README.md

# rnaseq v1.1

**Rnaseq** workflow , which agree to FAIR principles , was built in Nexflow dsl2 language, with singularity container for used softwares, optimized in terms of computing resources (cpu, memory), and its use on a informatic farm with a slurm scheduler.

## Install rnaseq flow and build singularity image

Clone rnaseq git and build local singularity image (with system admin rights) based on the provided singularity definition file.

```bash
git clone https://forgemia.inra.fr/lpgp/rnaseq.git
sudo singularity build ./rnaseq/singularity/rnaseq.sif ./rnaseq/singularity/rnaseq.def
```

## Usage examples

### bulk RNAseq paired end reads using STAR and HTSEQ-count

```bash
#!/bin/bash
#SBATCH -J rnaseq
#SBATCH --mem 10GB
module load containers/singularity/3.9.9
module load bioinfo/Nextflow/21.10.6
nextflow run /work/project/lpgp/Nextflow/rnaseq/ \
-profile slurm \
--input "${PWD}/raw/*_{1,2}.fastq.gz" \
--genome "${PWD}/genome.fa.gz" \
--gff_gtf "${PWD}/annot.gtf.gz" \
--method "star_htseq-count" \
--sjdbOverhang 80 \
--clip_r1 12 \
--three_prime_clip_r1 2 \
--clip_r2 12 \
--three_prime_clip_r2 2 \
--out_dir "${PWD}/results"
```

### bulk RNAseq from single end reads using Salmon in SAF mode

```bash
#!/bin/bash
#SBATCH -J rnaseq
#SBATCH --mem 10GB
module load containers/singularity/3.9.9
module load bioinfo/Nextflow/21.10.6
nextflow run /work/project/lpgp/Nextflow/rnaseq/ \
-profile slurm \
--input "${PWD}/raw/*.fastq.gz" \
--genome "${PWD}/genome.fa.gz" \
--transcriptome "${PWD}/transcriptome.fa.gz" \
--method "salmon_saf" \
--clip_r1 12 \
--three_prime_clip_r1 2 \
--out_dir "${PWD}/results"
```

### bulk RNAseq from paired end reads using Salmon in SAF mode

```bash
#!/bin/bash
#SBATCH -J rnaseq
#SBATCH --mem 10GB
module load containers/singularity/3.9.9
module load bioinfo/Nextflow/21.10.6
nextflow run /work/project/lpgp/Nextflow/rnaseq/ \
-profile slurm \
--input "${PWD}/raw/*_{1,2}.fastq.gz" \
--method "salmon_saf" \
--genome "${PWD}/genome.fa.gz" \
--transcriptome "${PWD}/transcriptome.fa.gz" \
--clip_r1 12 \
--three_prime_clip_r1 2 \
--clip_r2 12 \
--three_prime_clip_r2 2 \
--out_dir "${PWD}/results"
```

## bulk RNAseq from brb chemistry using STARsolo

```bash
#!/bin/bash
#SBATCH -J rnaseq
#SBATCH --mem 10GB
module load containers/singularity/3.9.9
module load bioinfo/Nextflow/21.10.6
nextflow run /work/project/lpgp/Nextflow/rnaseq/ \
-profile slurm \
--input "${PWD}/raw/*_{1,2}.fastq.gz" \
--genome "${PWD}/genome.fa.gz" \
--gff_gtf "${PWD}/annot.gtf.gz" \
--method "star_solo" \
--sjdbOverhang 99 \
--whitelist "${PWD}/whitelist.txt" \
--soloCBstart  1 \
--soloCBlen 12 \
--soloUMIstart 13 \
--soloUMIlen 16 \
--out_dir "${PWD}/results"
```


## Single cell RNAseq from chromium (v3) chemistry using STARsolo

```bash
# get The 10X Chromium V3 whitelist
wget https://github.com/10XGenomics/cellranger/raw/master/lib/python/cellranger/barcodes/3M-february-2018.txt.gz

# unzip
gunzip 3M-february-2018.txt.gz
```

```bash
#!/bin/bash
#SBATCH -J rnaseq
#SBATCH --mem 10GB
module load containers/singularity/3.9.9
module load bioinfo/Nextflow/21.10.6
nextflow run /work/project/lpgp/Nextflow/rnaseq/ \
-profile slurm \
--input "${PWD}/raw/*_{1,2}.fastq.gz" \
--genome "${PWD}/genome.fa.gz" \
--gff_gtf "${PWD}/annot.gtf.gz" \
--method "star_solo" \
--whitelist "${PWD}/3M-february-2018.txt" \
--soloCBstart  1 \
--soloCBlen 16 \
--soloUMIstart 17 \
--soloUMIlen 12 \
--out_dir "${PWD}/results"
```

## Single cell RNAseq from chromium (v3) chemistry using ALEVIN-fry (through simpleaf)

```bash
#!/bin/bash
#SBATCH -J rnaseq
#SBATCH --mem 10GB
module load containers/singularity/3.9.9
module load bioinfo/Nextflow/21.10.6
nextflow run /work/project/lpgp/Nextflow/rnaseq/ \
-profile slurm \
--input "${PWD}/raw/*_{1,2}.fastq.gz" \
--genome "${PWD}/genome.fa.gz" \
--gff_gtf "${PWD}/annot.gtf.gz" \
--method "alevin_fry" \
--chemistry "10xv3" \
--unfiltered-pl \
--rlen 91 \
--out_dir "${PWD}/results"
```

```bash
## chemistry options parameters

# chromium 10x v2 chemistry options
--chemitry "10xv2" # "1{b[16]u[10]x:}2{r:}"
--rlen 98

# chromium 10x v3 chemistry options
--chemistry "10xv3" # "1{b[16]u[12]x:}2{r:}"
--rlen 91

# brb chemistry options (bulk RNAseq)
--chemistry "brb" # "1{b[12]u[16]x:}2{r:}"
--whitelist "brb_whitelist.txt"
--rlen 91
```

## Defaults parameters

Please refer to [Trim Galore](https://github.com/FelixKrueger/TrimGalore), [STAR](https://github.com/alexdobin/STAR), [htseq-count](https://htseq.readthedocs.io/en/master/), and
[Salmon](https://salmon.readthedocs.io/en/latest/salmon.html) [simpleaf](https://simpleaf.readthedocs.io/en/latest/index.html) for complete arguments explanation.

```bash
# sequences
input = false
genome = false
transcriptome = false

# fastqc
skip_fastqc = false

# trimming
skip_trimming = false
clip_r1 = 0
clip_r2 = 0
three_prime_clip_r1 = 0
three_prime_clip_r2 = 0

# alignment mode should be star_htseq-count and/or salmon_saf for bulk-RNAseq
# alignment mode should be star_solo and/or alevin_saf and/or alevin_fry for BRBseq or scRNAseq
method = false

# STAR options
star_index = false
gff_gtf = false
sjdbOverhang = 99
keep_star_index = false
htseq_count_multimapped = false
feature_type = "exon"

# SALMON options
salmon_index = false
keep_salmon_index = false
writeMappings = false

# ALEVIN options
alevin_fry_index = false
keep_alevin_fry_index = false
chemistry = false
unfiltered-pl  = false
rlen = false
spliceu = false

# STAR SOLO options
star_index = false
gff_gtf = false
keep_star_index = false
barcodes = false
soloCBstart =  1
soloCBlen = 12
soloUMIstart = 13
soloUMIlen = 16

# save directory
out_dir = "${PWD}/results"
```

## References

1. Krueger F, Galore T. A wrapper tool around cutadapt and FastQC to consistently apply quality and adapter trimming to FastQ files [Internet]. Available from: http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/
2. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29:15–21.
3. Anders S, Pyl PT, Huber W. HTSeq–a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31:166–9.
4. Srivastava A, Malik L, Sarkar H, Zakeri M, Almodaresi F, Soneson C, et al. Alignment and mapping methodology influence transcript abundance estimation. Genome Biol. 2020;21:239.
5. Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods. 2017;14:417–9.