Bioinformatics training: transcriptomics

Protocol

We will follow the protocol described in Tophat2 bioinformatic protocol published in Nature protocol, 2012 for this course.

For simulated dataset:

• Tophat2 —> cufflinks —> cuffmerge —> cuffdiff —> cummeRbund
• Tophat2 —> cuffdiff —> cummeRbund
• Tophat2 —> featureCounts —> DESeq2/edgeR

For real life dataset

(Just because HISAT2 is new and much faster than Tophat2):

• HISAT2 —> StringTie —> Ballgown (There is an option to follow something similiar to cuffmerge as well)
• HISAT2 —> cufflinks pipeline (with or without cuffmerge) —> cummeRbund
• HISAT2 —> featureCounts —> DESeq2/edgeR
• HISAT2 worklow pipeline Nature protocol publication

Day 1

• Introduction of transcriptomic analyses
• Discusssion regarding reference-based and de novo approaches
• How to use tophat v2 - based on the Nature protocol (2012) paper

• Download genome reference and create an index using bowtie2

• in /work/projects/nn9305k/home//transcriptome/ref

  $ ln ../../../../bioinf_course/transcriptomics/ref/Dm.BDGP6.dna.toplevel.fa .
  $ ls ../../../../bioinf_course/transcriptomics/ref/Dm.BDGP6.91.gtf .
  $ bowtie2-build Dm.BDGP6.dna.toplevel.fa Dm_BDGP6_genome
  

• USAGE

  $ bowtie2-build <Reference_fasta_file_name> <bowtie2-build_ref_index_name_that_you_will_use_later>
  

To do

• Align the given reads to the Drosophila genome using tophat v2
• create a new folder called tophat in /work/projects/nn9305k/home//transcriptome/
• create a slurm script with time=12:00:00, ntasks=16 and mem-per-cpu=12Gb

  $ tophat -p 16 -G ../ref/Dm.BDGP6.91.gtf -o <tophat_output_folder_name> ../ref/Dm_BDGP6_genome <read1> <read2>
  

Day 2

• Discuss results from tophat v2 alignemnt
• Read about cufflinks and differential expression analysis pipeline

To do

• Run cufflinks on the tophat output
• Within tophat folder create a slurm script with time=12:00:00, ntasks=16 and mem-per-cpu=12Gb

  $ cufflinks -p 16 -o <cufflinks_output_folder_name> <tophat_output_folder_name>/accepted_hits.bam
  

Day 3

• Discuss about (long) using tophat -> cufflinks -> cuffmerge -> cuffdiff pipeline (To find novel transcripts and genes)
• Discuss about (short) using tophat -> cuffdiff pipeline (To calculate differential expression for only known genes and transcripts)

To do

• Run cuffmerge and cuffdiff on Day 2’s cufflinks output
• create a text file and call it assemblies.txt and it should contain the information below

$ cat assemblies.txt
<cufflinks_output_folder_name_for_Con1_Rep1>/transcripts.gtf
<cufflinks_output_folder_name_for_Con1_Rep2>/transcripts.gtf
<cufflinks_output_folder_name_for_Con1_Rep3>/transcripts.gtf
<cufflinks_output_folder_name_for_Con2_Rep1>/transcripts.gtf
<cufflinks_output_folder_name_for_Con2_Rep2>/transcripts.gtf
<cufflinks_output_folder_name_for_Con2_Rep3>/transcripts.gtf

• Within tophat folder create a slurm script with time=12:00:00, ntasks=8 and mem-per-cpu=12Gb

  $ cuffmerge -o <cuffmerge_output_folder_name> -g ../ref/Dm.BDGP6.91.gtf -s ../ref/Dm.BDGP6.dna.toplevel.fa -p 8 assemblies.txt
  

• For the long pipeline, create a slurm script

  cuffdiff -o cuffdiff_long_output -p 16 -L Con1_l,Con2_l <cuffmerge_output_folder_name>/merged.gtf Con1_Rep1_tophat/accepted_hits.bam,Con1_Rep2_tophat/accepted_hits.bam,Con1_Rep3_tophat/accepted_hits.bam Con2_Rep1_tophat/accepted_hits.bam,Con2_Rep2_tophat/accepted_hits.bam,Con2_Rep3_tophat/accepted_hits.bam
  

• For the short pipeline, create a slurm script

  cuffdiff -o cuffdiff_short_output -p 16 -L Con1_s,Con2_s ../ref/Dm.BDGP6.91.gtf Con1_Rep1_tophat/accepted_hits.bam,Con1_Rep2_tophat/accepted_hits.bam,Con1_Rep3_tophat/accepted_hits.bam Con2_Rep1_tophat/accepted_hits.bam,Con2_Rep2_tophat/accepted_hits.bam,Con2_Rep3_tophat/accepted_hits.bam
  

• Check the above two scripts and identify the difference

Day 4

• Load cuffdiff output from short and long pipeline in R using cummeRbund

To do

• Link to cummeRbund manual: Manual

Day 5

• Introduction to counting reads

To do

• Link to featureCounts manual: Manual

Day 6-7

• DESeq2 and cummeRbund

To do

• Link to DESeq2 webpage: Link
• Link to DESeq2 manual: Link
• Link to cummeRbund webpage: Link

• Link to cummeRbund manual: Link

• Link to DESeq2 Rscript: DESeq2.R

• Link to cummeRbund Rscript: cummeRbund.R

• Link to video on FPKM, RPKM and TPM): Youtube video
• Link to video on DESeq2 Normalisation: Youtube video

Day 8

• Gene set enrichment analysis
• Gene Ontology

• Pathway analyses - KEGG

• Gorilla
• g:Profiler
• Amigo
• DAVID
• PANTHER

Also, one can get the ortholog information from ENSEMBL

Day 9

• De novo assembly using Trinity
• Link to slide: presentation slides
• Trinity website: Github wiki
• Trinity worklow pipeline: Nature protocol publication