Help improve this workflow!
This workflow has been published but could be further improved with some additional meta data:- Keyword(s) in categories input, output, operation, topic
You can help improve this workflow by suggesting the addition or removal of keywords, suggest changes and report issues, or request to become a maintainer of the Workflow .
( PH age IDE ntification PIPE line R epository)
This repository contains a snakemake workflow that utilizes state-of-the-art tools to identify free-phages and prophages in metagenomic sequences (viral enriched and whole-community).
Code Snippets
60 61 62 63 64 65 | shell: """ # symlink input paths to renamed files ln -s {input.R1} {output.R1} ln -s {input.R2} {output.R2} """ |
95 96 97 98 99 100 | shell: """ # symlink input paths to renamed files ln -s {input.R1} {output.R1} ln -s {input.R2} {output.R2} """ |
118 119 120 121 122 | shell: """ gunzip -c {input.R1} > {output.R1} gunzip -c {input.R2} > {output.R2} """ |
147 148 149 150 151 152 153 154 155 156 157 158 | shell: """ # run clumpify clumpify.sh \ in={input.R1} \ in2={input.R2} \ out={output.R1} \ out2={output.R2} \ {params.extra_args} > {output.log} 2>&1 cp {output.log} {log} """ |
177 178 179 180 181 | shell: """ # download human genome reference to desired directory kneaddata_database --download human_genome bowtie2 {params.kneaddata_db} """ |
217 218 219 220 221 222 223 224 225 226 227 228 | shell: """ # run kneaddata to quality filter and remove host reads kneaddata --input {input.R1} --input {input.R2} \ --output {params.output_dir} \ --output-prefix {params.prefix} \ --reference-db {params.human_db} \ --threads {threads} \ {params.extra_args} cp {output.log} {log} """ |
262 263 264 265 266 267 268 | shell: """ # generate read counts from kneaddata log files kneaddata_read_count_table \ --input {params.log_dir} \ --output {output} """ |
68 69 70 71 72 73 74 75 | shell: """ # combine reads for coassembly cat {input.R1} > {output.R1} cat {input.R2} > {output.R2} cat {input.R1S} > {output.R1S} cat {input.R2S} > {output.R2S} """ |
103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 | shell: """ # assemble reads using metaspades spades.py \ --meta \ --pe1-1 {input.R1} \ --pe1-2 {input.R2} \ --pe1-s {input.R1S} \ --pe1-s {input.R2S} \ -o {params.output_dir} \ --threads {threads} \ {params.extra_args} # copy spades.log to log file cp {params.output_dir}/spades.log {log} """ |
142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 | shell: """ # assembly analysis using quast metaquast.py \ {input} \ -o {params.output_dir} \ --threads {threads} \ --min-contig {params.min_len} \ --contig-thresholds 0,1000,5000,10000,{params.min_len} \ --labels {params.labels} \ {params.extra_args} # copy spades.log to log file cp {params.output_dir}/quast.log {log} """ |
204 205 206 207 208 | shell: """ # combine quast reports for all assemblies, only keeping the header from one file awk 'FNR>1 || NR==1' {input} > {output} """ |
54 55 56 57 | shell: """ cat {input} > {output} """ |
82 83 84 85 86 87 88 89 90 91 92 93 94 95 | shell: """ # make a blast db from phage contigs makeblastdb -in {input} -out {params.blastdb} -dbtype nucl # all against all blast blastn -query {input} -db {params.blastdb} -out {params.blast_tsv} -num_threads {threads} -outfmt '6 std qlen slen' -max_target_seqs 25000 -perc_identity 90 # calculate ani and af from blast results python {params.blastani_script} -i {params.blast_tsv} -o {params.ani_tsv} # cluster phage genomes based on 95% ani and 85% af python {params.cluster_script} --fna {input} --ani {params.ani_tsv} --out {output} --min_ani {params.min_ani} --min_qcov {params.min_qcov} --min_tcov {params.min_tcov} """ |
133 134 135 136 137 138 139 140 141 142 143 144 145 146 | shell: """ # make a blast db from phage contigs makeblastdb -in {input} -out {params.blastdb} -dbtype nucl # all against all blast blastn -query {input} -db {params.blastdb} -out {params.blast_tsv} -num_threads {threads} -outfmt '6 std qlen slen' -max_target_seqs 25000 -perc_identity 90 # calculate ani and af from blast results python {params.blastani_script} -i {params.blast_tsv} -o {params.ani_tsv} # cluster phage genomes based on 95% ani and 85% af python {params.cluster_script} --fna {input} --ani {params.ani_tsv} --out {output} --min_ani {params.min_ani} --min_qcov {params.min_qcov} --min_tcov {params.min_tcov} """ |
171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 | shell: """ # make a bowtie2 db from virusdb bowtie2-build {input.virusdb} {params.db} --threads {threads} # align reads to bowtie2 database bowtie2 \ --threads {threads} \ -x {params.db} \ -1 {input.R1} \ -2 {input.R2} \ -U {input.R1S},{input.R2S} \ -S {params.sam} # convert sam to bam samtools view -S -b {params.sam} > {output} rm -rf {params.sam} """ |
199 200 201 202 203 204 205 | shell: """ # build metapop pip install metapop touch {output} """ |
228 229 230 231 232 233 234 235 236 | shell: """ # run metapop to identify viruses present in samples metapop --input_samples {params.bam_dir} \ --reference {input.virusdb} \ --genes /home/carsonjm/resources/virusdb/proteins/all_genomes_genes.fasta \ --output {params.out_dir} \ --no_micro --no_macro """ |
283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 | shell: """ # concatenate results cat {input.viruses} {input.virusdb} > {output.combined} # make a blast db from phage contigs makeblastdb -in {output.combined} -out {params.blastdb} -dbtype nucl # all against all blast blastn -query {output.combined} -db {params.blastdb} -out {params.blast_tsv} -num_threads {threads} -outfmt '6 std qlen slen' -max_target_seqs 25000 -perc_identity 90 # calculate ani and af from blast results python {params.blastani_script} -i {params.blast_tsv} -o {params.ani_tsv} # cluster phage genomes based on 95% ani and 85% af python {params.cluster_script} --fna {output.combined} --ani {params.ani_tsv} --out {output.clusters} --min_ani {params.min_ani} --min_qcov {params.min_qcov} --min_tcov {params.min_tcov} """ |
47 48 49 50 51 52 53 54 | shell: """ # make blastdb makeblastdb \ -in {input} \ -out {params.spacers_blastdb} \ -dbtype nucl """ |
70 71 72 73 74 75 76 77 78 79 80 81 | shell: """ # blast viruses against uhgg spacers blastn \ -query {input.viruses} \ -db {params.spacers_blastdb} \ -out {output} \ -outfmt '6 std qlen slen' \ -dust no \ -word_size 18 \ -num_threads {threads} """ |
114 115 116 117 118 119 120 121 122 123 124 125 126 127 | shell: """ # git clone phist rm -rf {params.phist_dir} git clone --recurse-submodules https://github.com/refresh-bio/PHIST {params.phist_dir} # build phist cd {params.phist_dir} make mkdir ./out # test phist python3 phist.py ./example/virus ./example/host ./out/common_kmers.csv ./out/predictions.csv """ |
158 159 160 161 162 163 | shell: """ # run phist using uhgg python3 {params.phist_script} {params.virus_dir} {params.bacteria_db_dir} {output.table} {output.predictions} \ --t {threads} """ |
200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 | shell: """ # download rafah files wget -P {params.rafah_dir} https://sourceforge.net/projects/rafah/files/RaFAH_v0.3_Files/README.md wget -P {params.rafah_dir} https://sourceforge.net/projects/rafah/files/RaFAH_v0.3_Files/RaFAH_v0.3_hmm_models.tgz wget -P {params.rafah_dir} https://sourceforge.net/projects/rafah/files/RaFAH_v0.3_Files/RaFAH_v0.3_Ranger_Model.tgz wget -P {params.rafah_dir} https://sourceforge.net/projects/rafah/files/RaFAH_v0.3_Files/RaFAH.pl wget -P {params.rafah_dir} https://sourceforge.net/projects/rafah/files/RaFAH_v0.3_Files/HP_Ranger_Model_3_Valid_Cols.txt wget -P {params.rafah_dir} https://sourceforge.net/projects/rafah/files/RaFAH_v0.3_Files/RaFAH_Predict_Host.R wget -P {params.rafah_dir} https://sourceforge.net/projects/rafah/files/RaFAH_v0.3_Files/RaFAH_Train_Model.R # decompress models cd {params.rafah_dir} tar -zxvf RaFAH_v0.3_hmm_models.tgz tar -zxvf RaFAH_v0.3_Ranger_Model.tgz """ |
239 240 241 242 243 244 245 246 247 248 249 250 251 252 | shell: """ cd {params.out_dir} perl {input.rafah} --predict \ --genomes_dir {params.virus_dir} \ --extension .fna \ --valid_ogs_file {input.valid_cols} \ --genomexog_table_file_name /home/carsonjm/CarsonJM/phide_piper/results/07_VIRUS_HOST/03_rafah/RaFAH_Genome_to_OGs_Score_Min_Score_50-Max_evalue_1e-05_Prediction.tsv \ --hmmer_db_file_name {params.hmm} \ --r_script_predict_file_name {input.predict_script} \ --r_model_file_name {input.filename} \ --threads {threads} """ |
46 47 48 49 50 51 | shell: """ # symlink input paths to renamed files ln -s {input.R1} {output.R1} ln -s {input.R2} {output.R2} """ |
70 71 72 73 74 75 | shell: """ # make a bowtie2 db from virusdb bowtie2-build {input} {params.db} --threads {threads} {params.extra_args} """ |
104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 | shell: """ # align reads to bowtie2 database bowtie2 \ --threads {threads} \ -x {params.db} \ -1 {input.R1} \ -2 {input.R2} \ -S {params.sam} \ > {log} 2>&1 \ {params.extra_args} # convert sam to bam samtools view -S -b {params.sam} > {output} rm {params.sam} """ |
152 153 154 155 156 157 158 | shell: """ kraken2-build --download-taxonomy --db {params.db} kraken2-build --add-to-library {input} --db {params.db} kraken2-build --build --db {params.db} {params.extra_args} """ |
180 181 182 183 184 185 186 | shell: """ kraken2 --paired {input.R1} {input.R2} \ --db {params.db} \ --report {output.report} > {output.classification} \ {params.extra_args} """ |
203 204 205 206 207 | shell: """ bracken-build -d {params.db} -t {threads} -k 35 -l 150 \ {params.extra_args} """ |
226 227 228 229 230 231 232 233 234 235 | shell: """ bracken -d {params.db} \ -i {input.report} \ -o {output.abundance} \ -r 150 \ -l {params.level} \ -t {threads} \ {params.extra_args} """ |
261 262 263 264 | shell: """ echo -e {wildcards.assembly_sample}”\t”$(samtools view -c {input} > {output}) """ |
273 274 275 276 | shell: """ cat {input} > {output} """ |
301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 | shell: """ pip install metapop # run metapop to identify viruses present in samples metapop --input_samples {params.bam_dir} \ --norm {input.read_counts} \ --reference {params.viruses_dir} \ --output {params.out_dir} \ --min_cov {params.min_breadth} \ --minimum_bases_for_detection {params.min_length} \ --min_dep {params.min_depth} \ --no_micro \ --threads {threads} \ {params.extra_args} """ |
331 332 333 334 335 | shell: """ prodigal -i {input} \ -o {output} """ |
344 345 346 347 | shell: """ samtools sort {input.bam} -o {output.sort} """ |
364 365 366 367 368 369 370 371 372 373 374 | shell: """ inStrain profile \ {input.bam} \ {input.fasta} \ -o {params.out_dir} \ --skip_mm_profiling \ --skip_genome_wide \ --min_cov {params.min_breadth} \ {params.extra_args} """ |
394 395 396 397 398 399 400 401 | shell: """ inStrain compare \ -i {params.profile} \ -o {params.out_dir} \ -bams {params.bam} \ {params.extra_args} """ |
Support
Do you know this workflow well? If so, you can
request seller status , and start supporting this workflow.
Created: 1yr ago
Updated: 1yr ago
Maitainers:
public
URL:
https://github.com/margotl9/phide_piper_dev
Name:
phide_piper_dev
Version:
1
Downloaded:
0
Copyright:
Public Domain
License:
None
Keywords:
- Future updates
Related Workflows
ENCODE pipeline for histone marks developed for the psychENCODE project
psychip pipeline is an improved version of the ENCODE pipeline for histone marks developed for the psychENCODE project.
The o...
Near-real time tracking of SARS-CoV-2 in Connecticut
Repository containing scripts to perform near-real time tracking of SARS-CoV-2 in Connecticut using genomic data. This pipeli...
snakemake workflow to run cellranger on a given bucket using gke.
A Snakemake workflow for running cellranger on a given bucket using Google Kubernetes Engine. The usage of this workflow ...
ATLAS - Three commands to start analyzing your metagenome data
Metagenome-atlas is a easy-to-use metagenomic pipeline based on snakemake. It handles all steps from QC, Assembly, Binning, t...
raw sequence reads
Genome assembly
Annotation track
checkm2
gunc
prodigal
snakemake-wrapper-utils
MEGAHIT
Atlas
BBMap
Biopython
BioRuby
Bwa-mem2
cd-hit
CheckM
DAS
Diamond
eggNOG-mapper v2
MetaBAT 2
Minimap2
MMseqs
MultiQC
Pandas
Picard
pyfastx
SAMtools
SemiBin
Snakemake
SPAdes
SqueezeMeta
TADpole
VAMB
CONCOCT
ete3
gtdbtk
h5py
networkx
numpy
plotly
psutil
utils
metagenomics
RNA-seq workflow using STAR and DESeq2
This workflow performs a differential gene expression analysis with STAR and Deseq2. The usage of this workflow is described ...
This Snakemake pipeline implements the GATK best-practices workflow
This Snakemake pipeline implements the GATK best-practices workflow for calling small germline variants. The usage of thi...