This document provides an overview of analyzing RNA-Seq data using the Tuxedo protocol in Galaxy. It describes experimental design considerations, quality control of sequencing data using FastQC, mapping reads to a reference genome using Tophat, determining differential expression with Cuffdiff, and visualizing results using IGV and CummeRbund. The tutorial walks through an example analysis on Drosophila melanogaster RNA-Seq data, covering topics such as setting file formats, running alignment and expression tools, extracting workflows, and useful Galaxy resources.
whole genome analysis
history
needs
steps involved
human genome data
NGS
pyrosequencing
illumina
SOLiD
Ion torrent
PacBio
applications
problems
benefits
Next generation-sequencing.ppt-convertedShweta Tiwari
The advance version, sequences the whole genome efficiently with high speed and high throughput sequencing at reduce cost is termed as Next Generation Sequencing (NGS) or massively parallel sequencing (MPS).
The quality of data is very important for various downstream analyses, such as sequence assembly, single nucleotide polymorphisms identification this ppt show parameters for
NGS Data quality check and Dataformat of top sequencing machine
RNA Sequence data analysis,Transcriptome sequencing, Sequencing steady state RNA in a sample is known as RNA-Seq. It is free of limitations such as prior knowledge about the organism is not required.
RNA-Seq is useful to unravel inaccessible complexities of transcriptomics such as finding novel transcripts and isoforms.
Data set produced is large and complex; interpretation is not straight forward.
A brief introduction to amplicon sequencing of the 16S rRNA gene for the analysis of microbial diversity. This talk was presented originally at the Workshop: Introduction to Systems Biology, Aalborg Denmark. 2013-10-29
Next Generation Sequencing (NGS) Is A Modern And Cost Effective Sequencing Technology Which Enables Scientists To Sequence Nucleic Acids At Much Faster Rate. In This Presentation, You Will Learn About What is NGS, Idea Behind NGS, Methodology And Protocol, Widely Adapted NGS Protocols, Applications And References For Further Study.
whole genome analysis
history
needs
steps involved
human genome data
NGS
pyrosequencing
illumina
SOLiD
Ion torrent
PacBio
applications
problems
benefits
Next generation-sequencing.ppt-convertedShweta Tiwari
The advance version, sequences the whole genome efficiently with high speed and high throughput sequencing at reduce cost is termed as Next Generation Sequencing (NGS) or massively parallel sequencing (MPS).
The quality of data is very important for various downstream analyses, such as sequence assembly, single nucleotide polymorphisms identification this ppt show parameters for
NGS Data quality check and Dataformat of top sequencing machine
RNA Sequence data analysis,Transcriptome sequencing, Sequencing steady state RNA in a sample is known as RNA-Seq. It is free of limitations such as prior knowledge about the organism is not required.
RNA-Seq is useful to unravel inaccessible complexities of transcriptomics such as finding novel transcripts and isoforms.
Data set produced is large and complex; interpretation is not straight forward.
A brief introduction to amplicon sequencing of the 16S rRNA gene for the analysis of microbial diversity. This talk was presented originally at the Workshop: Introduction to Systems Biology, Aalborg Denmark. 2013-10-29
Next Generation Sequencing (NGS) Is A Modern And Cost Effective Sequencing Technology Which Enables Scientists To Sequence Nucleic Acids At Much Faster Rate. In This Presentation, You Will Learn About What is NGS, Idea Behind NGS, Methodology And Protocol, Widely Adapted NGS Protocols, Applications And References For Further Study.
New High Throughput Sequencing technologies at the Norwegian Sequencing Centr...Lex Nederbragt
A talk I gave at the Microbiology Research Group (University of Oslo) about new High Throughput Sequencing instruments at the Norwegian Sequencing Centre. I also mentioned future upgrades, and the upcoming nanopore sequencing platform of Oxford nanopore
Molecular QC: Interpreting your Bioinformatics PipelineCandy Smellie
What is the impact of assay failure in your laboratory and how do you monitor for it?
The most heavily degraded samples are not suitable for standard exome coverage: sometimes it’s not even a matter of getting bad sequencing, you might get nothing at all!
FFPE artifacts increase with storage time
Artifacts go against the statistical power of your variant calling analysis
Molecular reference standards help filter out bad mappings and spurious variants
Bioinformatics pipelines allow adding Molecular Reference Standards in your joint variant calling pipeline
Genome In A Bottle Reference Standards are invaluable for validating variant calling analysis
NIST and its collaborators shared datasets created with most NGS technologies
Horizon Diagnostics shared annotated, merged variant calls from NIST for the Ashkenazim Trio
~35K variants are predicted having high or moderate impact within the Trio
GM24385 (Ashkenazim Son) includes 352 small variants with high/moderate impact which are absent in Father and Mother
Routinely monitor the performance of your workflows and assays with independent external controls
Dr. Douglas Marthaler - Use of Next Generation Sequencing for Whole Genome An...John Blue
Use of Next Generation Sequencing for Whole Genome Analysis of Pathogens - Dr. Douglas Marthaler, Veterinary Diagnostic Laboratory, College of Veterinary Medicine, University of Minnesota, from the 2016 Allen D. Leman Swine Conference, September 17-20, 2016, St. Paul, Minnesota, USA.
More presentations at http://www.swinecast.com/2016-leman-swine-conference-material
my students use ideas from my class on business models to develop a business model for ion proton's DNA sequencer. This sequencer uses semiconductor technology to read an organism's DNA sequence and is faster and cheaper than existing sequencers. This presentation describes the value proposition, customer selection, method of value capture and other aspects of a business model for Ion Proton's DNA sequencer
NGS Targeted Enrichment Technology in Cancer Research: NGS Tech Overview Webi...QIAGEN
This slidedeck discusses the most biologically efficient, cost-effective method for successful NGS. The GeneRead DNA QuantiMIZE Kits enable determination of the optimum conditions for targeted enrichment of DNA isolated from biological samples, while the GeneRead DNAseq Panels V2 allow you to quickly and reliably deep sequence your genes of interest. Applications in translational and clinical research are highlighted.
Knowing Your NGS Upstream: Alignment and VariantsGolden Helix Inc
Alignment algorithms are not just about placing reads in best-matching locations to a reference genome. They are now being expected to handle small insertions, deletions, gapped alignment of reads across intron boundaries and even span breakpoints of structural variations, fusions and copy number changes. At the same time, variant-calling algorithms can only reach their full potential by being intimately matched to the aligner's output or by doing local assemblies themselves. Knowing when these tools can be expected to perform well and when they will produce technical artifacts or be incapable of detecting features is critical when interpreting any analysis based on their output.
This presentation will compare the performance of the alignment and variant calling tools used by sequencing service providers including Illumina Genome Network, Complete Genomics and The Broad Institute. Using public samples analyzed by each pipeline, we will look at the level of concordance and dive into investigating problematic variants and regions of the genome.
Next-Generation Sequencing an Intro to Tech and Applications: NGS Tech Overvi...QIAGEN
This slidedeck provides a technical overview of DNA/RNA preprocessing, template preparation, sequencing and data analysis. It covers the applications for NGS technologies, including guidelines for how to select the technology that will best address your biological question.
"Einstürzenden Neudaten: Building an Analytics Engine from Scratch", Tobias J...Dataconomy Media
"Einstürzenden Neudaten: Building an Analytics Engine from Scratch", Tobias Johansson, Lead Developer at Valo.io
Watch more from Data Natives Berlin 2016 here: http://bit.ly/2fE1sEo
Visit the conference website to learn more: www.datanatives.io
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https://www.facebook.com/DataNatives
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About the Author:
Tobias is technical lead developer for Valo.io in London. He has a background in the financial sector as a front-office developer but changed track in 2013 to be part of a team building a new real-time analytics platform from the ground up. His goal is to outlive the JVM and his tea addiction. This is his first appearance on the conference scene as a speaker.
Organizations continue to adopt Solr because of its ability to scale to meet even the most demanding workflows. Recently, LucidWorks has been leading the effort to identify, measure, and expand the limits of Solr. As part of this effort, we've learned a few things along the way that should prove useful for any organization wanting to scale Solr. Attendees will come away with a better understanding of how sharding and replication impact performance. Also, no benchmark is useful without being repeatable; Tim will also cover how to perform similar tests using the Solr-Scale-Toolkit in Amazon EC2.
Neuroscience core lecture given at the Icahn school of medicine at Mount Sinai. This is the version 2 of the same topic. I have made some modifications to give a more gentle introduction and add a new example for ngs.plot.
Cassandra Tools and Distributed Administration (Jeffrey Berger, Knewton) | C*...DataStax
At Knewton we operate across five different VPCs a total of 29 clusters, each ranging from 3 nodes to 24 nodes. For a team of three to maintain this is not herculean, however good tools to diagnose issues and gather information in a distributed manner are vital to moving quickly and minimizing engineering time spent.
The database team at Knewton has been successfully using a combination of Ansible and custom open sourced tools to maintain and improve the Cassandra deployment at Knewton. I will be talking about several of these tools and giving examples of how we are using them. Specifically I will discuss the cassandra-tracing tool, which analyzes the contents of the system_traces keyspace, and the cassandra-stat tool, which gives real-time output of the operations of a cassandra cluster. Distributed administration with ad-hoc Ansible will also be covered and I will walk through examples of using these commands to identify and remediate clusterwide issues.
About the Speaker
Jeffrey Berger Lead Database Engineer, Knewton
Dr. Jeffrey Berger is currently the lead database engineer at Knewton, an education tech startup in NYC. He joined the tech scene in NYC in 2013 and spent two years working with MongoDB, becoming a certified MongoDB administrator and a MongoDB Master. He received his Cassandra Administrator certification at Cassandra Summit 2015. He holds a Ph.D. in Theoretical Physics from Penn State and spent several years working on high energy nuclear interactions.
Next-generation sequencing data format and visualization with ngs.plot 2015Li Shen
An introduction to the commonly used formats for the next-generation sequencing data. ngs.plot is a popular tool for the visualization and data mining of the NGS data.
Next-generation sequencing format and visualization with ngs.plotLi Shen
Lecture given at the department of neuroscience, Icahn school of medicine at Mount Sinai. ngs.plot has been published in BMC genomics. Link: http://www.biomedcentral.com/1471-2164/15/284
Open Source Cloud Sync and Share software provides synchronisation layer on top of a variety of backend storages such as local filesystems and object storage. In case of some software stacks, such as ownCloud, a SQL database is used to support the synchronisation requirements.
We tested how different technology stacks impact the ownCloud HTTP-based Synchronisation Protocol. Efficiency and scalability analysis was performed based on benchmarking results. The results have been produced using the ClawIO framework prototype.
ClawIO is a Cloud Synchronisation Benchmarking Framework. The software provides a base
architecture to stress different storage solutions against different cloud synchronisation protocols.
Such architecture is based on the IETF Storage Sync draft specification and CERN EOS.
The synchronisation logic is divided into control and data servers.
This separation is done by the use of highly-decoupled micro services connected to each other using high performance communication protocols such a gRPC and HTTP/2.
Serverless on OpenStack with Docker Swarm, Mistral, and StackStormDmitri Zimine
Intro to Serverless, 101 demo with StackStorm, and real world application of serverless solution.
Slides for OpenStack Summit Boston 2017 talk:
https://www.openstack.org/summit/boston-2017/summit-schedule/events/18325
Most of the talk was a demo, please stay tuned for recording.
Serverless, devops, automation, operations, faas, @Stack_Storm.
"Finding Bad Needles on a Worldwide Scale" - presentation on our experience of developing, testing and improving cross-site scripting scanners and the methods of more accurate web application security testing. See 2015.appsec.eu for more information.
Genome Wide SNP Analysis for Inferring the Population Structure and Genetic H...Hong ChangBum
Study of genome-wide SNPs, mitochondrial DNA and Y-chromosomal DNA variation can provide a valuable information about the population structure and peopling of human populations. To explain a genetic homogeneity of Koreans and population structure of Koreans and the East Asian populations, we analyzed 153 individuals from the Korea and 77 individuals from the East Asia at 46,559 common single-nucleotide polymorphic loci. The 137 CHB and 113 JPT individuals at 25,769 common SNPs from the International HapMap project were further analyzed to reveal the population structure of the East Asians. Principal Component analyses (PCA) and population differentiation ( ) are examined. In the PCA test, the Jeju individuals were slightly different from other Koreans but their values were not significant. This reflect the genetic homogeneity of Korea population. In general, all the individual samples studied here were clustered into subset of ethnic origin according to their geographical location except Mongolians. Whole genome sequencing of Koreans and other population genome by next generation sequencing technology will provide great opportunity to understand the population expansion and peopling of Korea better.
Perspectives of identifying Korean genetic variationsHong ChangBum
Single Nucleotide Polymorphism (SNP) is the genetic variation most frequently occurred in human genome. SNP is considered as one of the well characterized genetic marker which is useful for the research on human disease genomics as well as the human population stratification. Currently a type of structural variation in the genome, so called Copy Number Variation (CNV), have received public attention in the hope to get additional genetic information that can not be answered by SNPs.
To gain insight into Korean specific genetic markers, we analyzed 54,794 SNPs from 159 individuals in 10 regional areas in Korea (CheonAn, NaJu, GimJe, UlSan, Jeju, YeonCheon, JeCheon, GoRyeong, GyeongJu, PyeongChang) and obtained from 1,629 individuals in Pan-Asia (70 population) data set. In addition, we analyzed considerable number of CNVs typed from 16 pairs of twins in Korea.
In our study we were able to identify several informative SNP markers that are valuable to distinguish Korean from other ethnic groups. In addition, the investigation of the distribution of identity by descent (IBD) distance within a large Korean family provided a way to examine relationship between individuals. Another interesting finding resulted from this study include the differences in CNV patterns between identical twins. Possible application of genotype data to figuring out individual phenotypes (such as pigmentation, eye color, hair color, height, blood type, etc.) would be an additional profit obtained from this study in the hope to montage or even identify individuals (such as criminal suspects) using genotype data in the near future.
In this presentation, I will discuss results generated from this study which may represent the most comprehensive characterization to date for the Korean genome.
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
Factory Supply Best Quality Pmk Oil CAS 28578–16–7 PMK Powder in Stockrebeccabio
Factory Supply Best Quality Pmk Oil CAS 28578–16–7 PMK Powder in Stock
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Anti ulcer drugs and their Advance pharmacology ||
Anti-ulcer drugs are medications used to prevent and treat ulcers in the stomach and upper part of the small intestine (duodenal ulcers). These ulcers are often caused by an imbalance between stomach acid and the mucosal lining, which protects the stomach lining.
||Scope: Overview of various classes of anti-ulcer drugs, their mechanisms of action, indications, side effects, and clinical considerations.
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
New Directions in Targeted Therapeutic Approaches for Older Adults With Mantl...i3 Health
i3 Health is pleased to make the speaker slides from this activity available for use as a non-accredited self-study or teaching resource.
This slide deck presented by Dr. Kami Maddocks, Professor-Clinical in the Division of Hematology and
Associate Division Director for Ambulatory Operations
The Ohio State University Comprehensive Cancer Center, will provide insight into new directions in targeted therapeutic approaches for older adults with mantle cell lymphoma.
STATEMENT OF NEED
Mantle cell lymphoma (MCL) is a rare, aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for 5% to 7% of all lymphomas. Its prognosis ranges from indolent disease that does not require treatment for years to very aggressive disease, which is associated with poor survival (Silkenstedt et al, 2021). Typically, MCL is diagnosed at advanced stage and in older patients who cannot tolerate intensive therapy (NCCN, 2022). Although recent advances have slightly increased remission rates, recurrence and relapse remain very common, leading to a median overall survival between 3 and 6 years (LLS, 2021). Though there are several effective options, progress is still needed towards establishing an accepted frontline approach for MCL (Castellino et al, 2022). Treatment selection and management of MCL are complicated by the heterogeneity of prognosis, advanced age and comorbidities of patients, and lack of an established standard approach for treatment, making it vital that clinicians be familiar with the latest research and advances in this area. In this activity chaired by Michael Wang, MD, Professor in the Department of Lymphoma & Myeloma at MD Anderson Cancer Center, expert faculty will discuss prognostic factors informing treatment, the promising results of recent trials in new therapeutic approaches, and the implications of treatment resistance in therapeutic selection for MCL.
Target Audience
Hematology/oncology fellows, attending faculty, and other health care professionals involved in the treatment of patients with mantle cell lymphoma (MCL).
Learning Objectives
1.) Identify clinical and biological prognostic factors that can guide treatment decision making for older adults with MCL
2.) Evaluate emerging data on targeted therapeutic approaches for treatment-naive and relapsed/refractory MCL and their applicability to older adults
3.) Assess mechanisms of resistance to targeted therapies for MCL and their implications for treatment selection
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journeygreendigital
Tom Selleck, an enduring figure in Hollywood. has captivated audiences for decades with his rugged charm, iconic moustache. and memorable roles in television and film. From his breakout role as Thomas Magnum in Magnum P.I. to his current portrayal of Frank Reagan in Blue Bloods. Selleck's career has spanned over 50 years. But beyond his professional achievements. fans have often been curious about Tom Selleck Health. especially as he has aged in the public eye.
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Introduction
Many have been interested in Tom Selleck health. not only because of his enduring presence on screen but also because of the challenges. and lifestyle choices he has faced and made over the years. This article delves into the various aspects of Tom Selleck health. exploring his fitness regimen, diet, mental health. and the challenges he has encountered as he ages. We'll look at how he maintains his well-being. the health issues he has faced, and his approach to ageing .
Early Life and Career
Childhood and Athletic Beginnings
Tom Selleck was born on January 29, 1945, in Detroit, Michigan, and grew up in Sherman Oaks, California. From an early age, he was involved in sports, particularly basketball. which played a significant role in his physical development. His athletic pursuits continued into college. where he attended the University of Southern California (USC) on a basketball scholarship. This early involvement in sports laid a strong foundation for his physical health and disciplined lifestyle.
Transition to Acting
Selleck's transition from an athlete to an actor came with its physical demands. His first significant role in "Magnum P.I." required him to perform various stunts and maintain a fit appearance. This role, which he played from 1980 to 1988. necessitated a rigorous fitness routine to meet the show's demands. setting the stage for his long-term commitment to health and wellness.
Fitness Regimen
Workout Routine
Tom Selleck health and fitness regimen has evolved. adapting to his changing roles and age. During his "Magnum, P.I." days. Selleck's workouts were intense and focused on building and maintaining muscle mass. His routine included weightlifting, cardiovascular exercises. and specific training for the stunts he performed on the show.
Selleck adjusted his fitness routine as he aged to suit his body's needs. Today, his workouts focus on maintaining flexibility, strength, and cardiovascular health. He incorporates low-impact exercises such as swimming, walking, and light weightlifting. This balanced approach helps him stay fit without putting undue strain on his joints and muscles.
Importance of Flexibility and Mobility
In recent years, Selleck has emphasized the importance of flexibility and mobility in his fitness regimen. Understanding the natural decline in muscle mass and joint flexibility with age. he includes stretching and yoga in his routine. These practices help prevent injuries, improve posture, and maintain mobilit
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...kevinkariuki227
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?bkling
Are you curious about what’s new in cervical cancer research or unsure what the findings mean? Join Dr. Emily Ko, a gynecologic oncologist at Penn Medicine, to learn about the latest updates from the Society of Gynecologic Oncology (SGO) 2024 Annual Meeting on Women’s Cancer. Dr. Ko will discuss what the research presented at the conference means for you and answer your questions about the new developments.
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists
Galaxy RNA-Seq Analysis: Tuxedo Protocol
1. Galaxy RNA-Seq
Analysis: Tuxedo Protocol
ChangBum Hong, KT Bioinformatics, GenomeCloud SCIC
genome-cloud.com
This work is licensed under the Creative Commons Attribution-NonCommercialShareAlike 3.0 New Zealand License. To view a copy of this license, visit http://
creativecommons.org/licenses/by-nc-sa/3.0/nz/ or send a letter to Creative
Commons, 171 Second Street, Suite 300, San Francisco, California, 94105, USA.
3. Experimental design
• What are my goals?
• Transcriptome assembly?
• Differential expression analysis?
• Identify rare transcripts?
• What are the characteristics of my system?
• Large, complex genome?
• Introns and high degree of alternative splicing?
• No reference genome or transcriptome?
6. Data Quality Control
• Data Quality Assessment
• Identify poor/bad sample
• Identify contaminates
• Trimming: remove bad bases from read
• Filtering: remove bad reads from library
7. Read Mapping
• Alignment algorithm must be
• fast
• able to handle SNPs, indels, and sequencing errors
• allow for introns for reference genome alignment
• Input
• fastq read library
• reference genome index
• insert size mean and stddev(for paired-end libraries)
• Output
• SAM (text) / BAM (binary) alignment files
8. Differential Expression
• Cuffdiff (Cufflinks package)
• Pairwise comparisons
• Differnetial gene, transcript, and primary transcript
expression
• Easy to use, well documented
• Input: transcriptome, SAM/BAM read alignments
9. Transcriptome Assembly
• RNA-Seq
• Reference genome
• Reference transcriptome
• RNA-Seq
• Reference genome
• No reference transcriptome
• RNA-Seq
• No reference genome
• No reference transcriptome
11. Combining tools in a pipeline
• Linux Command-line Tools
• Shell script, Makefile
• GUI Based pipeline
• DNANexus
• SevenBridegs Genomics
• Galaxy
• Open Source
• Wrapper for command line utilites
• Workflows
• Save all steps you did in your analysis
• Return the entire analysis on a new dataset
• Share your workflow with other people
12. How to use Galaxy?
GALAXY MAIN: User disk quotas 250GB for registered users, maximum concurrent jobs: 8
NO
WAIT
TIMES
NO
NO
JOB
STORAGE
SUBMISSION
QUOTAS
LIMITS
NO
DATA
TRANSFER
BOTTLENECKS
NO
IT
EXPERIENCE
REQUIRED
NO
REQUIRED
INFRASTRUCTURE
COST
GALAXY
MAIN
Free
LOCAL
GALAXY
Free ?
CLOUD
GALAXY
(AMAZON)
동일사양 대비
약 2배 (KT의)
SLIPSTREAM
GALAXY
$19,995
(2천2백만원)
KT
GenomeCloud
GALAXY
시간당 740원
부터
13. Outline of tutorial
• Starting Galaxy
• Mapping with Tophat
• Workflows
• Visualizing alignment with IGV
• Computing differential expression with cuffdiff
• Cuffdiff visuaalization with CummeRbund
14.
15. Starting Galaxy
• Tutorial Dataset
• Accessing Galaxy
• Import files for one sample into current history
• Set file attributes
• Run FastQC
18. Tutorial Dataset
Reference & Gene sets
•illumina iGenomes
• The iGenomes are a collection of reference sequences and annotation files for commonly analyzed
organisms. The files have been downloaded from Ensembl, NCBI, or UCSC, and chromosome names have
been changed to be simple and consistent with their download source. Each iGenome is available as a
compressed file that contains sequences and annotation files for a single genomic build of an organism.
• http://support.illumina.com/sequencing/sequencing_software/igenome.ilmn
19. Tutorial Dataset
Sequencing data
•Sequencing data (Drosophila melanogaster)
• Gene Expression Omnibus at accession GSE32038
• http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32038
21. Accessing Galaxy
•
•
Open a web browser and navigate to Galaxy website usegalaxy.org or www.genome-cloud.com
Log in with username and password
select galaxy service
GenomeCloud (genome-cloud.com)
22. when your galaxy is ready
you will recive the e-mail
access the galaxy via public ip address
you can register via user menu > register
Center pane
Tools pane
History pane
23. Import files
•
•
Open a web browser and navigate to Galaxy website usegalaxy.org or www.genome-cloud.com
Log in with username and password
example fastq and gtf files are located in shared data > RNA-Seq with Drosophila melanogaster
import data into your history panel (read to analysis)
24. Set file attributes
•
•
In the history pane click on the pencil icon
Enter “fastqsanger” (It will takes time)
Sanger Phread+33 fastqsanger (cassava 1.8 ▲ )
Ilumina 1.3 Phread+64 fastqillunina (cassava 1.8 ▼)
Solexa Solexa+64 fastqsolexa
Tophat options
--solexa-quals: Use the Solexa scale for quality values in FASTQ files
--solexa1.3-quals: Phred64/Illumina 1.3~1.5
!
BWA options
-l : The input is in the Illumina 1.3+ read format (quality equals ASCII-64)
!
GenomeCloud (g-Analysis)
28. illumina
(in-house data)
IonTorrent
(in-house data)
illumina
(good dataset in FastQC homepage)
illumina
(bad dataset in FastQC homepage)
Per base sequence quality
illumina
(in-house data)
IonTorrent
(in-house data)
illumina
(good dataset in FastQC homepage)
illumina
(bad dataset in FastQC homepage)
Per sequence quality score
illumina
(in-house data)
IonTorrent
(in-house data)
illumina
(good dataset in FastQC homepage)
Per base sequence content
illumina
(bad dataset in FastQC homepage)
29. illumina
(in-house data)
IonTorrent
(in-house data)
illumina
(good dataset in FastQC homepage)
illumina
(bad dataset in FastQC homepage)
Per base GC content
illumina
(in-house data)
IonTorrent
(in-house data)
illumina
(good dataset in FastQC homepage)
illumina
(bad dataset in FastQC homepage)
Per sequence GC content
illumina
(in-house data)
IonTorrent
(in-house data)
illumina
(good dataset in FastQC homepage)
Per base N content
illumina
(bad dataset in FastQC homepage)
30. illumina
(in-house data)
IonTorrent
(in-house data)
illumina
(good dataset in FastQC homepage)
illumina
(bad dataset in FastQC homepage)
Sequence Length Distribution
illumina
(in-house data)
IonTorrent
(in-house data)
illumina
(good dataset in FastQC homepage)
Sequence Duplication Levels
illumina
(bad dataset in FastQC homepage)
31.
32. Mapping with Tophat
• Initial Tophat run
• Determine insert size
• Rerun Tophat with correct insert size
• Review mapping statistics
33. Initial Tophat run
•
•
•
Use Full Tophat paramters
Paired-end FASTQ files, Select reference genome, Use Own Juctions(Yes), Use Gene Annotation Model(Yes)
Gene Model Anntations (use GFF file)
36. Rerun Tophat
•
•
•
Click any one of the Tophat2 output files in the history panne
Click on the circular blue arrow icon
Change the “Mean Inner Distance between Mate Pairs” (198)
37. Tophat Output
•
•
unmapped.bam (BAM)
•
junctions.bed (BED): list BED track of junctions reported by Tophat
where each junction consists of two connected BED blocks where
each block is as long as the max overhang of nay read spanning
juction
•
deletions.bed (BED): mentions the last genomic base before the
deletion
•
insertions.bed (BED): mentions the first genomic base of deletion
accepted_hits.bam (BAM): a list of read alignments in BAM/SAM
format
38. Load files into IGV
•
•
•
•
Click on the “accepted hits” file in the history pane
Click on the “display with IGV web current”
A file named “igv.jnlp” will be downloaded by your browser
Open with text editor copy BAM file location
39. IGV with Housekeeping gene
http://www.sabiosciences.com/rt_pcr_product/HTML/PADM-000Z.html
40. Load files into IGV
•
•
Enter “Act42A” in the search box to view the reads aligning
Right-click on the coverage track and select “Set Data Range” (max value to 4372)
Housekeeping gene: Act42A
Set max value
48. •
•
View and filter cuffdiff
output
Differential Gene Expression (DGE)
Filter out genes with significant change in expression with a log fold-change of at least 1 “C14
== ‘yes’ and abs(c10)>1” in the “With following condition” text box
51. Samples have similar density
distribution(density plot)
Samples cluster by expression condition
(MDS / PCA plot)
Samples cluster by experimental condition
(Dendogram)
52. Volcano
Differential analysis results for regucalcin
Expression plot shows clear differences in the
expression of regucalcin across conditions C1
and C2 (four alternative isoforms)
Scatter plots highlight general similarities
and specific outliers between conditions
C1 and C2
54. Edit workflow
•
•
Click on “Workflow” at the top of the Galaxy window
Move the elements of the workflow
55. Run workflow
•
•
•
Load a workflow by clicking on “Workflow” ath the top of the screen
Click on “Run”
Select the input datas
56.
57. Useful galaxy sites
•
Public main galaxy site (user disk quotas 250GB for registered users, maximum concurrent jobs: 8)
•
•
Test galaxy site (beta site for galaxy main instance)
•
•
http://hongiiv.tistory.com/701
Galaxy를 이용한 SNP 분석 (Korean)
•
•
https://wiki.galaxyproject.org/Learn
Galaxy를 이용한 NGS 분석 (Korean)
•
•
https://test.galaxyproject.org/
Galaxy screen cast and tutorials
•
•
https://usegalaxy.org/
http://hongiiv.tistory.com/652
Galaxy를 이용한 부시맨 genome 분석 (Korean)
•
http://hongiiv.tistory.com/655