RNA-seq analysis in de novo

An integrated worklow for de novo analysis and DE gene assessment to conduct RNA-seq data analyses

This Workflow is developped in Louis Bernatchez' lab.

WARNING

The software is provided "as is", without warranty of any kind, express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose and noninfringement. In no event shall the authors or copyright holders be liable for any claim, damages or other liability, whether in an action of contract, tort or otherwise, arising from, out of or in connection with the software or the use or other dealings in the software.

Downloading

You can clone this repository with:

git clone https://github.com/jleluyer/rna-seq_denovo_workflow

Documentation

1. Clone git hub directory

git clone https://github.com/jleluyer/rna-seq_denovo_workflow

2. Prepare utilities

cd rna-seq_denovo_workflow

./00_scripts/00_import_trinity.sh

This script will create the utilities directories that have to be configured and installed

cd 00_scripts/trinity_utils/
make
make plugins
cd ../..

cd 00_scripts/transdecoder_utils/
make
cd ../..

For Corset, small changes need to be done to correctly confgure and install the software. Change userNAME for your username.

cd 00-scripts/corset_utils
./configure --with-bam_inc=/prg/samtools/0.1.19/ --with-bam_lib=/prg/samtools/0.1.19/ --prefix=/home/userNAME/local
make
make install
cd ../..

Make sure Bowtie is in your $PATH.

3. Import data

cp /path/to/the/data/repository/*.gz 02_data

4. Trimming the data

• Import univec.fasta

wget 01_info_files/univec.fasta ftp://ftp.ncbi.nlm.nih.gov/pub/UniVec/UniVec

Add your specific adaptors if absent in the database.

• Trimming

Two scripts are provided for Single-End or Paired-end data, 00_scripts/01_trimmomatic_se.sh and 00_scripts/01_trimmomatic_pe.sh, respectively.

sbatch 00_scripts/01_trimmomatic_se.sh

You may also want to check the quality of your data prior to trimming using 00_scripts/utility_scripts/fastq.sh. This will require to have fastQC installed in your $PATH.

4. Merging data for assembly

Note: Trinity is memory-consuming, make sure you adapt the number of samples to the memory available. When limited in memory, you could use a in silico normalization provided in the 00_scripts/utility_scripts/insilico_normalization.sh. Otherwise, you may want to select a subset of the data and modify ./00_scripts/02_merge.sh. For more information regarding memory usage, please visit Trinity memory usage

sbatch 00_scripts/02_merge.sh

5. Assembly

Before running assembly, you need to make sure that the folder 05_trinity_assembly is empty. You also need to adapt the script for your own needs. For instance, you will need to adapt the input files (either SE, PE or strand-specific) in the global variables section. Other parameters need also to be carefuly chosen (e.g: minimum length of transcripts, ...).

sbatch 00_scripts/03_assemble.sh

6. Check assembly quality

sbatch 00_scripts/04_assembly_stats.sh

This script will output file 06_assembly_stats/results_stats.txt

Other scripts are provided to assess the quality of the transcriptome: 00_scripts/utility_scripts/assessing_read_content.sh

7. Downstream analysis

7.1 Transcript abundance

• Prepare reference

sbatch 00_scripts/05_prep_ref.sh

• Quantify transcripts abundance

sbatch 00_scripts/06_transcripts_abundance.sh

Several options are possible ase well as severel tools for quantifying trasncripts aboundance such as RSEM, Kallisto, eXpress or salmon as well as different aligners Bowtie or Bowtie2

• Cluster transcripts

sbatch 00_scripts/utilities/corset.sh

7.2 Annotation

• Predict longest ORFs

sbatch 00_scripts/utility_scripts/transdecoder_getorfs.sh

• Blast against Uniprot

sbatch 00_scripts/utility_scripts/blastp.sh

note: you will need access to uniprot_sprot.fasta database

• Identify protein families

sbatch 00_scripts/utility_scripts/pfam.sh

note: you will need access to Pfam-A database

• Identify signal peptides

sbatch 00_scripts/utility_scripts/signalip.sh

need to install signalip

• Identify transmembrane regions

sbatch 00_scripts/utility_scripts/tmhmm.sh

need to install tmhmm

• Identify rRNA transcripts

sbatch 00_scripts/utility_scripts/rnammer.sh

need to install rnammer

• Compile the annotation in a final report

sbatch 00_scripts/utility_scripts/trianotate.sh

note: you will need access to Trinotate.sqlite database

7.3 Differential expression analysis

• Build transcripts expression matrices

sbatch 00_scripts/07_matrix.sh

• running DE

sbatch 00_scripts/08_de_analysis.sh

Several packages are available and implemented in the script such as DeSeq2, Lima/voom, EdgeR and ROTS.

Notes

Dependencies

Softwares

Trinity

Trinotate

RSEM

Bowtie

java 1.7 or higher

R

R packages

edgeR

DESeq2

limma/voom

ROTS

goseq

Install R packages

%R
source("http://bioconductor.org/biocLite.R")
biocLite('edgeR')
biocLite('limma')
biocLite('DESeq2')
biocLite('ctc')
biocLite('Biobase')
bioclite("goseq")
install.packages('gplots')
install.packages('ape')

Citations

Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, Adiconis X, Fan L, Raychowdhury R, Zeng Q, Chen Z, Mauceli E, Hacohen N, Gnirke A, Rhind N, di Palma F, Birren BW, Nusbaum C, Lindblad-Toh K, Friedman N, Regev A. (2011). Full-length transcriptome assembly from RNA-seq data without a reference genome. Nat. Biotechnol. doi: 10.1038/nbt.1883

Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, Couger MB, Eccles D, Li B, Lieber M, Macmanes MD, Ott M, Orvis J, Pochet N, Strozzi F, Weeks N, Westerman R, William T, Dewey CN, Henschel R, Leduc RD, Friedman N, Regev A. (2013). De novo transcript sequence reconstruction from RNA-Seq: reference generation and analysis with Trinity. Nat. Protoc. doi: 10.1038/nprot.2013.084

Trinity documentation

Licence

The rna-seq_denovo_workflow is licensed under the GPL3 license. See the LICENCE file for more details.