evolutionary Molecular logy, and she received several early career awards while at the George Washington University. Dr. Florea holds a PhD degree from the Pennsylvania State University.

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Reviews

3.8

82 reviews in total

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By Andrew M on 22-Aug-19

Interesting course. I have used some of this tools for some time but I find their's still something new to learn

By José A C E on 4-Aug-19

I considered this course was condiserably harder than previous courses from the Genomic Data Science specialization due to lacking instructions and exams asking about concepts not reviewed in class, for instance, soft/hard links distinctions, the use of cuffcompare, a clear distinction between mate reads and paired reads, a thorough explanation of the use of CDS vs exon in gtf files. At the other hand, the difficulty possed by this course made it satisfying. I would really like the course team and support to consider add complementary readings in order to help the understanding of topics not intensely reviewd in the videos.

By Noam H on 2-Jun-19

Great and practical material. Instructions for tests aren't clear and sometimes very time consuming to understand

By Thiago C S on 15-May-19

Some questions were way too specific and out of scope from real practice.

By Geoffrey K on 22-Apr-19

A worthy introduction to the problems facing computational biologists.

By Javier A D on 15-Apr-19

I really like this course! (The exams are a bit challenging though.)

By Jitesh D on 30-Mar-19

Course content is really good! Lot of informational resources. Course delivery was little monotonous though. Exam 4 really made it very difficult due to not so clear instructions, otherwise it was a good course. Learnt lot of command lines tools and mainly to effectively use Linux commands in analysis.

By Erik K on 4-Mar-19

Excellent Introduction to Command Line Tools used in High Throughput Sequencing Analysis.

By 李俊宏 on 3-Mar-19

This course is reasonably difficult. The assignments are quite fulfilling and well organized by virtual machine. I hope the slides could be more detailed because it too simple.

By Keri M on 27-Feb-19

I learned a ton and feel like I understand the formats of all of the different really well. I will say that week 4 is out of date in that Tophat has been replaced with HISAT and I wasn't able to download the tools needed. It wasn't a waste of time to learn tophat but would have been nice to learn the most recent tools.

By Tran N on 25-Feb-19

It was a quite challenging experience, especially the final module. The problem you have to deal with is not "how to properly use the programs/tools", instead, we have to learn "how to play with the parameters" so that we can have the right answers for the quiz/exam questions. There were a lot of failures throughout this course, I had to watch the lectures again and again, deeply dive into the discussions in course forum, search google and seqsanswer/biostar forum, etc.... I became hating the lecturer and the mentors for theirs not so well organized lectures and answers ... But afterall, I've learned a lot. Thank you!

By Amy G on 16-Feb-19

This course is not at all up to the standards set by its companion courses. The assignments require a VMbox that is broken, the transcripts are way off base, the tools are somewhat out of date, and the content and message board reflect lack of sincere oversight and care for student experience. Yes, it is possible to pass if you are diligent. Yes, it contains useful commands. No, it is not at all worth the effort. It should be replaced, removed for the sequence, or severely revised.

Showing 12 of 82 reviews

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Overall Score : 76 / 100