Use ShortStack (Axtell 2013; Shahid and Axtell 2014; Johnson et al. 2016)to perform alignment of sRNAseq data and annotation of sRNA-producing genes.

The P.meandrina genome will be used as the reference genome.


Inputs:

Outputs:

Software requirements:

  • Utilizes a ShortStack Conda/Mamba environment, per the installation instructions.

Replace with name of your ShortStack environment and the path to the corresponding conda installation (find this after you’ve activated the environment).

E.g.

# Activate environment
conda activate ShortStack4_env

# Find conda path
which conda

1 Set R variables

shortstack_conda_env_name <- c("ShortStack-4.0.3_env")
shortstack_cond_path <- c("/home/sam/programs/mambaforge/condabin/conda")

2 Create a Bash variables file

This allows usage of Bash variables across R Markdown chunks.

{
echo "#### Assign Variables ####"
echo ""

echo "# Trimmed FastQ naming pattern"
echo "export trimmed_fastqs_pattern='*fastp-adapters-polyG-31bp-merged.fq.gz'"

echo "# Data directories"
echo 'export deep_dive_dir=/home/shared/8TB_HDD_01/sam/gitrepos/deep-dive'
echo 'export deep_dive_data_dir="${deep_dive_dir}/data"'
echo 'export output_dir_top=${deep_dive_dir}/F-Pmea/output/13.2-Pmea-sRNAseq-ShortStack-31bp-fastp-merged'
echo 'export trimmed_fastqs_dir="${deep_dive_dir}/F-Pmea/output/08.2-Pmea-sRNAseq-trimming-31bp-fastp-merged/trimmed-reads"'
echo ""

echo "# Input/Output files"
echo 'export genome_fasta_dir=${deep_dive_dir}/F-Pmea/data'
echo 'export genome_fasta_name="Pocillopora_meandrina_HIv1.assembly.fasta"'
echo 'export shortstack_genome_fasta_name="Pocillopora_meandrina_HIv1.assembly.fa"'
echo 'export mirbase_mature_fasta=mature.fa'
echo 'export mirbase_mature_fasta_version=mirbase-mature-v22.1.fa'
echo 'export genome_fasta="${genome_fasta_dir}/${shortstack_genome_fasta_name}"'
echo ""

echo "# External data URLs"
echo 'export mirbase_fasta_url="https://mirbase.org/download_version_files/22.1/"'
echo ""

echo "# Set number of CPUs to use"
echo 'export threads=46'
echo ""

echo "# Initialize arrays"
echo 'export trimmed_fastqs_array=()'


} > .bashvars

cat .bashvars
#### Assign Variables ####

# Trimmed FastQ naming pattern
export trimmed_fastqs_pattern='*fastp-adapters-polyG-31bp-merged.fq.gz'
# Data directories
export deep_dive_dir=/home/shared/8TB_HDD_01/sam/gitrepos/deep-dive
export deep_dive_data_dir="${deep_dive_dir}/data"
export output_dir_top=${deep_dive_dir}/F-Pmea/output/13.2-Pmea-sRNAseq-ShortStack-31bp-fastp-merged
export trimmed_fastqs_dir="${deep_dive_dir}/F-Pmea/output/08.2-Pmea-sRNAseq-trimming-31bp-fastp-merged/trimmed-reads"

# Input/Output files
export genome_fasta_dir=${deep_dive_dir}/F-Pmea/data
export genome_fasta_name="Pocillopora_meandrina_HIv1.assembly.fasta"
export shortstack_genome_fasta_name="Pocillopora_meandrina_HIv1.assembly.fa"
export mirbase_mature_fasta=mature.fa
export mirbase_mature_fasta_version=mirbase-mature-v22.1.fa
export genome_fasta="${genome_fasta_dir}/${shortstack_genome_fasta_name}"

# External data URLs
export mirbase_fasta_url="https://mirbase.org/download_version_files/22.1/"

# Set number of CPUs to use
export threads=46

# Initialize arrays
export trimmed_fastqs_array=()

3 Load ShortStack conda environment

If this is successful, the first line of output should show that the Python being used is the one in your [ShortStack](https://github.com/MikeAxtell/ShortStack conda environment path.

E.g.

python: /home/sam/programs/mambaforge/envs/mirmachine_env/bin/python

use_condaenv(condaenv = shortstack_conda_env_name, conda = shortstack_cond_path)

# Check successful env loading
py_config()
python:         /home/sam/programs/mambaforge/envs/ShortStack-4.0.3_env/bin/python
libpython:      /home/sam/programs/mambaforge/envs/ShortStack-4.0.3_env/lib/libpython3.10.so
pythonhome:     /home/sam/programs/mambaforge/envs/ShortStack-4.0.3_env:/home/sam/programs/mambaforge/envs/ShortStack-4.0.3_env
version:        3.10.13 | packaged by conda-forge | (main, Dec 23 2023, 15:36:39) [GCC 12.3.0]
numpy:          /home/sam/programs/mambaforge/envs/ShortStack-4.0.3_env/lib/python3.10/site-packages/numpy
numpy_version:  1.26.4

NOTE: Python version was forced by use_python() function

4 Download miRBase mature miRNA FastA

# Load bash variables into memory
source .bashvars

wget \
--directory-prefix ${deep_dive_data_dir} \
--recursive \
--no-check-certificate \
--continue \
--no-host-directories \
--no-directories \
--no-parent \
--quiet \
--execute robots=off \
 ${mirbase_fasta_url}/${mirbase_mature_fasta}

# Rename to indicate miRBase FastA version
mv ${deep_dive_data_dir}/${mirbase_mature_fasta} ${deep_dive_data_dir}/${mirbase_mature_fasta_version}

ls -lh "${deep_dive_data_dir}"
total 13M
drwxr-xr-x 2 sam sam 4.0K Nov  7 14:36 blast_dbs
-rw-r--r-- 1 sam sam 3.7M Feb 16 12:36 mirbase-mature-v22.1.fa
-rw-r--r-- 1 sam sam 3.7M Dec  4 11:05 mirbase-mature-v22.1-no_spaces.fa
-rw-r--r-- 1 sam sam 3.7M Nov 17 07:59 mirbase-mature-v22.1-no_U.fa
-rw-r--r-- 1 sam sam 726K Nov  7 14:36 mirgene-mature-all-v2.1.fa
-rw-r--r-- 1 sam sam 726K Nov 17 07:59 mirgene-mature-all-v2.1-no_U.fa

5 Run ShortStack

5.1 Modify genome filename for ShortStack compatability

# Load bash variables into memory
source .bashvars

# Check for FastA file first
# Then create rename file if doesn't exist
if [ -f "${genome_fasta_dir}/${shortstack_genome_fasta_name}" ]; then
  echo "${genome_fasta_dir}/${shortstack_genome_fasta_name} already exists. Nothing to do."
  echo ""
else

  # Copy genome FastA to ShortStack-compatible filename (ending with .fa)
  cp ${genome_fasta_dir}/${genome_fasta_name} ${genome_fasta_dir}/${shortstack_genome_fasta_name}
fi

# Confirm
ls -lh ${genome_fasta_dir}/${shortstack_genome_fasta_name}
/home/shared/8TB_HDD_01/sam/gitrepos/deep-dive/F-Pmea/data/Pocillopora_meandrina_HIv1.assembly.fa already exists. Nothing to do.

-rw-r--r-- 1 sam sam 360M Feb 16 10:28 /home/shared/8TB_HDD_01/sam/gitrepos/deep-dive/F-Pmea/data/Pocillopora_meandrina_HIv1.assembly.fa

5.2 Excecute ShortStack command

Uses the --dn_mirna option to identify miRNAs in the genome, without relying on the --known_miRNAs.

This part of the code redirects the output of time to the end of shortstack.log file.

  • ; } \ 2>> ${output_dir_top}/shortstack.log
# Load bash variables into memory
source .bashvars

# Make output directory, if it doesn't exist
mkdir --parents "${output_dir_top}"

# Create array of trimmed FastQs
trimmed_fastqs_array=(${trimmed_fastqs_dir}/${trimmed_fastqs_pattern})


# Pass array contents to new variable as space-delimited list
trimmed_fastqs_list=$(echo "${trimmed_fastqs_array[*]}")


###### Run ShortStack ######
{ time \
ShortStack \
--genomefile "${genome_fasta}" \
--readfile ${trimmed_fastqs_list} \
--known_miRNAs ${deep_dive_data_dir}/${mirbase_mature_fasta_version} \
--dn_mirna \
--threads ${threads} \
--outdir ${output_dir_top}/ShortStack_out \
&> ${output_dir_top}/shortstack.log ; } \
2>> ${output_dir_top}/shortstack.log

5.3 Check runtime

# Load bash variables into memory
source .bashvars

tail -n 3 ${output_dir_top}/shortstack.log \
| grep "real" \
| awk '{print "ShortStack runtime:" "\t" $2}'
ShortStack runtime: 44m14.960s

6 Results

6.1 ShortStack synopsis

# Load bash variables into memory
source .bashvars

tail -n 25 ${output_dir_top}/shortstack.log
Writing final files

Found a total of 34 MIRNA loci


Non-MIRNA loci by DicerCall:
N 7091
22 36
23 34
21 17
24 15

Creating visualizations of microRNA loci with strucVis
<<< WARNING >>>
Do not rely on these results alone to annotate new MIRNA loci!
The false positive rate for de novo MIRNA identification is low, but NOT ZERO
Insepct each mirna locus, especially the strucVis output, and see
https://doi.org/10.1105/tpc.17.00851 , https://doi.org/10.1093/nar/gky1141

Fri 16 Feb 2024 12:31:08 -0800 PST
Run Completed!

real    44m14.960s
user    814m50.436s
sys 284m22.086s

ShortStack identified 34 miRNAs.

6.2 Inspect Results.txt

# Load bash variables into memory
source .bashvars

head ${output_dir_top}/ShortStack_out/Results.txt

echo ""
echo "----------------------------------------------------------"
echo ""

echo "Nummber of potential loci:"
awk '(NR>1)' ${output_dir_top}/ShortStack_out/Results.txt | wc -l
Locus   Name    Chrom   Start   End Length  Reads   DistinctSequences   FracTop Strand  MajorRNA    MajorRNAReads   Short   Long    21  22  23  24  DicerCall   MIRNA   known_miRNAs
Pocillopora_meandrina_HIv1___Sc0000000:9092-9521    Cluster_1   Pocillopora_meandrina_HIv1___Sc0000000  9092    9521    430 10833   356 0.9999076894673682  +   GGGGGUAUAGCUCAGUGGUAGA  3890    1408    3758    629 4434    178 426 N   N   NA
Pocillopora_meandrina_HIv1___Sc0000000:53578-53997  Cluster_2   Pocillopora_meandrina_HIv1___Sc0000000  53578   53997   420 286 13  0.9965034965034965  +   GCCUAAGUUGCUUGGAACA 137 284 2   0   0   0   0   N   N   NA
Pocillopora_meandrina_HIv1___Sc0000000:150243-150718    Cluster_3   Pocillopora_meandrina_HIv1___Sc0000000  150243  150718  476 2549    247 0.0 -   UGGCUAUGAUGAAAAUGACU    335 849 380 634 376 139 171 N   N   NA
Pocillopora_meandrina_HIv1___Sc0000000:173728-174150    Cluster_4   Pocillopora_meandrina_HIv1___Sc0000000  173728  174150  423 1257    65  0.9968178202068417  +   UUUGAUUGCUGUGAUCUGGUUG  432 106 2   39  636 444 30  22  N   NA
Pocillopora_meandrina_HIv1___Sc0000000:187562-188076    Cluster_5   Pocillopora_meandrina_HIv1___Sc0000000  187562  188076  515 187 35  0.4385026737967914  .   AUAAAUGUCACUACAAGAAACCUGAAAUCGU 25  0   179 1   1   2   4   N   N   NA
Pocillopora_meandrina_HIv1___Sc0000000:485730-486254    Cluster_6   Pocillopora_meandrina_HIv1___Sc0000000  485730  486254  525 286 127 1.0 +   GAUGGGUGUUAUUACUCCUCAGACAGAC    48  66  183 7   11  3   16  N   N   NA
Pocillopora_meandrina_HIv1___Sc0000000:496020-496432    Cluster_7   Pocillopora_meandrina_HIv1___Sc0000000  496020  496432  413 72  24  1.0 +   AUGUAGUCGAGCAAAGUCCAUGUGGACGA   27  0   66  2   1   1   2   N   N   NA
Pocillopora_meandrina_HIv1___Sc0000000:525310-527342    Cluster_8   Pocillopora_meandrina_HIv1___Sc0000000  525310  527342  2033    14694   2987    0.1809582142371036  -   UUUUCGUCACUUUCUUCAGCCUCAGAGU    966 136 13598   50  106 303 501 N   N   NA
Pocillopora_meandrina_HIv1___Sc0000000:541262-541723    Cluster_9   Pocillopora_meandrina_HIv1___Sc0000000  541262  541723  462 726 137 0.081267217630854   -   UUGGACGAAAUUUCGAGGUUCACACUCGUU  91  1   720 1   2   1   1   N   N   NA

----------------------------------------------------------

Nummber of potential loci:
7227

Column 20 of the Results.txt file identifies if a cluster is a miRNA or not (Y or N).

# Load bash variables into memory
source .bashvars

echo "Number of loci characterized as miRNA:"
awk '$20=="Y" {print $0}' ${output_dir_top}/ShortStack_out/Results.txt \
| wc -l
echo ""

echo "----------------------------------------------------------"

echo ""
echo "Number of loci _not_ characterized as miRNA:"
awk '$20=="N" {print $0}' ${output_dir_top}/ShortStack_out/Results.txt \
| wc -l
Number of loci characterized as miRNA:
34

----------------------------------------------------------

Number of loci _not_ characterized as miRNA:
7193

Column 21 of the Results.txt file identifies if a cluster aligned to a known miRNA (miRBase) or not (Y or NA).

Since there are no miRNAs, the following code will not print any output.

The echo command after the awk command is simply there to prove that the chunk executed.

# Load bash variables into memory
source .bashvars

echo "Number of loci matching miRBase miRNAs:"
awk '$21!="NA" {print $0}' ${output_dir_top}/ShortStack_out/Results.txt \
| wc -l
echo ""

echo "----------------------------------------------------------"

echo ""
echo "Number of loci _not_ matching miRBase miRNAs:"
awk '$21=="NA" {print $0}' ${output_dir_top}/ShortStack_out/Results.txt \
| wc -l
Number of loci matching miRBase miRNAs:
79

----------------------------------------------------------

Number of loci _not_ matching miRBase miRNAs:
7149

Although there are loci with matches to miRBase miRNAs, ShortStack did not annotate these clusters as miRNAs likely because they do not also match secondary structure criteria.

6.2.1 Directory tree of all ShortStack outputs

Many of these are large (by GitHub standards) BAM files, so will not be added to the repo.

Additionally, it’s unlikely we’ll utilize most of the other files (bigwig) generated by ShortStack.

# Load bash variables into memory
source .bashvars

tree -h ${output_dir_top}/
/home/shared/8TB_HDD_01/sam/gitrepos/deep-dive/F-Pmea/output/13.2-Pmea-sRNAseq-ShortStack-31bp-fastp-merged/
├── [ 21K]  shortstack.log
└── [ 16K]  ShortStack_out
    ├── [ 28K]  alignment_details.tsv
    ├── [606K]  Counts.txt
    ├── [160K]  known_miRNAs.gff3
    ├── [1.8M]  known_miRNAs_unaligned.fasta
    ├── [6.9M]  merged_alignments_21_m.bw
    ├── [7.1M]  merged_alignments_21_p.bw
    ├── [6.7M]  merged_alignments_22_m.bw
    ├── [6.8M]  merged_alignments_22_p.bw
    ├── [ 13M]  merged_alignments_23-24_m.bw
    ├── [ 13M]  merged_alignments_23-24_p.bw
    ├── [1.0G]  merged_alignments.bam
    ├── [153K]  merged_alignments.bam.csi
    ├── [ 45M]  merged_alignments_other_m.bw
    ├── [ 45M]  merged_alignments_other_p.bw
    ├── [ 23M]  merged_alignments_sRNA-POC-47-S1-TP2-fastp-adapters-polyG-31bp-merged.bw
    ├── [ 30M]  merged_alignments_sRNA-POC-48-S1-TP2-fastp-adapters-polyG-31bp-merged.bw
    ├── [ 24M]  merged_alignments_sRNA-POC-50-S1-TP2-fastp-adapters-polyG-31bp-merged.bw
    ├── [ 38M]  merged_alignments_sRNA-POC-53-S1-TP2-fastp-adapters-polyG-31bp-merged.bw
    ├── [ 49M]  merged_alignments_sRNA-POC-57-S1-TP2-fastp-adapters-polyG-31bp-merged.bw
    ├── [ 12K]  mir.fasta
    ├── [919K]  Results.gff3
    ├── [1.4M]  Results.txt
    ├── [179M]  sRNA-POC-47-S1-TP2-fastp-adapters-polyG-31bp-merged.bam
    ├── [169K]  sRNA-POC-47-S1-TP2-fastp-adapters-polyG-31bp-merged.bam.csi
    ├── [192M]  sRNA-POC-48-S1-TP2-fastp-adapters-polyG-31bp-merged.bam
    ├── [170K]  sRNA-POC-48-S1-TP2-fastp-adapters-polyG-31bp-merged.bam.csi
    ├── [174M]  sRNA-POC-50-S1-TP2-fastp-adapters-polyG-31bp-merged.bam
    ├── [169K]  sRNA-POC-50-S1-TP2-fastp-adapters-polyG-31bp-merged.bam.csi
    ├── [231M]  sRNA-POC-53-S1-TP2-fastp-adapters-polyG-31bp-merged.bam
    ├── [169K]  sRNA-POC-53-S1-TP2-fastp-adapters-polyG-31bp-merged.bam.csi
    ├── [209M]  sRNA-POC-57-S1-TP2-fastp-adapters-polyG-31bp-merged.bam
    ├── [159K]  sRNA-POC-57-S1-TP2-fastp-adapters-polyG-31bp-merged.bam.csi
    └── [4.0K]  strucVis
        ├── [ 12K]  Cluster_1007.ps
        ├── [ 35K]  Cluster_1007.txt
        ├── [ 11K]  Cluster_1062.ps
        ├── [3.6K]  Cluster_1062.txt
        ├── [ 11K]  Cluster_1075.ps
        ├── [ 10K]  Cluster_1075.txt
        ├── [ 11K]  Cluster_1115.ps
        ├── [7.3K]  Cluster_1115.txt
        ├── [ 12K]  Cluster_1287.ps
        ├── [ 25K]  Cluster_1287.txt
        ├── [ 13K]  Cluster_1293.ps
        ├── [ 64K]  Cluster_1293.txt
        ├── [ 13K]  Cluster_1798.ps
        ├── [ 41K]  Cluster_1798.txt
        ├── [ 12K]  Cluster_1954.ps
        ├── [ 39K]  Cluster_1954.txt
        ├── [ 12K]  Cluster_1955.ps
        ├── [ 30K]  Cluster_1955.txt
        ├── [ 12K]  Cluster_20.ps
        ├── [ 30K]  Cluster_20.txt
        ├── [ 12K]  Cluster_2790.ps
        ├── [8.3K]  Cluster_2790.txt
        ├── [ 12K]  Cluster_2834.ps
        ├── [5.1K]  Cluster_2834.txt
        ├── [ 11K]  Cluster_2836.ps
        ├── [7.4K]  Cluster_2836.txt
        ├── [ 11K]  Cluster_2856.ps
        ├── [ 14K]  Cluster_2856.txt
        ├── [ 11K]  Cluster_2973.ps
        ├── [5.6K]  Cluster_2973.txt
        ├── [ 11K]  Cluster_3400.ps
        ├── [ 31K]  Cluster_3400.txt
        ├── [ 11K]  Cluster_34.ps
        ├── [3.7K]  Cluster_34.txt
        ├── [ 12K]  Cluster_359.ps
        ├── [ 40K]  Cluster_359.txt
        ├── [ 11K]  Cluster_3668.ps
        ├── [ 14K]  Cluster_3668.txt
        ├── [ 12K]  Cluster_4055.ps
        ├── [7.7K]  Cluster_4055.txt
        ├── [ 12K]  Cluster_4056.ps
        ├── [5.1K]  Cluster_4056.txt
        ├── [ 12K]  Cluster_4138.ps
        ├── [ 14K]  Cluster_4138.txt
        ├── [ 12K]  Cluster_4458.ps
        ├── [ 36K]  Cluster_4458.txt
        ├── [ 12K]  Cluster_4460.ps
        ├── [ 53K]  Cluster_4460.txt
        ├── [ 12K]  Cluster_4461.ps
        ├── [ 25K]  Cluster_4461.txt
        ├── [ 12K]  Cluster_4462.ps
        ├── [ 30K]  Cluster_4462.txt
        ├── [ 12K]  Cluster_4591.ps
        ├── [ 64K]  Cluster_4591.txt
        ├── [ 12K]  Cluster_4769.ps
        ├── [6.9K]  Cluster_4769.txt
        ├── [ 12K]  Cluster_4839.ps
        ├── [ 31K]  Cluster_4839.txt
        ├── [ 12K]  Cluster_5639.ps
        ├── [ 16K]  Cluster_5639.txt
        ├── [ 12K]  Cluster_5768.ps
        ├── [ 17K]  Cluster_5768.txt
        ├── [ 12K]  Cluster_6424.ps
        ├── [ 21K]  Cluster_6424.txt
        ├── [ 12K]  Cluster_753.ps
        ├── [ 27K]  Cluster_753.txt
        ├── [ 12K]  Cluster_914.ps
        └── [ 29K]  Cluster_914.txt

2 directories, 101 files

Citations

Axtell, Michael J. 2013. “ShortStack: Comprehensive Annotation and Quantification of Small RNA Genes.” RNA 19 (6): 740–51. https://doi.org/10.1261/rna.035279.112.
Johnson, Nathan R, Jonathan M Yeoh, Ceyda Coruh, and Michael J Axtell. 2016. “Improved Placement of Multi-Mapping Small RNAs.” G3 Genes|Genomes|Genetics 6 (7): 2103–11. https://doi.org/10.1534/g3.116.030452.
Shahid, Saima, and Michael J. Axtell. 2014. “Identification and Annotation of Small RNA Genes Using ShortStack.” Methods 67 (1): 20–27. https://doi.org/10.1016/j.ymeth.2013.10.004.
---
title: "13.2-Pmea-sRNAseq-ShortStack-31bp-fastp-merged"
author: "Sam White"
date: "2024-02-16"
output: 
  bookdown::html_document2:
    theme: cosmo
    toc: true
    toc_float: true
    number_sections: true
    code_folding: show
    code_download: true
  github_document:
    toc: true
    number_sections: true
  html_document:
    theme: cosmo
    toc: true
    toc_float: true
    number_sections: true
    code_folding: show
    code_download: true
bibliography: references.bib
link-citations: true
---

```{r setup, include=FALSE}
library(knitr)
library(kableExtra)
library(dplyr)
library(reticulate)
knitr::opts_chunk$set(
  echo = TRUE,         # Display code chunks
  eval = FALSE,        # Evaluate code chunks
  warning = FALSE,     # Hide warnings
  message = FALSE,     # Hide messages
  comment = ""         # Prevents appending '##' to beginning of lines in code output
)
```

Use [ShortStack](https://github.com/MikeAxtell/ShortStack) [@axtell2013a; @shahid2014; @johnson2016a]to perform alignment of sRNAseq data and annotation of sRNA-producing genes.

The *P.meandrina* genome will be used as the reference genome.

------------------------------------------------------------------------

Inputs:

-   Requires trimmed sRNAseq files generated by [08.1-Pmea-sRNAseq-trimming-R1-only.Rmd](https://github.com/urol-e5/deep-dive/blob/main/F-Pmea/code/08.1-Pmea-sRNAseq-trimming-R1-only.Rmd)

    -   Filenames formatted: `*fastp-adapters-polyG-31bp-merged.fq.gz`

-   *P.meandrina* genome FastA. See [12-Pmea-sRNAseq-MirMachine.Rmd](https://github.com/urol-e5/deep-dive/blob/main/F-Pmea/code/12-Pmea-sRNAseq-MirMachine.Rmd) for download info if needed.

Outputs:

-   See [ShortStack outputs documentation](https://github.com/MikeAxtell/ShortStack#outputs) for full list and detailed descriptions.

Software requirements:

-   Utilizes a [ShortStack](https://github.com/MikeAxtell/ShortStack#installation) Conda/Mamba environment, per the installation instructions.

Replace with name of your ShortStack environment and the path to the corresponding conda installation (find this *after* you've activated the environment).

E.g.

``` bash
# Activate environment
conda activate ShortStack4_env

# Find conda path
which conda
```

------------------------------------------------------------------------

# Set R variables

```{r R-variables, eval=TRUE}
shortstack_conda_env_name <- c("ShortStack-4.0.3_env")
shortstack_cond_path <- c("/home/sam/programs/mambaforge/condabin/conda")
```

# Create a Bash variables file

This allows usage of Bash variables across R Markdown chunks.

```{r save-bash-variables-to-rvars-file, engine='bash', eval=TRUE}
{
echo "#### Assign Variables ####"
echo ""

echo "# Trimmed FastQ naming pattern"
echo "export trimmed_fastqs_pattern='*fastp-adapters-polyG-31bp-merged.fq.gz'"

echo "# Data directories"
echo 'export deep_dive_dir=/home/shared/8TB_HDD_01/sam/gitrepos/deep-dive'
echo 'export deep_dive_data_dir="${deep_dive_dir}/data"'
echo 'export output_dir_top=${deep_dive_dir}/F-Pmea/output/13.2-Pmea-sRNAseq-ShortStack-31bp-fastp-merged'
echo 'export trimmed_fastqs_dir="${deep_dive_dir}/F-Pmea/output/08.2-Pmea-sRNAseq-trimming-31bp-fastp-merged/trimmed-reads"'
echo ""

echo "# Input/Output files"
echo 'export genome_fasta_dir=${deep_dive_dir}/F-Pmea/data'
echo 'export genome_fasta_name="Pocillopora_meandrina_HIv1.assembly.fasta"'
echo 'export shortstack_genome_fasta_name="Pocillopora_meandrina_HIv1.assembly.fa"'
echo 'export mirbase_mature_fasta=mature.fa'
echo 'export mirbase_mature_fasta_version=mirbase-mature-v22.1.fa'
echo 'export genome_fasta="${genome_fasta_dir}/${shortstack_genome_fasta_name}"'
echo ""

echo "# External data URLs"
echo 'export mirbase_fasta_url="https://mirbase.org/download_version_files/22.1/"'
echo ""

echo "# Set number of CPUs to use"
echo 'export threads=46'
echo ""

echo "# Initialize arrays"
echo 'export trimmed_fastqs_array=()'


} > .bashvars

cat .bashvars
```

# Load [ShortStack](https://github.com/MikeAxtell/ShortStack) conda environment

If this is successful, the first line of output should show that the Python being used is the one in your [ShortStack](<https://github.com/MikeAxtell/ShortStack> conda environment path.

E.g.

`python:         /home/sam/programs/mambaforge/envs/mirmachine_env/bin/python`

```{r load-shortstack-conda-env, eval=TRUE}
use_condaenv(condaenv = shortstack_conda_env_name, conda = shortstack_cond_path)

# Check successful env loading
py_config()
```

# Download [miRBase](https://mirbase.org/) mature miRNA FastA

```{r download-mirbase-mature-fasta, engine='bash', eval=TRUE}
# Load bash variables into memory
source .bashvars

wget \
--directory-prefix ${deep_dive_data_dir} \
--recursive \
--no-check-certificate \
--continue \
--no-host-directories \
--no-directories \
--no-parent \
--quiet \
--execute robots=off \
 ${mirbase_fasta_url}/${mirbase_mature_fasta}

# Rename to indicate miRBase FastA version
mv ${deep_dive_data_dir}/${mirbase_mature_fasta} ${deep_dive_data_dir}/${mirbase_mature_fasta_version}

ls -lh "${deep_dive_data_dir}"
```

# Run ShortStack

## Modify genome filename for ShortStack compatability

```{r rename-genome-filename, engine='bash', cache=TRUE, eval=TRUE}
# Load bash variables into memory
source .bashvars

# Check for FastA file first
# Then create rename file if doesn't exist
if [ -f "${genome_fasta_dir}/${shortstack_genome_fasta_name}" ]; then
  echo "${genome_fasta_dir}/${shortstack_genome_fasta_name} already exists. Nothing to do."
  echo ""
else

  # Copy genome FastA to ShortStack-compatible filename (ending with .fa)
  cp ${genome_fasta_dir}/${genome_fasta_name} ${genome_fasta_dir}/${shortstack_genome_fasta_name}
fi

# Confirm
ls -lh ${genome_fasta_dir}/${shortstack_genome_fasta_name}
```

## Excecute ShortStack command

Uses the `--dn_mirna` option to identify miRNAs in the genome, without relying on the `--known_miRNAs`.

This part of the code redirects the output of `time` to the end of `shortstack.log` file.

-   `; } \ 2>> ${output_dir_top}/shortstack.log`



```{r shortstack, engine='bash', cache=TRUE}
# Load bash variables into memory
source .bashvars

# Make output directory, if it doesn't exist
mkdir --parents "${output_dir_top}"

# Create array of trimmed FastQs
trimmed_fastqs_array=(${trimmed_fastqs_dir}/${trimmed_fastqs_pattern})


# Pass array contents to new variable as space-delimited list
trimmed_fastqs_list=$(echo "${trimmed_fastqs_array[*]}")


###### Run ShortStack ######
{ time \
ShortStack \
--genomefile "${genome_fasta}" \
--readfile ${trimmed_fastqs_list} \
--known_miRNAs ${deep_dive_data_dir}/${mirbase_mature_fasta_version} \
--dn_mirna \
--threads ${threads} \
--outdir ${output_dir_top}/ShortStack_out \
&> ${output_dir_top}/shortstack.log ; } \
2>> ${output_dir_top}/shortstack.log

```

## Check runtime

```{r engine='bash', eval=TRUE}
# Load bash variables into memory
source .bashvars

tail -n 3 ${output_dir_top}/shortstack.log \
| grep "real" \
| awk '{print "ShortStack runtime:" "\t" $2}'

```


# Results

## ShortStack synopsis

```{r shortstack-synopsis, engine='bash', eval=TRUE}
# Load bash variables into memory
source .bashvars

tail -n 25 ${output_dir_top}/shortstack.log
```

ShortStack identified 34 miRNAs.

## Inspect `Results.txt`

```{r results-txt-file, engine='bash', eval=TRUE}
# Load bash variables into memory
source .bashvars

head ${output_dir_top}/ShortStack_out/Results.txt

echo ""
echo "----------------------------------------------------------"
echo ""

echo "Nummber of potential loci:"
awk '(NR>1)' ${output_dir_top}/ShortStack_out/Results.txt | wc -l
```

Column 20 of the `Results.txt` file identifies if a cluster is a miRNA or not (`Y` or `N`).

```{r results-txt-miRNAs, engine='bash', eval=TRUE}
# Load bash variables into memory
source .bashvars

echo "Number of loci characterized as miRNA:"
awk '$20=="Y" {print $0}' ${output_dir_top}/ShortStack_out/Results.txt \
| wc -l
echo ""

echo "----------------------------------------------------------"

echo ""
echo "Number of loci _not_ characterized as miRNA:"
awk '$20=="N" {print $0}' ${output_dir_top}/ShortStack_out/Results.txt \
| wc -l

```

Column 21 of the `Results.txt` file identifies if a cluster aligned to a known miRNA (miRBase) or not (`Y` or `NA`).

Since there are no miRNAs, the following code will *not* print any output.

The `echo` command after the `awk` command is simply there to prove that the chunk executed.

```{r results-txt-miRBase-miRNAs, engine='bash', eval=TRUE}
# Load bash variables into memory
source .bashvars

echo "Number of loci matching miRBase miRNAs:"
awk '$21!="NA" {print $0}' ${output_dir_top}/ShortStack_out/Results.txt \
| wc -l
echo ""

echo "----------------------------------------------------------"

echo ""
echo "Number of loci _not_ matching miRBase miRNAs:"
awk '$21=="NA" {print $0}' ${output_dir_top}/ShortStack_out/Results.txt \
| wc -l

```

Although there are loci with matches to miRBase miRNAs, ShortStack did *not* annotate these clusters as miRNAs likely [because they do not *also* match secondary structure criteria](https://github.com/MikeAxtell/ShortStack#mirna-annotation).

### Directory tree of all ShortStack outputs

Many of these are large (by GitHub standards) BAM files, so will not be added to the repo.

Additionally, it's unlikely we'll utilize most of the other files (bigwig) generated by ShortStack.

```{r shortstack-directory-tree, engine='bash', eval=TRUE}
# Load bash variables into memory
source .bashvars

tree -h ${output_dir_top}/

```

------------------------------------------------------------------------

# Citations