Introduction to Galaxy

Transcription

1 Introduction to Galaxy Dr Jason Wong Prince of Wales Clinical School Introductory bioinformatics for human genomics workshop, UNSW Day 1 Thurs 28 th January 2016

2 Overview What is Galaxy? Description of the web interface. Description of file formats used. How to Upload files to Galaxy. Join 2 data sets. Text Manipulations Group, count, sort, filter Genomic operations Using histories and workflows.

3 What is Galaxy? Galaxy is a scientific workflow, data integration, and data analysis platform that aims to make computational biology accessible to research scientists that do not have computer programming experience. It has a web-based framework for running command-line utilities from a user-friendly graphical interface.

4 Galaxy Web Interface Tool bar Contains the available steps to apply to data History Shows steps previously taken to manipulate input data. Focus pane Shows options, parameters and output for current item.

5 What is Galaxy? The Galaxy web server that we will be using today is the Galaxy Main, which is hosted at Penn State. But there are many other instances located all around the world including one at the Garvan, UQ, VLSCI, etc Not all instances have the same functions and people can add their own plugins to the original version of Galaxy.

6 What can we use Galaxy for? Mainly designed to process genomic data. By default contains standard tools necessary for NGS data analysis. Alignment Variant calling RNA-seq ChIP-seq, etc But can be used for just about any type of text data manipulation.

7 Example uses Find the intersection of two sets of genomic intervals. Filter specific lines in a text file. Perform variant calling on exome sequencing data. Gene expression analysis from RNA-seq data. Generate summary statistics on columns. Useful for manipulating files too large for Excel and not ready to learn R or Linux. Usage is basically limitless and is dependent on plug-in tools available.

8 What else is Galaxy good for? Automatically keeps track of all operations and datasets at each step. Accessible Workflows can be stored and automated. Data and workflows can be shared between users. Reproducible Transparent

9 Create a free account

10 Overview of the Functions in the Tool bar The set of functions under Filter and Sort consist of MS Excel like commands. Filter Sort Select lines It also contains operations on GFF (another file format like BED)

11 Overview of the Functions in the Tool bar The set of functions under Join, Subtract and Group are standard SQL operations on datasets. Subtract one dataset from another Join two datasets Compare two data sets to find rows in common or distinct. Group data by column

12 Overview of the Functions in the Tool bar The set of functions under Operate on Genomic Intervals are operations on genomic coordinates (BedTools). Subtract intervals of two datasets Intersect intervals of two datasets Join intervals of two datasets Get flanks Get complements of intervals etc

13 Overview of the Functions in the Toolbar The set of functions under Text manipulation consist of basic linux commands for text files. add a value to each row, add a column, Merge 2 datasets Convert delimiters (e.g comma to tab) Merge columns Cut, Paste Change case (e.g. upper case to lower case) Remove beginning of file Select random lines, select first n lines, select last n lines

14 Upload files to Galaxy

15 Description of File Formats The main type of file that will be used today is the.bed file format. It is a tab-delimited text file that contains genomic coordinates. Can be viewed through any text editor or MS Excel

16 In this tutorial, we will try to work out the top 5 most mutated genes in this pediatric brain cancer set. PediatricBrain_mutations.bed contains somatic point mutations from 100 pediatric brain cancer samples from the ICGC ( more on ICGC tomorrow. hg19_gene_exons.bed contains the coordinates of coding exons from all genes with the gene name in the 4 th column. Non-coding Intergenic region Coding

17 Brings up a pop-up window where we can drag and drop local files

18 Type bed Type hg19 Drop in hg19_gene_exons.bed and PediatricBrain_mutations.bed. Make sure hg19 is selected as the Genome and bed as Type.

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21 Step 1 Joining exons with mutations (i.e. printing exons and mutations that overlap side by side)

22 It can be seen that some genes such as PIK3CD come up twice even in the window meaning that this gene must be mutated at least twice.

23 Step 2 Counting the number of mutations per gene We can easily compute the number of mutations per gene by simply counting the number of repetitions of name for each gene. This can be easily done with the Join, Subtract, and Group -> Group tool Column 4 contains the gene name 4.

24 Need to tell Galaxy to count the number of occurrences of each item (gene) in column 4

25 Mutation count for each gene is shown. Now how do we find the top 5 mutated genes in the list?

26 Step 3 Sort genes by mutation count

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28 Make histogram to view distribution of mutations Set the way the histogram looks

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30 Which samples have FGFR1 mutations? Step 1 get FGFR1 exons

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32 Step 2 Join mutations with exons This time make sure PediatricBrain_mutations.bed is first!

33 5 samples have 6 mutations with DO35937 with 2 mutations. chr8: is mutated in 2 samples chr8: is mutated in 3 samples This strongly suggest that these mutations are being selected for in pediatric brain cancer. We will look into annotating mutations/snps tomorrow.

34 Saving the history

35 Or just create an account... Australian academic Galaxy servers are faster and provides much more space. See links in resources file.

36 Workflows We will use a publically available workflow to add chr to the chromosome number in column 1 of the bed file. Upload hg19_genes_nochr.bed From workshop_files

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42 Further reading Official Galaxy tutorial Genomics Virtual Lab tutorial (maintained by VLSCI) Papers about Galaxy Operating on genomic intervals Bedtools (