{"id":3589,"date":"2022-02-07T09:30:15","date_gmt":"2022-02-07T08:30:15","guid":{"rendered":"https:\/\/bioinfo.ird.fr\/?page_id=3589"},"modified":"2022-04-06T14:50:45","modified_gmt":"2022-04-06T12:50:45","slug":"rnaseq1","status":"publish","type":"page","link":"https:\/\/bioinfo.ird.fr\/index.php\/tutorials-fr\/rnaseq1\/","title":{"rendered":"Tutorials &#8211; RNASeq practice : from fastq to read count"},"content":{"rendered":"<h2>RNASeq Practice<\/h2>\n<table>\n<thead>\n<tr>\n<th style=\"text-align: left;\">Description<\/th>\n<th style=\"text-align: left;\">Hands On Lab Exercises for RNASeq<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"text-align: left;\">Related-course materials<\/td>\n<td style=\"text-align: left;\"><a href=\"https:\/\/southgreenplatform.github.io\/trainings\/linux\/\">Linux for Dummies<\/a><\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: left;\">Authors<\/td>\n<td style=\"text-align: left;\">Julie Orjuela (julie.orjuela_AT_irf.fr), Pierre Larmande (pierre.larmande_AT_ird.fr), Christine Tranchant (christine.tranchant_AT_ird.fr)<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: left;\">Creation Date<\/td>\n<td style=\"text-align: left;\">04\/02\/2022<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: left;\">Last Modified Date<\/td>\n<td style=\"text-align: left;\">14\/03\/2022<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<hr \/>\n<h3>Summary<\/h3>\n<p><!-- TOC depthFrom:2 depthTo:2 withLinks:1 updateOnSave:1 orderedList:0 --><\/p>\n<p><a href=\"#preambule-1\">Preambule: Dataset used during this pratice<\/a><\/p>\n<p><a href=\"#practice-1\">Practice 1: Connect on the cluster and prepare your working environment - <code>ssh,srun,scp<\/code><\/a><br \/>\n<a href=\"#practice-2\">Practice 2: Check Reads Quality - <code>fastqc<\/code>,<code>multiqc<\/code><\/a><br \/>\n<a href=\"#practice-3\">Practice 3: fastq cleaning - <code>cutadapt<\/code><\/a><br \/>\n<a href=\"#practice-4\">Practice 4: Using the workflow manager <code>TOGGLe<\/code> to execute cutadapt and fastqc on a large number of samples<\/a><br \/>\n<a href=\"#practice-5\">Practice 5: Running Hisat2 and Stringtie with <code>TOGGLe<\/code><\/a><\/p>\n<p><a href=\"#tip\">TIP<\/a><\/p>\n<ul>\n<li><a href=\"#tip-1\">TIP 1: renaming fastq files - <code>bash<\/code><\/a><\/li>\n<li><a href=\"#tip-2\">TIP 2:  scripts &quot;slurm&quot; <\/a><\/li>\n<li><a href=\"#tip-3\">TIP 3:  How to choose a node to execute my analysis <\/a><\/li>\n<\/ul>\n<p><a href=\"#links\">Links<\/a><br \/>\n<a href=\"#license\">License<\/a><\/p>\n<hr \/>\n<p><a name=\"preambule-1\"><\/a><\/p>\n<h2>Preambule. Dataset used during this pratice<\/h2>\n<h3>Datasets used in this practical<\/h3>\n<p>Origin :<\/p>\n<ul>\n<li>ref : <a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC3488244\/\">https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC3488244\/<\/a><\/li>\n<li>data : NCBI SRA database under accession number SRS307298 <em>S. cerevisiae<\/em>.<\/li>\n<li>Genome size of  <em>S. cerevisiae<\/em> : 12M (12.157.105) (<a href=\"https:\/\/www.yeastgenome.org\/strain\/S288C#genome_sequence\">https:\/\/www.yeastgenome.org\/strain\/S288C#genome_sequence<\/a>)<\/li>\n<\/ul>\n<p>In this session, we will analyze RNA-seq data from one sample of <em>S. cerevisiae<\/em> (NCBI SRA SRS307298). It is from two different origin (CENPK and Batch), with three biological replications for each origin (rep1, rep2 and rep3).<\/p>\n<h3>Where is this dataset on the cluster ?<\/h3>\n<p>Dataset were downloaded on the i-trop cluster here : <strong>\/data2\/formation\/TP_read2count\/RAW_DATA<\/strong> (server nas)<\/p>\n<details>\n<p>```<br \/>\nRAW_DATA\/<br \/>\n\u251c\u2500\u2500 adapt-125pbLib.txt<br \/>\n\u251c\u2500\u2500 FASTQ<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 SRR453566_1.fastq.gz<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 SRR453566_2.fastq.gz<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 SRR453567_1.fastq.gz<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 SRR453567_2.fastq.gz<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 SRR453568_1.fastq.gz<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 SRR453568_2.fastq.gz<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 SRR453569_1.fastq.gz<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 SRR453569_2.fastq.gz<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 SRR453570_1.fastq.gz<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 SRR453570_2.fastq.gz<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 SRR453571_1.fastq.gz<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 SRR453571_2.fastq.gz<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 SRR453578_1.fastq.gz<br \/>\n\u2502\u00a0\u00a0 \u2514\u2500\u2500 SRR453578_2.fastq.gz<br \/>\n\u251c\u2500\u2500 REF<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 GCF_000146045.2_R64_cds_from_genomic.fna<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 GCF_000146045.2_R64_cds_from_genomic.fna.gz<br \/>\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 GCF_000146045.2_R64_genomic.fna<br \/>\n\u2502\u00a0\u00a0 \u2514\u2500\u2500 GCF_000146045.2_R64_genomic.gtf<br \/>\n\u2514\u2500\u2500 samples.txt<\/p>\n<p>2 directories, 20 files<br \/>\n```<br \/>\n<\/details>\n<p><a name=\"practice-1\"><\/a><\/p>\n<h2>Practice 1.  Connect on the cluster and prepare your working environment - <code>ssh,srun,scp<\/code><\/h2>\n<h3>Connection on the cluster through <code>ssh<\/code> mode<\/h3>\n<p>We will work on the i-trop cluster using SLURM scheduler.<\/p>\n<pre><code>ssh login@bioinfo-master.ird.fr<\/code><\/pre>\n<h3>Opening an interactive bash session on a node via slurm <code>srun -p partition --pty bash -i<\/code><\/h3>\n<p>Read this survival document containig basic commands to SLURM (<a href=\"https:\/\/southgreenplatform.github.io\/trainings\/slurm\/\">https:\/\/southgreenplatform.github.io\/trainings\/slurm\/<\/a>)<\/p>\n<pre><code>srun  --pty bash -i<\/code><\/pre>\n<h3>Prepare your input files<\/h3>\n<h4>Create your working directory in the scratch partition (\/scratch).<\/h4>\n<p>Please replace LOGIN with your own user login.<\/p>\n<pre><code>cd \/scratch\nmkdir LOGIN\ncd LOGIN<\/code><\/pre>\n<h4>Copy fastq files from the nas into your scratch directory.<\/h4>\n<pre><code>scp -r nas:$PATHTODATA\/RAWDATA\/* \/scratch\/LOGIN\/<\/code><\/pre>\n<p>Check that the files have been correctly copied with the command <code>ls -alR<\/code> ou <code>tree<\/code>. You should see 14 gzipped fastq files, a <code>samples.txt<\/code> file and a <code>adapt-125pbLib.txt<\/code> file. <\/p>\n<pre><code>[orjuela@node25 RAWDATA]$ more samples.txt\nCENPK   CENPK_rep1  PATH\/SRR453569_1.fastq.gz   PATH\/SRR453569_2.fastq.gz\nCENPK   CENPK_rep2  PATH\/SRR453570_1.fastq.gz   PATH\/SRR453570_2.fastq.gz\nCENPK   CENPK_rep3  PATH\/SRR453571_1.fastq.gz   PATH\/SRR453571_2.fastq.gz\nBatch   Batch_rep1  PATH\/SRR453566_1.fastq.gz   PATH\/SRR453566_2.fastq.gz\nBatch   Batch_rep2  PATH\/SRR453567_1.fastq.gz   PATH\/SRR453567_2.fastq.gz\nBatch   Batch_rep3  PATH\/SRR453568_1.fastq.gz   PATH\/SRR453568_2.fastq.gz<\/code><\/pre>\n<h4>Check the size of fastq directory<\/h4>\n<pre><code>du -sh FASTQ_PATH<\/code><\/pre>\n<hr \/>\n<p><a name=\"practice-2\"><\/a><\/p>\n<h2>Practice 2. Check Reads Quality<\/h2>\n<p>FastQC performs some simple quality control checks to ensure that the raw data looks good and there are no problems or biases in data which may affect how user can usefully use it. <a href=\"http:\/\/www.bioinformatics.babraham.ac.uk\/projects\/fastqc\/\">http:\/\/www.bioinformatics.babraham.ac.uk\/projects\/fastqc\/<\/a><\/p>\n<h3>Create the repertory <code>FASTQC<\/code> in your scratch directory<\/h3>\n<pre><code>mkdir FASTQC\ncd FASTQC<\/code><\/pre>\n<h3>Load FastQC software (last version)<\/h3>\n<pre><code>module load bioinfo\/FastQC\/0.11.9<\/code><\/pre>\n<h3>Run fastqc in the whole of samples (it will take 10min)<\/h3>\n<pre><code>fastqc \/scratch\/tranchant-802\/fastq\/* -o \/scratch\/tranchant-802\/FASTQC\/<\/code><\/pre>\n<h3>Run MultiQC<\/h3>\n<p>Multiqc is a modular tool to aggregate results from bioinformatics analyses across many samples into a single report. Use this tool to visualise all the results of fastqc . <a href=\"https:\/\/multiqc.info\/\">https:\/\/multiqc.info\/<\/a><\/p>\n<pre><code>#charge module\nmodule load bioinfo\/multiqc\/1.9\n\n#launch Multiqc to create a html report centralizing informations generated by fastqc per fastq file\nmultiqc \/scratch\/LOGIN\/FASTQC<\/code><\/pre>\n<h3>Transfer fastqc and multiqc files<\/h3>\n<p>now, transfert results from : node -&gt; nas -&gt; computer<\/p>\n<ul>\n<li>Transfert from \/scratch to NAS<\/li>\n<\/ul>\n<pre><code>scp -r FASTQC nas:\/home\/LOGIN\/<\/code><\/pre>\n<ul>\n<li>Transfert from NAS to your computer using  <code>scp<\/code> or <code>filezilla<\/code><\/li>\n<\/ul>\n<pre><code>scp -r LOGIN@bioinfo-nas.ird.fr:\/home\/LOGIN\/FASTQC .<\/code><\/pre>\n<h3>Open the multiqc report <code>multiqc_report.html<\/code> on your favorite web navigator<\/h3>\n<h3>Remove data in scratch directory<\/h3>\n<pre><code>rm -rf \/scratch\/LOGIN\/FASTQC\/<\/code><\/pre>\n<h3>Your turn !<\/h3>\n<ul>\n<li>Launch th same analysis through a slurm script !<\/li>\n<\/ul>\n<hr \/>\n<p><a name=\"practice-3\"><\/a><\/p>\n<h1>Practice 3. fastq cleaning<\/h1>\n<p><a name=\"cutadapt\"><\/a><\/p>\n<h4>Using <code>cutadapt<\/code> to remove adapters and to trim reads based on quality<\/h4>\n<ul>\n<li><a href=\"https:\/\/code.google.com\/p\/cutadapt\/\">cutadapt website<\/a><\/li>\n<\/ul>\n<pre><code>cutadapt  -q 30,30 -m 35  -B GATCGGAAGAGCACACGTCTGAACTCCAGTCACATCACGATCTCGTATGCCGTCTTCTGCTTG -B GTTCGTCTTCTGCCGTATGCTCTAGCACTACACTGACCTCAAGTCTGCACACGAGAAGGCTAG -b GATCGGAAGAGCACACGTCTGAACTCCAGTCACATCACGATCTCGTATGCCGTCTTCTGCTTG -b GTTCGTCTTCTGCCGTATGCTCTAGCACTACACTGACCTCAAGTCTGCACACGAGAAGGCTAG-o P1_R1.CUTADAPT.fastq.gz -p P1_R2.CUTADAPT.fastq.gz P1_R1.fq.gz P1_R2.fq.gz<\/code><\/pre>\n<ul>\n<li><code>Cutadapt<\/code> supports trimming of multiple types of adapters:<\/li>\n<\/ul>\n<table>\n<thead>\n<tr>\n<th style=\"text-align: left;\">Adapter type<\/th>\n<th style=\"text-align: left;\">Command-line option<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td style=\"text-align: left;\">3\u2019 adapter<\/td>\n<td style=\"text-align: left;\">-a ADAPTER<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: left;\">5\u2019 adapter<\/td>\n<td style=\"text-align: left;\">-g ADAPTER<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: left;\">5\u2019 or 3\u2019 (both possible)<\/td>\n<td style=\"text-align: left;\">-b ADAPTER<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>-q 30, 30 : by default, only the 3\u2019 end of each read is quality-trimmed. If you want to trim the 5\u2019 end as well, use the -q option with two comma-separated cutoffs<\/p>\n<p>-p is the short form of --paired-output. The option -B is used here to specify an adapter sequence that cutadapt should remove from the second read in each pair.<\/p>\n<hr \/>\n<p><a name=\"practice-4\"><\/a><\/p>\n<h1>Practice 4 : Using the workflow manager <code>TOGGLe<\/code> to execute cutadapt and fastqc on a large number of samples<\/h1>\n<h3>Data used for this pratice<\/h3>\n<p>Input data for this TP are accessible in the directory <code> \/data2\/formation\/TP_read2count\/<\/code>.<\/p>\n<ul>\n<li>fastq files :  <code>RAW_DATA\/FASTQ_RENAMED<\/code><\/li>\n<li>configuration file used by TOGGLe : <code>scripts\/TOGGLE_CONFIG\/cleaning.config.txt<\/code><\/li>\n<li>slurm script used to launch our analysis worflow withTOGGLe : <code>scripts\/runTOGGLe_cleaning.sh<\/code><\/li>\n<\/ul>\n<pre><code>PATHTODATA=&quot;nas:\/data2\/formation\/TP_read2count\/&quot;\n* Input data : $PATHTODATA\/RAW_DATA\/FASTQ_RENAMED\n* Config file: $PATHTODATA\/scripts\/TOGGLE_CONFIG\/cleaning.config.txt\n* Script : $PATHTODATA\/scripts\/runTOGGLe_cleaning.sh<\/code><\/pre>\n<p>Nb : You can also download a predefined TOGGLe configuration file such as  <a href=\"https:\/\/raw.githubusercontent.com\/SouthGreenPlatform\/TOGGLE\/master\/exampleConfigs\/fastqCheckQuality.config.txt\">fastqCheckQuality.config.txt<\/a> and modify it.<\/p>\n<h3>Prepare your working environment<\/h3>\n<h5>Opening an interactive bash session on a node via slurm<\/h5>\n<p><code><code>srun -p partition --pty bash -i<\/code><\/code><\/p>\n<h5>Create your working directory in the scratch partition (\/scratch).<\/h5>\n<pre><code># Create a new directory in your \/scratch\nmkdir \/scratch\/$USER-TOGGLe\ncd \/scratch\/$USER-TOGGLe\/\nmkdir cleaning\ncd  cleaning<\/code><\/pre>\n<h4>Import fastq from $PATHTODATA to your \/scratch repertory and configure TOGGLe to cleaning analysis<\/h4>\n<pre><code># declare where data is\nPATHTODATA=&quot;nas:\/data2\/formation\/TP_read2count\/&quot;\n\n# Transfert reads to cleaning to \/scratch\nscp -r $PATHTODATA\/RAW_DATA\/FASTQ_RENAMED .<\/code><\/pre>\n<h4>Import TOGGLE configuration file into your \/scratch directory<\/h4>\n<h6>Copy the configuration file used by TOGGLe into the  directory cleaning and display the content of this file<\/h6>\n<pre><code>scp $PATHTODATA\/scripts\/TOGGLE_CONFIG\/cleaning.config.txt .<\/code><\/pre>\n<pre><code>[orjuela@nodeXX cleaning]$ more cleaning.config.txt \n$order\n1=cutadapt\n2=fastqc\n\n$fastqc\n\n$cutadapt\n-q 30,30\n-m 35\n-u 9 \n-B GATCGGAAGAGCACACGTCTGAACTCCAGTCACGGCTACATCTCGTATGC\n-B ATCGGAAGAGCACACGTCTGAACTCCAGTCACGGCTACATCTCGTATGCC\n-B GTCCATTATATGTCTCCCAAACCACCAAACTCTTTGACTCCGGTGTGTTG\n-B GATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGTGGTCGCCG\n-b GATCGGAAGAGCACACGTCTGAACTCCAGTCACGGCTACATCTCGTATGC\n-b ATCGGAAGAGCACACGTCTGAACTCCAGTCACGGCTACATCTCGTATGCC\n-b GTCCATTATATGTCTCCCAAACCACCAAACTCTTTGACTCCGGTGTGTTG\n-b GATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGTGGTCGCCG\n\n# PUT YOUR OWN SLURM CONFIGURATION HERE IF AVAILABLE RESSOURCES\n$slurm\n-p PARTITION\n--nodelist=nodeXXX\n\n# If your data are already in scratch don&#039;t activate this option\n#$scp\n#\/scratch\/\n\n$env\nmodule load bioinfo\/TOGGLE-dev\/0.3.7<\/code><\/pre>\n<h6>Modify this configuration file<\/h6>\n<p>Using a text editor such nano, modify the  configuration file  <code>cleaning.config.txt<\/code> and check the whole of parameters.<\/p>\n<ul>\n<li>\n<p>Adapt the parameters of <code>Cutadapt<\/code>  and <code>FastQC<\/code> if necessary<\/p>\n<\/li>\n<li>\n<p>Change the slurm configuration (key <code>$slurm<\/code>) by adding the correct partition and node names :<\/p>\n<ul>\n<li>-p PARTITION. Partition can be short, normal, highmem etc... <\/li>\n<li>--nodelist=nodeX (node used by slurm)<\/li>\n<\/ul>\n<\/li>\n<li>\n<p>if your fastq files are in a project space,  use\/activate the  <code>$scp<\/code> key , TOGGLe will transfer data from your project space into the scratch directory of the node used by slurm.<\/p>\n<\/li>\n<\/ul>\n<p>Nb : If your data are already in \/scratch, deactivate this option and activate <code>$env<\/code> key giving <code>module load bioinfo\/TOGGLE-dev\/0.3.7<\/code>.<\/p>\n<h4>Create a slurm script to launch TOGGLe<\/h4>\n<p>This script is also available in the <code>\/data2\/formation\/TP_read2count\/scripts\/runTOGGLe_cleaning.sh<\/code><\/p>\n<pre><code>#!\/bin\/bash -l\n#SBATCH -J TOGGLeCleaning\n#SBATCH --export=ALL\n#SBATCH -e toggle.&quot;%j&quot;.err\n#SBATCH -o toggle.&quot;%j&quot;.out\n#SBATCH -p PARTITION\n#SBATCH --nodelist=nodeXX \n\n# Defining scratch and destination repertories\n\nREP=&quot;\/scratch\/$USER-TOGGLe\/cleaning&quot;\ndir=&quot;$REP\/FASTQ_RENAMED&quot;\nout=&quot;$REP\/OUTPUT_TOGGLE-CLEANING&quot;\nconfig=&quot;$REP\/cleaning.config.txt&quot;\n\n# Software-specific settings exported to user environment\nmodule load bioinfo\/TOGGLE-dev\/0.3.7\n\n# running tooglegenerator \ntoggleGenerator.pl -d $dir -c $config -o $out --nocheck;\n\necho &quot;FIN de TOGGLe for cleaning ^^&quot;\n<\/code><\/pre>\n<ul>\n<li>Convert runTOGGLe_cleaning in an executable file with <code>chmod +x runTOGGLe_cleaning.sh<\/code><\/li>\n<\/ul>\n<h3>Launch the script runTOGGLe_cleaning.sh through slurm<\/h3>\n<pre><code>sbatch .\/runTOGGLe_cleaning.sh<\/code><\/pre>\n<h3>Check your jobs are correctly running<\/h3>\n<ul>\n<li>Explore output <code>OUT<\/code> TOGGLe and check if everything was ok.<\/li>\n<li>Check if your jobs are running with : squeue -u login -i 10<\/li>\n<li>test the top command ('c' and 'u')<\/li>\n<\/ul>\n<h3>Remove your data in the scratch directory<\/h3>\n<hr \/>\n<p><a name=\"practice-5\"><\/a><\/p>\n<h1>Practice 5 : Running Hisat2 and Stringtie with TOGGLe<\/h1>\n<h3>Data used for this practice<\/h3>\n<p>Input data are available in the directory <code>\/data2\/formation\/TP_read2count<\/code> :<\/p>\n<ul>\n<li>fastq files : <code>RAW_DATA\/FASTQ_RENAMED<\/code><\/li>\n<li>Genome sequence (fasta) : <code>RAW_DATA\/REF\/GCF_000146045.2_R64_genomic.fna<\/code><\/li>\n<li>Genome annotation (gff) : <code>RAW_DATA\/REF\/GCF_000146045.2_R64_genomic.gtf<\/code><\/li>\n<li>configuration file used by TOGGLe : <code>scripts\/TOGGLE_CONFIG\/RNASeqHisat2Stringtie.config.txtt<\/code><\/li>\n<li>slurm script used to launch our analysis worflow withTOGGLe : <code>scripts\/runTOGGLeRNASEQ.sh<\/code><\/li>\n<\/ul>\n<pre><code> PATHTODATA=&quot;nas:\/data2\/formation\/TP_read2count&quot;\n* Input data : $PATHTODATA\/RAW_DATA\/FASTQ_RENAMED\n* Reference : $PATHTODATA\/RAW_DATA\/REF\/GCF_000146045.2_R64_genomic.fna\n* Annotation : $PATHTODATA\/RAW_DATA\/REF\/GCF_000146045.2_R64_genomic.gtf\n* config file : $PATHTODATA\/scripts\/TOGGLE_CONFIG\/RNASeqHisat2Stringtie.config.txt\n* Script to run TOGGLe: $PATHTODATA\/scripts\/runTOGGLeRNASEQ.sh<\/code><\/pre>\n<p>In this practive, we don't transfert data from nas into \/scratch manually !  TOGGLe is able to manage data transfert for you ! Let's try it! <\/p>\n<h3>Prepare your analysis<\/h3>\n<h5>Opening an interactive bash session on a node via slurm<\/h5>\n<pre><code>srun -p partition --pty bash -i<\/code><\/pre>\n<h5>Copy data used for this practice in your own projet directory (NAS, NAS2 or NAS3 servers).<\/h5>\n<pre><code># 1 Go to your project on NASX\nssh NASX\ncd \/dataX\/project\/MyProject\/\n\n# 2 Create a directory to work\nmkdir TEST-TOGGLe\ncd  TEST-TOGGLe\n\n# 3 Declare a variable : to change if needed\nPATHTODATA=&quot;nas:\/data2\/formation\/TP_read2count\/&quot;\n\n# 4 Transfert  READS and REF  test to NAS, NAS2 or NAS3 \nscp -r $PATHTODATA\/RAW_DATA\/FASTQ_RENAMED .\nscp -r $PATHTODATA\/RAW_DATA\/REF .\n\n# 5 Make \u00e0 copy of the configuration file used by TOGGLe adapted to RNAseq\nscp $PATHTODATA\/scripts\/TOGGLE_CONFIG\/RNASeqHisat2Stringtie.config.txt .\n\n# 6 Transfert script used to run TOGGLe\nscp $PATHTODATA\/scripts\/runTOGGLeRNASEQ.sh .<\/code><\/pre>\n<h5>Adapt the configuration file used by <code>TOGGLe<\/code><\/h5>\n<p>Using a text editor, adapt the file <code>RNASeqHisat2Stringtie.config.txt<\/code> and  check the whole of parameters. This predefined configuration file ca be obtained from  <a href=\"https:\/\/raw.githubusercontent.com\/SouthGreenPlatform\/TOGGLE\/master\/exampleConfigs\/RNASeqHisat2Stringtie.config.txt\">RNASeqReadCount.config.txt<\/a><\/p>\n<ul>\n<li>\n<p>Change SLURM key <code>$slurm<\/code> giving -p PARTITION. Partition can be short, normal, highmem etc...<\/p>\n<\/li>\n<li>\n<p>Complete the <code>$scp<\/code> key with \/scratch. TOGGLe will use this key to copy data from a nas server into a node (scratch partition) then it will run jobs using data in the scratch directory.<br \/>\nNb : If your data are already in \/scratch, comment this key<\/p>\n<\/li>\n<li>\n<p>Add, after the <code>$env<\/code> key, the line <code>module load bioinfo\/TOGGLE-dev\/0.3.7<\/code>. <\/p>\n<\/li>\n<li>\n<p>Check parameters of every step in <code>RNASeqHisat2Stringtie.config.txt<\/code> as recommended by stringtie manual recomendations <a href=\"http:\/\/ccb.jhu.edu\/software\/stringtie\/index.shtml?t=manual\">http:\/\/ccb.jhu.edu\/software\/stringtie\/index.shtml?t=manual<\/a>.<\/p>\n<\/li>\n<\/ul>\n<pre><code>$ more RNASeqHisat2Stringtie.config.txt \n$order\n1=hisat2\n2=samtoolsView\n3=samtoolsSort\n4=stringtie\n\n$hisat2\n--dta\n\n$samtoolsview\n-b\n-h\n\n$stringtie\n-e\n-B\n\n$cleaner\n1\n2\n\n$slurm\n--job-name=TOGGLe\n--partition normal\n--export=ALL\n\n$scp\n\/scratch\/\n\n$env\nmodule load bioinfo\/TOGGLE-dev\/0.3.7\n<\/code><\/pre>\n<h4>HISAT and STRINGTIE in some words :<\/h4>\n<p>Before mapping, a reference genome index is required. TOGGle creates automatically index genome if indexes are absent in reference folder.<\/p>\n<p>Mapping is performed using HISAT2 and mapped reads are assembled into transcripts with StringTie. Transcript assemblies can be done with or without a reference annotation. <\/p>\n<p>Stringtie is able to estimate the expression levels of the &quot;reference&quot; transcripts provided and generate  a matrix of read counts mapped to particular genomic features (e.g., genes). <\/p>\n<h4>Create a slurm script to launch your analysis  - <code>runTOGGLeRNASEQ.sh<\/code><\/h4>\n<p>This script is also avalaible in the data directory used for this practice. <\/p>\n<pre><code>$ more runTOGGLe_RNAseq.sh \n#!\/bin\/bash -l\n#SBATCH -J TOGGLeRNASeq\n#SBATCH --export=ALL\n#SBATCH -e toggle.&quot;%j&quot;.err\n#SBATCH -o toggle.&quot;%j&quot;.out\n#SBATCH -p PARTITION\n\n# Defining my project and destination repertories\nREP=&quot;\/dataX\/projects\/MyProject\/TEST-TOGGLe&quot;\ndir=&quot;$REP\/FASTQ_RENAMED&quot;\nout=&quot;$REP\/OUTPUT_TOGGLE-H2SSM&quot;\nconfig=&quot;$REP\/RNASeqHisat2Stringtie.config.txt&quot;\nref=&quot;$REP\/REF\/GCF_000146045.2_R64_genomic.fna&quot;\ngff=&quot;$REP\/REF\/GCF_000146045.2_R64_genomic.gtf&quot;\n\n# Software-specific settings exported to user environment\nmodule load bioinfo\/TOGGLE-dev\/0.3.7\n\n# running tooglegenerator \ntoggleGenerator.pl -d $dir -c $config -r $ref -g $gff -o $out --report --nocheck;\n\necho &quot;FIN de TOGGLe  - RNASEQ ^^&quot;<\/code><\/pre>\n<h3>Launch the TOGGLE analysis - <code>runTOGGLeRNASEQ.sh<\/code><\/h3>\n<h4>Convert runTOGGLeRNASEQ in an executable file with <code>chmod +x runTOGGLeRNASEQ.sh<\/code><\/h4>\n<pre><code>chmod +x .\/runTOGGLeRNASEQ.sh<\/code><\/pre>\n<h4>Launch runTOGGLeRNASEQ.sh in sbatch mode<\/h4>\n<pre><code>sbatch .\/runTOGGLeRNASEQ.sh<\/code><\/pre>\n<h4>Check your jobs are correctly running<\/h4>\n<ul>\n<li>Explore the output <code>OUTPUT_TOGGLE-H2SSM<\/code> and check if everything was ok.<\/li>\n<li>Check the final_results directory and observe .gtf files<\/li>\n<\/ul>\n<h3>Convert <code>GTF<\/code> file into <code>COUNTS<\/code> file<\/h3>\n<h4>create a <code>samples_gtf.txt<\/code> file<\/h4>\n<p>Go to the <code>finalResults directory<\/code> and create a <code>samples_gtf.txt<\/code> doing ...<\/p>\n<pre><code>cd \/dataX\/projects\/MyProject\/TEST-TOGGLe\/OUTPUT_TOGGLE-H2SSM\/finalResults\nls *gtf | sed &#039;s\/.STRINGTIE.gtf\/\/&#039; - &gt; names.txt\nrealpath *gtf &gt; paths.txt\npaste names.txt paths.txt &gt; samples_gtf.txt\nrm names.txt paths.txt<\/code><\/pre>\n<p><code>samples_gtf.txt<\/code> is looking now such as (no header) : <\/p>\n<pre><code>Batch-rep1  \/dataX\/projects\/MyProject\/TEST-TOGGLe\/OUTPUT_TOGGLE-H2SSM\/finalResults\/Batch-rep1.STRINGTIE.gtf\nBatch-rep2  \/dataX\/projects\/MyProject\/TEST-TOGGLe\/OUTPUT_TOGGLE-H2SSM\/finalResults\/Batch-rep2.STRINGTIE.gtf\nBatch-rep3  \/dataX\/projects\/MyProject\/TEST-TOGGLe\/OUTPUT_TOGGLE-H2SSM\/finalResults\/Batch-rep3.STRINGTIE.gtf\nCENPK-rep1  \/dataX\/projects\/MyProject\/TEST-TOGGLe\/OUTPUT_TOGGLE-H2SSM\/finalResults\/CENPK-rep1.STRINGTIE.gtf\nCENPK-rep2  \/dataX\/projects\/MyProject\/TEST-TOGGLe\/OUTPUT_TOGGLE-H2SSM\/finalResults\/CENPK-rep2.STRINGTIE.gtf\nCENPK-rep3  \/dataX\/projects\/MyProject\/TEST-TOGGLe\/OUTPUT_TOGGLE-H2SSM\/finalResults\/CENPK-rep3.STRINGTIE.gtf<\/code><\/pre>\n<h4>Convert GTF to counts<\/h4>\n<pre><code>module load system\/python\/3.7.2\npython3 \/data2\/formation\/TP_read2count\/scripts\/prepDE.py3 -i samples_gtf.txt<\/code><\/pre>\n<p><code>gene_count_matrix.csv<\/code> and <code>transcript_count_matrix.csv<\/code> has been created!!! <\/p>\n<p>You can use  DESeq2 and edgeR for analyzing differential expression in R or some shiny packages such as DIANE <a href=\"https:\/\/oceanecsn.github.io\/DIANE\/\">https:\/\/oceanecsn.github.io\/DIANE\/<\/a> or PIVOT <a href=\"https:\/\/github.com\/kimpenn\/PIVOT\">https:\/\/github.com\/kimpenn\/PIVOT<\/a><\/p>\n<hr \/>\n<p><a name=\"tip\"><\/a><\/p>\n<h3>TIP<\/h3>\n<p><a name=\"tip-1\"><\/a><\/p>\n<h1>TIP 1 : Renaming reads names<\/h1>\n<p>Several ways exist to rename files. We propose here a solution from a csv file. We will use symbolic links to avoid to change original names. We will use the naming convention defined in TOGGLe <a href=\"https:\/\/toggle.ird.fr\/manual\/quickManual\/\">https:\/\/toggle.ird.fr\/manual\/quickManual\/<\/a>!!<\/p>\n<pre><code>[orjuela@master0 FASTQ]$ pwd\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\n\n[orjuela@master0 FASTQ]$ realpath *gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453566_1.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453566_2.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453567_1.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453567_2.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453568_1.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453568_2.fastq.gz\n...\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453578_1.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453578_2.fastq.gz\n\n[orjuela@master0 FASTQ]$ realpath *gz &gt; ..\/names_tmp.txt<\/code><\/pre>\n<p>names_tmp.txt can be modified in excel for example in order to have a second column with the new name such as in a new file (named <code>file4renaming.csv<\/code> par example) :<\/p>\n<pre><code>[orjuela@master0 RAW_DATA\/]$ more file4renaming.csv\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453566_1.fastq.gz  Batch-rep1_R1.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453566_2.fastq.gz  Batch-rep1_R2.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453567_1.fastq.gz  Batch-rep2_R1.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453567_2.fastq.gz  Batch-rep2_R2.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453568_1.fastq.gz  Batch-rep3_R1.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453568_2.fastq.gz  Batch-rep3_R2.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453569_1.fastq.gz  CENPK-rep1_R1.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453569_2.fastq.gz  CENPK-rep1_R2.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453570_1.fastq.gz  CENPK-rep2_R1.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453570_2.fastq.gz  CENPK-rep2_R2.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453571_1.fastq.gz  CENPK-rep3_R1.fastq.gz\n\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453571_2.fastq.gz  CENPK-rep3_R2.fastq.gz<\/code><\/pre>\n<p>Now we will use this <code>file4renaming.csv<\/code> to create symbolic links.<\/p>\n<pre><code># go to the new FASTQ repertory\nmkdir FASTQ_RENAMED\ncd FASTQ_RENAMED\n\n# first verify command line is ok before to launch &quot;eval&quot;\nwhile read -r line; do echo &quot;ln -s $line&quot;;  done &lt; ..\/file4renaming.csv\n\n# Once all its ok,\nwhile read -r line; do ln -s $line;  done &lt; ..\/file4renaming.csv\n\nln -s \/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453566_1.fastq.gz    SRR453566_R1.fastq.gz\nln -s \/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453566_2.fastq.gz    SRR453566_R2.fastq.gz\nln -s \/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453567_1.fastq.gz    SRR453567_R1.fastq.gz\nln -s \/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453567_2.fastq.gz    SRR453567_R2.fastq.gz\nln -s \/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453568_1.fastq.gz    SRR453568_R1.fastq.gz\nln -s \/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/SRR453568_2.fastq.gz    SRR453568_R2.fastq.gz\n\n# verify links by using ls -l command<\/code><\/pre>\n<hr \/>\n<p><a name=\"tip-2\"><\/a><\/p>\n<h2>TIP 2 :  scripts<\/h2>\n<h3>Slurm script to run fastqc and cutadapt<\/h3>\n<h4>A first script with all commands used for the pratice 2 : <code>run_fastqc-multiqc.sh<\/code><\/h4>\n<ul>\n<li>The command to execute this script<\/li>\n<\/ul>\n<pre><code>sbatch \/data2\/formation\/TP_read2count\/scripts\/run_fastqc-multiqc.sh<\/code><\/pre>\n<ul>\n<li><strong>Before running this script, don't forget to update the script (ex: email adress used by slurm)<\/strong> . This script runs with the TP data but don't forget to update it if you want use it with other datasets (READS variable in the script)<\/li>\n<\/ul>\n<details>\n<p>```<br \/>\n#!\/bin\/bash<\/p>\n<p>######## CONFIGURATION SLURM ##<br \/>\n# Definir le nom du job<br \/>\n#SBATCH--job-name=FastQC<\/p>\n<p># on definit la partition o\u00f9 lancer la commande et le noeud<br \/>\n#SBATCH -p normal<br \/>\n####SBATCH -w nodeX<\/p>\n<p># On choisit le nombre de coeur<br \/>\n#SBATCH -c 2<\/p>\n<p># Definir notre adresse mail<br \/>\n#SBATCH --mail-user=PUT_YOUR_EMAIL@ird.fr<\/p>\n<p># type de mail \u00e0 recevoir<br \/>\n# BEGIN, ABORT, END ou ALL<br \/>\n#SBATCH --mail-type=ALL<br \/>\n############################################<\/p>\n<p>READS=&quot;nas:\/data2\/formation\/TP_read2count\/RAW_DATA\/FASTQ\/&quot;<\/p>\n<p># Print le noeud o\u00f9 mon job tourne<br \/>\necho &quot;###### Je suis dans ce node : $HOSTNAME&quot;<\/p>\n<p># creer un repertoire personnel dans le scratch du noeud<br \/>\ncd \/scratch<br \/>\nmkdir $USER-$SLURM_JOB_ID<br \/>\ncd $USER-$SLURM_JOB_ID<br \/>\necho &quot;###### Je suis dans ce node : $HOSTNAME&quot;<\/p>\n<p># recup\u00e9rer les donn\u00e9es depuis le nas<br \/>\necho &quot;##### on fait le scp des reads vers le node ...&quot;<br \/>\necho &quot;## scp -r $READS \/scratch\/$USER-$SLURM_JOB_ID&quot;<br \/>\nscp -r $READS \/scratch\/$USER-$SLURM_JOB_ID<\/p>\n<p>## cr\u00e9er un dossier FastQC<br \/>\nmkdir FastQC<\/p>\n<p>## charger le logiciel<br \/>\nmodule load bioinfo\/FastQC\/0.11.9<\/p>\n<p># lancer l&amp;#039;analyse<br \/>\necho &quot;#### on lance FastQ ...&quot;<br \/>\ncd FastQC<\/p>\n<p>echo &quot;## fastqc \/scratch\/$USER-$SLURM_JOB_ID\/FASTQ\/* -o \/scratch\/$USER-$SLURM_JOB_ID\/FASTQC -t 2&quot;<br \/>\nfastqc \/scratch\/$USER-$SLURM_JOB_ID\/FASTQ\/* -o \/scratch\/$USER-$SLURM_JOB_ID\/FASTQC -t 2<\/p>\n<p>#charge module multiQC<br \/>\nmodule load bioinfo\/multiqc\/1.9<\/p>\n<p>echo &quot;#### on lance multiqc ...&quot;<br \/>\nmultiqc \/scratch\/$USER-$SLURM_JOB_ID\/FastQC<\/p>\n<p># recup\u00e9ration des donn\u00e9es<br \/>\necho &amp;#039;#### je transfert les reads vers le projet ...&amp;#039;<br \/>\necho &quot;## scp -r FastQC $READS&quot;<br \/>\nscp -r \/scratch\/$USER-$SLURM_JOB_ID\/FastqQC  $READS<\/p>\n<p>#suppression des donn\u00e9es<br \/>\n#cd \/scratch<br \/>\n#rm - rf $USER-$SLURM_JOB_ID<\/p>\n<p>#stats sur le job<br \/>\nseff $SLURM_JOB_ID<br \/>\n```<br \/>\n<\/details>\n<h4>An improved  script with all commands used for the pratice 2 : <code>run_fastqc-multiqc-arg.sh<\/code><\/h4>\n<ul>\n<li>The command to excute this script<\/li>\n<\/ul>\n<pre><code>sbatch \/data2\/formation\/TP_read2count\/scripts\/run_fastqc-multiqc-arg.sh PUT_path2reads PUT_output_directory_name<\/code><\/pre>\n<details>\n<p>```<br \/>\n#!\/bin\/bash<br \/>\n#SBATCH -p normal<br \/>\n#SBATCH -J fastqc-multiqc<br \/>\n#SBATCH -c 4<\/p>\n<p>if [[ -z $1 ]]; then<br \/>\n echo &quot;ce script attends 2 arguments : pathtoreads et outputname&quot;;<br \/>\n exit;<br \/>\nfi<\/p>\n<p>if [[ -z $2 ]]; then<br \/>\n echo &quot;ce script attends outputname en 2 argument&quot;;<br \/>\n exit;<br \/>\nfi<\/p>\n<p>#chargement des modules<br \/>\n#module load bioinfo\/FastQC\/0.11.9<br \/>\nmodule load bioinfo\/FastQC\/0.11.5<br \/>\nmodule load bioinfo\/multiqc\/1.9<\/p>\n<p># ==&gt; declaration des variables<br \/>\n#on recupere le chemin du directoire ou sont les reads<br \/>\nDIRFASTQ=$(realpath $1)<br \/>\nTMP=\/scratch\/$USER-readsquality<br \/>\nREADS=$TMP\/READS<br \/>\nOUTFASTQC=$TMP\/OUTPUTFASTQC<br \/>\nOUTMQC=$TMP\/$2<br \/>\nFINAL=$(dirname $DIRFASTQ)<\/p>\n<p>#on cree un dossier de travail dans le scratch d&amp;#039;un node<br \/>\nmkdir -p $TMP<br \/>\n#on cree un dossier ou on va placer les reads<br \/>\nmkdir -p $READS<br \/>\n#on cree un dossier pour FASTQC ou on va placer les reads<br \/>\nmkdir -p $OUTFASTQC<br \/>\n#on cree un dossier pour MultiQC ou on va placer les reads<br \/>\nmkdir -p $OUTMQC<\/p>\n<p>#on transfert les reads dans le dossier tmp\/fastq<br \/>\necho &quot;=&gt; On transfert les reads du projet au \/scratch ...&quot;<br \/>\necho &quot;scp nas:$DIRFASTQ\/*gz $READS&quot;<br \/>\nscp nas:$DIRFASTQ\/*gz $READS<\/p>\n<p># fastQC<br \/>\necho &quot;Les fastq sont dans : $READS dans le node&quot;<br \/>\necho &quot;=&gt; On lance FastQC ...&quot;<br \/>\necho &quot;fastqc $READS\/* -o $OUTFASTQC -t 4&quot;<br \/>\nfastqc $READS\/* -o $OUTFASTQC -t 4<\/p>\n<p>#MultiQC<br \/>\necho &quot;=&gt; On lance MultiQC ...&quot;<br \/>\necho &quot;multiqc $OUTFASTQC --outdir $OUTMQC&quot;<br \/>\nmultiqc $OUTFASTQC --outdir $OUTMQC<\/p>\n<p># on transfert les donn\u00e9es<br \/>\necho &quot;=&gt; On retransfert les resultats sur le projet ...&quot;<br \/>\necho &quot;scp -r $OUTMQC nas:$FINAL\/&quot;<br \/>\nscp -r $OUTMQC nas:$FINAL\/<\/p>\n<p># on efface les donn\u00e9es du \/scratch<br \/>\necho &quot;=&gt; On efface les donn\u00e9es du \/scratch . bye!!!&quot;<br \/>\nrm -rf $TMP<\/p>\n<p>```<br \/>\n<\/details>\n<hr \/>\n<p><a name=\"tip-3\"><\/a><\/p>\n<h3>TIP 3:  How to choose a node to execute my analysis ]<\/h3>\n<hr \/>\n<h3>Links<\/h3>\n<p><a name=\"links\"><\/a><\/p>\n<p>slides <a href=\"https:\/\/southgreenplatform.github.io\/trainings\/\/files\/RNAseq_ouaga_2019_10102019-short.pdf\">https:\/\/southgreenplatform.github.io\/trainings\/\/files\/RNAseq_ouaga_2019_10102019-short.pdf<\/a><\/p>\n<p>Practice\u00a0: <a href=\"https:\/\/bioinfo.ird.fr\/index.php\/tutorials-fr\/rnaseq1\/\">https:\/\/bioinfo.ird.fr\/index.php\/tutorials-fr\/rnaseq1\/<\/a><\/p>\n<hr \/>\n<h3>License<\/h3>\n<p><a name=\"license\"><\/a><\/p>\n<div>\n","protected":false},"excerpt":{"rendered":"<p>RNASeq Practice Description Hands On Lab Exercises for RNASeq Related-course materials Linux for Dummies Authors Julie Orjuela (julie.orjuela_AT_irf.fr), Pierre Larmande&hellip; 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