Bioinformatics for biologists Dr. Habil Zare, PhD PI of Oncinfo Lab Assistant Professor, Department...

Bioinformatics for biologists

Dr. Habil Zare, PhDPI of Oncinfo Lab

Assistant Professor, Department of Computer Science Texas State University

Presented at University of Texas, Health Science Center – San Antonio20 November 2015

Part 1

- BioLinux - Mapping RNAseq data to transcriptome (Salmon)

Bioinformatics for biologists workshop, Dr. Habil Zare, Oncinfo Lab UTHSC San Antonio, 20 Nov 2015

3

Bioinformatics: Computational and statistical analysis of biological data

Data

Biologists

ResultsGenotypes / Phenotypes


4

In this workshop: A compact demo of bioinformatics analysis starting from raw data to produce useful plots and meaningful interpretation of the data

RNAseq

Biologists

Pathway and Network Analysis


5

Goals of the workshop

- A practical introduction to some basic bioinformatics tools for biologists.

- Having hands-on experience with simple, toy-example data.


6

Bio-Linux

Bio-Linux is a free workstation platform that facilitates running hundreds of bioinformatics tools without the corresponding installation hassles.

An easy way to install it on Mac OS X and Windows computers is described below:http://oncinfo.org/file/view/BioLinux_VM.pptx/564155065/BioLinux_VM.pptx

http://oncinfo.org/file/view/BioLinux_VM.pptx/564155065/BioLinux_VM.pptx


7

Browsing files and folders

tar.gz refers to a compressed file in Linux. Let’s practice decompressing such a file with an example. Follow the next steps in BioLinux.


8

.Double-click on Bio-Linux

Documentation to open it.


9

.

Double-click on Introductory Tutorial


10

.Click on File>New TAb


11

.Select the second tab and click

on Home.


12

.

Drag and drop this file from intro_course tab to Home tab.


13

.

Right-click on the file and then Extract Here…


14

.This folder will appear. Open it

and have a look inside.


15

.


16

Downloading and installing

Most useful bioinformatics tools are publicly available. You can download, install, and use them easily.

Let’s practice with an example. Follow the next steps in BioLinux.


17

.

This is the “Dash”. Use it to launch and organize applications.


18

.E.g., use “Firefox” to browse the web.


19

.Type oncinfo.org in the address bar and press enter.


20

From the right menu, click on the workshop link.


21

.

Click on “zipped” to download the folder.


22

.

Choose to save the file.


23

1- Click on Files icon.

2- Click on Downloads.

The file that you just downloaded was saved in Downloades folder.


24

This is the file you just downloaded.

The file that you just downloaded was saved in Downloades folder.


25

Extract (decompress) the file that you just .

Right-click on the file and then Extract Here…


26

The file that you just downloaded in saved in Downloades folder.


27

Salmon

Salmon, a successor of Sailfish, is a useful tool for mapping RNAseq data. It is faster and easier to run than alternatives such as TopHat.


28

Installing Salmon software

We will run a script provided in the zipped file using a terminal.

Terminal is an interface that uses only text to communicate between the user and the computer.


29

.

Click on the black rectangular to open a terminal.

How to open a terminal?


30

.Try a few simple Linux commands e.g.,echo, date, cal, …


31

.

Type “cd” in the terminal to “change directory”.


32

.

Drag the folder to the terminal.


33

.

Now press Enter.


34

. Double-click on the folder to open it.

What is in the folder?


35

Equivalently, “ls” shows you the list

of files in this folder.



36

This script will install Salmon for you.



37

Type the name of the script

and then press Enter.

How to run the script?


38

How to run the script?

Type your password, which is “manager” by default.


39

How to make sure Salmon is installed?

Type “salmon v” to test if it is installed or not.

The script should download and install salmon. The following test indicates that installation was OK.


40

1- A FASTA file, which has the sequence information of the transcriptome of the species of interest.

2- One or more FASTQ files, which are provided by the sequencer instrument and contain the reads information from the samples.

Input for Salmon


41

Toy examples of FASTA and FASTQ files

Open the sample_data folder


42

Next generation sequencing A sequencer produces millions of short reads (50-200 bps).

Biological sample Sequencer Short reads


43

Toy examples of a FASTQ file

Double click on reads_1.fastq file.


44

This is a read of length 50 with nucleotide and (Phred) quality information.

Toy examples of a FASTQ file


45

Double click on transcripts.fasta file.

Toy examples of a FASTA file


46

This is a transcript.



47

It is an mRNA with RefSeq ID NM_001168316



48

Type the RefSeq ID, e.g., NM_001168316

More information on the transcript Search in the NCBI database http://www.ncbi.nlm.nih.gov/nuccore/

http://www.ncbi.nlm.nih.gov/nuccore/






49

Type the RefSeq ID, e.g., NM_001168316

Visualize the transcript on the genome Search in the UCSC genome browserhttps://genome.ucsc.edu/cgi-bin/hgGateway

https://genome.ucsc.edu/cgi-bin/hgGateway



50

This is the transcript

Visualize the transcript on the genome Search in the UCSC genome browserhttps://genome.ucsc.edu/cgi-bin/hgGateway




51

More information on this region is available.

Visualize the transcript on the genome Search in the UCSC Genome Browserhttps://genome.ucsc.edu/cgi-bin/hgGateway




52

Quantify the level of expressionThe level of expression of each transcript can be quantified by counting the number of reads that are aligned to it.


53

Next generation sequencing A sequencer produces millions of short reads (50-200 bps).

Biological sample Sequencer Short reads


54

Only exons are present in mRNA

} } } }

exon 1 exon 2 exon 3 exon 4


55

Alignment

Gene 1 Gene 2

Determines what transcript (where on the genome) each read was originated from.

Short reads in a FASTQ file


56

Alignment

Gene 1 Gene 2

Short reads in a FASTQ file

Determines what transcript (where on the genome) each read was originated from.


57

Alignment

Gene 1 Gene 2

Count the number of aligned (mapped) reads to each region.


58

Alignment

Gene 1 Gene 2

High expression Low expression

Compare the level of expression between genes.


59

Quantifying expression from RNAseq data

Salmon processes raw data and quantifies expression levels in 2 steps.http://salmon.readthedocs.org/en/latest/salmon.html#using-salmon

Step 1- Building an index for the transcriptome. Step 2- Aligning the reads to the transcriptome.

http://salmon.readthedocs.org/en/latest/salmon.html%23using-salmon





60

Are you in the right directory?Before you start, make sure you are in the correct directory.The pwd command in Linux shows the current directory.

Typing “pwd” and then “Enter” will “print the working directory”, i.e., your current path.


61

Always make sure that the files are stored where you expect them to be.

Are you in the right directory?Before you start, make sure you are in the correct directory.The pwd command in Linux shows the current directory.


62

Step 1- Building an index for the transcriptome.

Run the following command in the terminal in BioLinux:

salmon index -t transcripts.fasta -i transcripts_index --type fmd


63

Type the command here.


64

For now, ig

nore this

warning.


65

The index is built.


66

Salmon created a new folder.


67

Step 2- Aligning the reads to the transcriptome.


salmon quant -i transcripts_index –l IU -1 reads_1.fastq -2 reads_2.fastq –o transcripts_quanton


68

Step 2- Aligning the reads to the transcriptome.


}

The command

}

The indexing built in step 1

}

The first input file

}The secondinput file

}

Output folder

salmon quant -i transcripts_index –l IU -1 reads_1.fastq -2 reads_2.fastq –o transcripts_quanton


69

Salmon created a new folder and stored the results there.


70

quant.sf is the main output file that reports the number of reads and expression. Double click on it.


71

The names of the transcripts (RefSeq IDs) and their length are in the first 2 columns.


72

The number of mapped reads is reported on the last column.


73

Transcript per million (TPM) is the estimated expression.


74

Transcript per million (TPM) is the estimated expression.

TPM values correspond to counts normalized by the length of transcripts and also the depth of sequencing. There are other normalization methods such as RPKM and FPKM.


75

This transcript is highly expressed


76

This transcript is highly expressed

These transcripts have low expression.

Instaling BioLinux using VM, Dr. Habil Zare 27 Oct 2015

77

References:

• Some of the slides are based on Introduction to Biolinux http://nebc.nerc.ac.uk/downloads/courses/Bio-Linux/bl8_latest.pdf

• Salmon is a useful tool for mapping and analyzing RNAseq data. https://combine-lab.github.io/salmon/

• I prepared these guidelines to facilitate the “Bioinformatics for biologists workshop”, 20 Nov 2015, UTHSC – San Antonio.http://oncinfo.org/Bioinformatics+for+biologist+workshop

http://nebc.nerc.ac.uk/downloads/courses/Bio-Linux/bl8_latest.pdf

https://combine-lab.github.io/salmon/

http://oncinfo.org/Bioinformatics+for+biologist+workshop

Bioinformatics for biologists Dr. Habil Zare, PhD PI of Oncinfo Lab Assistant Professor, Department...

Documents

Transcript of Bioinformatics for biologists Dr. Habil Zare, PhD PI of Oncinfo Lab Assistant Professor, Department...