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.
이 강좌는 Genomic Data Science 전문 분야의 일부입니다.
Command Line Tools for Genomic Data Science
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About this Course
최근 조회 37,453회
학습자 경력 결과
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이 강좌를 수료한 후 새로운 경력 시작하기
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급여 인상 또는 승진하기
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지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 전문 분야의 8개 강좌 중 5번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
완료하는 데 약 12시간 필요
영어
자막: 영어
귀하가 습득할 기술
BioinformaticsSamtoolsUnixCommand-Line Interface
학습자 경력 결과
50%
이 강좌를 수료한 후 새로운 경력 시작하기
43%
이 강좌를 통해 확실한 경력상 이점 얻기
20%
급여 인상 또는 승진하기
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 전문 분야의 8개 강좌 중 5번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
완료하는 데 약 12시간 필요
영어
자막: 영어
제공자:
존스홉킨스대학교
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
강의 계획 - 이 강좌에서 배울 내용
완료하는 데 3시간 필요
Basic Unix Commands
In this module, you will be introduced to command Line Tools for Genomic Data Science
완료하는 데 3시간 필요
12개 동영상 (총 105분), 5 readings, 2 quizzes
12개의 동영상
Basic Unix Commands 2: Files, Directories, Paths7m
Basic Unix Commands 3: File Naming4m
Basic Unix Commands 4: Content Creation9m
Basic Unix Commands 5: Accessing Content I6m
Basic Unix Commands 6: Accessing Content II4m
Basic Unix Commands 7: Redirecting Content6m
Basic Unix Commands 8: Querying Content15m
Basic Unix Commands 9: Comparing Content11m
Basic Unix Commands 10: Archiving Content13m
Basic Unix Commands 11: Practical Exercises I13m
Basic Unix Commands 12: Practical Exercises II9m
5개의 읽기 자료
Welcome Message10m
Syllabus10m
VMBox Download & Instructions10m
Pre-Course Survey10m
Module 1 Exam Instructions **IMPORTANT**10m
2개 연습문제
Module 1 Quiz20m
Module 1 Exam34m
완료하는 데 3시간 필요
Week Two
In this module, we'll be taking a look at Sequences and Genomic Features in a sequence of 10 presentations.
완료하는 데 3시간 필요
11개 동영상 (총 127분), 1 reading, 2 quizzes
11개의 동영상
Sequences and Genomic Features 2: Sequence Representation and Generation11m
Sequences and Genomic Features 3: Annotation14m
Sequences and Genomic Features 4.1: Alignment I13m
Sequences and Genomic Features 4.2: Alignment II9m
Sequences and Genomic Features 5: Recreating Sequences & Features12m
Sequences and Genomic Features 6: Genomic Feature Retrieval5m
Sequences and Genomic Features 7: SAMtools I11m
Sequences and Genomic Features 8: SAMtools II9m
Sequences and Genomic Features 9: BEDtools I15m
Sequences and Genomic Features 10: BEDtools II15m
1개의 읽기 자료
Module 2 Exam Instructions **IMPORTANT**10m
2개 연습문제
Module 2 Quiz20m
Module 2 Exam40m
완료하는 데 2시간 필요
Week Three
In this module, we'll be going over Alignment and Sequence Variation in another sequence of 8 presentations.
완료하는 데 2시간 필요
8개 동영상 (총 55분), 1 reading, 2 quizzes
8개의 동영상
Alignment & Sequence Variation 2: Alignment & Variant Detection Tools5m
Alignment & Sequence Variation 3: VCF11m
Alignment & Sequence Variation 4: Bowtie9m
Alignment & Sequence Variation 5: BWA 4m
Alignment & Sequence Variation 6: SAMtools (mpileup)6m
Alignment & Sequence Variation 7: BCFtools8m
Alignment & Sequence Variation 8: Variant Calling5m
1개의 읽기 자료
Module 3 Exam Instructions **IMPORTANT**10m
2개 연습문제
Module 3 Quiz20m
Module 3 Exam48m
완료하는 데 3시간 필요
Week Four
In this module, we'll be going over Tools for Transcriptomics in a sequence of 6 presentations.
완료하는 데 3시간 필요
8개 동영상 (총 75분), 2 readings, 2 quizzes
8개의 동영상
Tools for Transcriptomics 2: RNA-seq7m
Tools for Transcriptomics 3.1: Tophat I9m
Tools for Transcriptomics 3.2: Tophat II 8m
Tools for Transcriptomics 4: Cufflinks10m
Tools for Transcriptomics 5: Cuffdiff16m
Tools for Transcriptomics 6.1: Integrated Genomics Viewer I8m
Tools for Transcriptomics 6.2: Integrated Genomics Viewer II 6m
2개의 읽기 자료
Module 4 Exam Instructions **IMPORTANT**10m
Post-Course Survey10m
2개 연습문제
Module 4 Quiz20m
Module 4 Exam1시 10분
검토
4.2
COMMAND LINE TOOLS FOR GENOMIC DATA SCIENCE의 최상위 리뷰
SC 제공Oct 17, 2016
Th lecturer could be a little more engaging and the materials used during classes, if made available would help following it better, by replicating the examples being shown.
GG 제공May 10, 2017
Great course. The last exam is a little bit tricky, specially when some commands are large and confusing. But with the help of forums, you can still find the right answers.
AD 제공Aug 26, 2018
Very informative course. Only downside is that the example datasets/scripts are not provided (which I tend to find to be useful for learning informatics).
JJ 제공Jun 22, 2018
Thank you very much Dr./Professor, Liliana Florea. I've learned a lot. It's a very good opportunity to improve my knowledge. This means a lot to me.
GV 제공Mar 13, 2016
Very informative course. Because I am new to this, it was at times confusing. But overall, great teaching and great experience. Thank you.
WL 제공Jul 6, 2016
This is perhaps one of the most clearly taught courses I have had on Coursera. Thank you for putting in time to teach us!
AM 제공Aug 21, 2019
Interesting course. I have used some of this tools for some time but I find their's still something new to learn
EK 제공Mar 3, 2019
Excellent Introduction to Command Line Tools used in High Throughput Sequencing Analysis.
VD 제공Jan 8, 2017
More in-depth explanation would be better. Reasonable projects, overall. Well structured.
GY 제공Aug 28, 2017
Highly recommended.\n\nI suggest you take it before "Genomic Data Science with Galaxy".
SA 제공Jul 13, 2018
Great resource to learn unix codes and prepare your self for analysing genomic data
SY 제공Feb 17, 2020
very good course, the flow of the course is really good, learned so many things
RS 제공Mar 16, 2018
This was one of the most valuable courses I have taken online.\n\nThank you
GK 제공Apr 21, 2019
A worthy introduction to the problems facing computational biologists.
YW 제공Apr 14, 2019
I really like this course! (The exams are a bit challenging though.)
YY 제공Feb 26, 2016
very basic and useful command line tools for genomic data analysis.
SM 제공Feb 12, 2018
Great course. I think it should be the first in the whole series.
CZ 제공Feb 9, 2016
I learned a LOT from this class and the instructor is very clear.
QL 제공May 11, 2018
Could have more tools introduced, for instance SNP calling tools.
MA 제공Mar 5, 2017
very information with hands on training exercises.
Genomic Data Science 전문 분야 정보
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, Bioconductor, and Galaxy.
This Specialization is designed to serve as both a standalone introduction to genomic data science or as a perfect compliment to a primary degree or postdoc in biology, molecular biology, or genetics, for scientists in these fields seeking to gain familiarity in data science and statistical tools to better interact with the data in their everyday work.
To audit Genomic Data Science courses for free, visit https://www.coursera.org/jhu, click the course, click Enroll, and select Audit. Please note that you will not receive a Certificate of Completion if you choose to Audit.
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