lrbase-workflow

Workflow to construct SQLite files of LRBase.XXX.eg.db-type packages.

Pre-requisites

• Bash: GNU bash, version 4.2.46(1)-release (x86_64-redhat-linux-gnu)
• Snakemake: 6.0.5
• Singularity: 3.5.3

Summary

Evidence code

1. Known Ligand-Receptor (only human)

• DLRP: L-R list in DLRP database
• IUPHAR: L-R list in IUPHAR database
• HPMR: L-R list in HPMR database
• CELLPHONEDB: L-R list in CellPhoneDB database
• SINGLECELLSIGNALR: L-R list in SingleCellSignalR database

2. Known Ligand-Receptor (other species, ortholog based)

• ENSEMBL_DLRP: L-R list in DLRP based on the ortholog of Human genes in Ensembl Protein trees
• ENSEMBL_IUPHAR: L-R list in IUPHAR based on the ortholog of Human genes in Ensembl Protein trees
• ENSEMBL_HPMR: L-R list in HPMR based on the ortholog of Human genes in Ensembl Protein trees
• ENSEMBL_CELLPHONEDB: L-R list in CellPhoneDB database based on the ortholog of Human genes in Ensembl Protein trees
• ENSEMBL_SINGLECELLSIGNALR: L-R list in SingleCellSignalR database based on the ortholog of Human genes in Ensembl Protein trees
• NCBI_DLRP: L-R list in DLRP based on the ortholog of Human genes in NCBI Homologene
• NCBI_IUPHAR: L-R list in IUPHAR based on the ortholog of Human genes in NCBI Homologene
• NCBI_HPMR: L-R list in HPMR based on the ortholog of Human genes in NCBI Homologene
• NCBI_CELLPHONEDB: L-R list in CellPhoneDB database based on the ortholog of Human genes in NCBI Homologene
• NCBI_SINGLECELLSIGNALR: L-R list in SingleCellSignalR database based on the ortholog of Human genes in NCBI Homologene
• RBBH_DLRP: L-R list in DLRP based on the ortholog of Human genes in Reciprocal BLAST Best Hit used in MeSH.XXX.eg.db workflow
• RBBH_IUPHAR: L-R list in IUPHAR based on the ortholog of Human genes in Reciprocal BLAST Best Hit used in MeSH.XXX.eg.db workflow
• RBBH_HPMR: L-R list in HPMR based on the ortholog of Human genes in Reciprocal BLAST Best Hit used in MeSH.XXX.eg.db workflow
• RBBH_CELLPHONEDB: L-R list in CellPhoneDB database based on the ortholog of Human genes in Reciprocal BLAST Best Hit used in MeSH.XXX.eg.db workflow
• RBBH_SINGLECELLSIGNALR: L-R list in SingleCellSignalR database based on the ortholog of Human genes in Reciprocal BLAST Best Hit used in MeSH.XXX.eg.db workflow

3. Putative Ligand-Receptor (only human)

• SWISSPROT_HPRD: Known subcellular localization in Swiss-Prot and PPI list in HPRD
• TREMBL_HPRD: Predicted subcellular localization in TrEMBL and PPI list in HPRD
• FANTOM5: Predicted L-R list used in the FANTOM5 project
• BADERLAB: Predicted L-R list used in the Bader Lab

4. Putative Ligand-Receptor (other species, ortholog based)

• ENSEMBL_SWISSPROT_HPRD: Known subcellular localization in Swiss-Prot and PPI list in HPRD based on the ortholog of Human genes in Ensembl Protein trees
• ENSEMBL_TREMBL_HPRD: Predicted subcellular localization in TrEMBL and PPI list in HPRD based on the ortholog of Human genes in Ensembl Protein trees
• ENSEMBL_FANTOM5: Predicted L-R list used in the FANTOM5 project based on the ortholog of Human genes in Ensembl Protein trees
• ENSEMBL_BADERLAB: Predicted L-R list used in the Bader Lab based on the ortholog of Human genes in Ensembl Protein trees
• NCBI_SWISSPROT_HPRD: Known subcellular localization in Swiss-Prot and PPI list in HPRD based on the ortholog of Human genes in NCBI Homologene
• NCBI_TREMBL_HPRD: Predicted subcellular localization in TrEMBL and PPI list in HPRD based on the ortholog of Human genes in NCBI Homologene
• NCBI_FANTOM5: Predicted L-R list used in the FANTOM5 project based on the ortholog of Human genes in NCBI Homologene
• NCBI_BADERLAB: Predicted L-R list used in the Bader Lab based on the ortholog of Human genes in NCBI Homologene
• RBBH_SWISSPROT_HPRD: Known subcellular localization in Swiss-Prot and PPI list in HPRD based on the ortholog of Human genes in Reciprocal BLAST Best Hit used in MeSH.XXX.eg.db workflow
• RBBH_TREMBL_HPRD: Predicted subcellular localization in TrEMBL and PPI list in HPRD based on the ortholog of Human genes in Reciprocal BLAST Best Hit used in MeSH.XXX.eg.db workflow
• RBBH_FANTOM5: Predicted L-R list used in the FANTOM5 project based on the ortholog of Human genes in Reciprocal BLAST Best Hit used in MeSH.XXX.eg.db workflow
• RBBH_BADERLAB: Predicted L-R list used in the Bader Lab based on the ortholog of Human genes in Reciprocal BLAST Best Hit used in MeSH.XXX.eg.db workflow

5. Putative Ligand-Receptor (all species)

• SWISSPROT_SPRING: Known subcellular localization in Swiss-Prot and PPI list in SPRING
• TREMBL_SPRING: Predicted subcellular localization in TrEMBL and PPI list in SPRING

How to reproduce this workflow

1. Configuration

• data/rbbh/*.txt: Download from mesh-workflow/output/rbbh/*.txt and set them to data/rbbh/ directory.
• config.yaml: Check the latest version of STRING database (e.g., v11.0 on 2021/3/26 https://string-db.org) and change the value of VERSION_STRING, if it is needed. Also, specify the version of LRBase to crate.

2. Perform snakemake command

The workflow consists of two snakemake workflows. After performing workflow/workflow1.smk, perform workflow/workflow2.smk as follows.

In local machine:

snakemake -s workflow/download.smk -j 4 --use-singularity
snakemake -s workflow/preprocess_known_human.smk -j 4 --use-singularity
snakemake -s workflow/preprocess_known_otherspecies.smk -j 4 --use-singularity
snakemake -s workflow/preprocess_putative_human.smk -j 4 --use-singularity
snakemake -s workflow/preprocess_putative_otherspecies.smk -j 4 --use-singularity
snakemake -s workflow/preprocess_putative_allspecies.smk -j 4 --use-singularity
snakemake -s workflow/csv.smk -j 4 --use-singularity
snakemake -s workflow/sqlite.smk -j 4 --use-singularity
snakemake -s workflow/metadata.smk -j 4 --use-singularity
snakemake -s workflow/plot.smk -j 4 --use-singularity

In parallel environment (GridEngine):

snakemake -s workflow/download.smk -j 32 --cluster "qsub -l nc=4 -p -50 -r yes -q node.q" --latency-wait 600 --use-singularity
snakemake -s workflow/preprocess_known_human.smk -j 32 --cluster "qsub -l nc=4 -p -50 -r yes -q node.q" --latency-wait 600 --use-singularity
snakemake -s workflow/preprocess_known_otherspecies.smk -j 32 --cluster "qsub -l nc=4 -p -50 -r yes -q node.q" --latency-wait 600 --use-singularity
snakemake -s workflow/preprocess_known_allspecies.smk -j 32 --cluster "qsub -l nc=4 -p -50 -r yes -q node.q" --latency-wait 600 --use-singularity
snakemake -s workflow/preprocess_putative_human.smk -j 32 --cluster "qsub -l nc=4 -p -50 -r yes -q node.q" --latency-wait 600 --use-singularity
snakemake -s workflow/preprocess_putative_otherspecies.smk -j 32 --cluster "qsub -l nc=4 -p -50 -r yes -q node.q" --latency-wait 600 --use-singularity
snakemake -s workflow/csv.smk -j 32 --cluster "qsub -l nc=4 -p -50 -r yes -q node.q" --latency-wait 600 --use-singularity
snakemake -s workflow/sqlite.smk -j 32 --cluster "qsub -l nc=4 -p -50 -r yes -q node.q" --latency-wait 600 --use-singularity
snakemake -s workflow/metadata.smk -j 32 --cluster "qsub -l nc=4 -p -50 -r yes -q node.q" --latency-wait 600 --use-singularity
snakemake -s workflow/plot.smk -j 32 --cluster "qsub -l nc=4 -p -50 -r yes -q node.q" --latency-wait 600 --use-singularity

In parallel environment (Slurm):

snakemake -s workflow/download.smk -j 32 --cluster "sbatch -n 4 --nice=50 --requeue -p node03-06" --latency-wait 600 --use-singularity
snakemake -s workflow/preprocess_known_human.smk -j 32 --cluster "sbatch -n 4 --nice=50 --requeue -p node03-06" --latency-wait 600 --use-singularity
snakemake -s workflow/preprocess_known_otherspecies.smk -j 32 --cluster "sbatch -n 4 --nice=50 --requeue -p node03-06" --latency-wait 600 --use-singularity
snakemake -s workflow/preprocess_putative_human.smk -j 32 --cluster "sbatch -n 4 --nice=50 --requeue -p node03-06" --latency-wait 600 --use-singularity
snakemake -s workflow/preprocess_putative_otherspecies.smk -j 32 --cluster "sbatch -n 4 --nice=50 --requeue -p node03-06" --latency-wait 600 --use-singularity
snakemake -s workflow/preprocess_putative_allspecies.smk -j 32 --cluster "sbatch -n 4 --nice=50 --requeue -p node03-06" --latency-wait 600 --use-singularity
snakemake -s workflow/csv.smk -j 32 --cluster "sbatch -n 4 --nice=50 --requeue -p node03-06" --latency-wait 600 --use-singularity
snakemake -s workflow/sqlite.smk -j 32 --cluster "sbatch -n 4 --nice=50 --requeue -p node03-06" --latency-wait 600 --use-singularity
snakemake -s workflow/metadata.smk -j 32 --cluster "sbatch -n 4 --nice=50 --requeue -p node03-06" --latency-wait 600 --use-singularity
snakemake -s workflow/plot.smk -j 32 --cluster "sbatch -n 4 --nice=50 --requeue -p node03-06" --latency-wait 600 --use-singularity

License

Copyright (c) 2021 Koki Tsuyuzaki and RIKEN Bioinformatics Research Unit Released under the Artistic License 2.0.

Authors

• Koki Tsuyuzaki
• Manabu Ishii
• Itoshi Nikaido