This pipeline was developed using the Snakemake workflow management system
You would need to have the Snakefile, the
env
folder and its contents (YAML files with environment d
Code Snippets
7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 | import os import re from collections import deque # ranks that krakefaction needs for lineage TAXA_RANKS = ['d','p','c','o','f','g','s', 's1'] """ # ============================================================================= # ============================================================================= """ """ # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Class - TaxonNode ------ PURPOSE ------- This class represents a node of a taxonomic level, with links to subtaxa and supertaxon. # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ """ class TaxonNode: def __init__(self, clade_count, taxa_count, rank, taxid, name, supertaxon=None): self.clade_count = int(clade_count) # num of db entries of this + subtaxa self.taxa_count = int(taxa_count) # num of db entries of this exact taxa self.rank = rank.lower() self.taxid = taxid self.name = name.strip().replace(' ', '_') self.supertaxon = supertaxon # link to supertaxon node self.subtaxa = [] # list of links to subtaxa nodes self.subtaxa_sum = int(taxa_count) self.lineage = '' def create_lineage(self): """Returns appropriate lineage string, based on ancestors""" # first case (domain) if self.rank == 'd': return 'd__' + self.name elif self.rank in TAXA_RANKS: return self.supertaxon.lineage + '|{}__{}'.format(self.rank, self.name) elif self.supertaxon: return self.supertaxon.lineage else: return '' def add_child(self, child): """Add a subtaxon child node to this node Add the new node's taxa_count to the subtaxa_sum of all supertaxa""" # add to parent's subtaxa list self.subtaxa.append(child) # add parent as child's supertaxa child.supertaxon = self if child.taxa_count != 0: # add tax_count to parent's sum self.subtaxa_sum += child.taxa_count curr_parent = self # add to any further ancestor's sums while curr_parent.supertaxon is not None: curr_parent = curr_parent.supertaxon curr_parent.subtaxa_sum += child.taxa_count # now that child has parent, create lineage child.lineage = child.create_lineage() return def has_full_subtaxa(self): """Return boolean whether all subtaxa have been added to this node""" return self.subtaxa_sum == self.clade_count def __str__(self): s = 'Taxon name: {} - Rank {}\n'.format(self.name, self.rank) s += '\tLineage: {}\n'.format(self.lineage) s += '\tTaxa ID: {}\n'.format(self.taxid) s += '\tClade count: {}\n'.format(self.clade_count) s += '\tTaxa count: {}\n'.format(self.taxa_count) s += '\tSubtaxa sum: {}\n'.format(self.subtaxa_sum) if self.supertaxon is not None: s += '\tSupertaxa: {}\n'.format(self.supertaxon.name) else: s += '\tSupertaxa: None\n' s += '\tSubtaxa: {}\n'.format(' '.join([subtaxon.name for subtaxon in self.subtaxa])) return s # def get_superlineage(node): # """Recursively finds the most recent lineage string from ancestors""" # # if supertaxon's lineage is not an empty string, return it # if node.supertaxon.lineage: # return node.supertaxon.lineage # # Else, recurse # else: # return get_superlineage(node.supertaxon) """ # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ """ """ # ============================================================================= MAIN # ============================================================================= """ def main(): """Verify inputs, then run script""" # get inspection filename and filtered kraken output file paths from snakemake db_inspection, infile_paths = get_inputs() run(db_inspection, infile_paths) """ # ============================================================================= # ============================================================================= """ def get_inputs(): """Get the inputs from snakemake. Database inspection file, and paths to filtered kraken output files""" # retrieve the name of the inspection file from snakemake db_inspection = snakemake.input[0] # retrieve the paths of filtered files from snakemake infile_paths = snakemake.input[1:] # verifiy files check_file_existence(db_inspection, infile_paths) return(db_inspection, infile_paths) def check_file_existence(db_ins, in_paths): """Validate file existence, raising error upon failure""" # check database inspection file if not os.path.isfile(db_ins): raise RuntimeError( "ERROR: could not open database inspection file {}\n".format(db_ins)) # check each kraken input file for f in in_paths: if not os.path.isfile(f): raise RuntimeError( "ERROR: could not open input file {}\n".format(f)) return """ # ============================================================================= """ def run(db_inspection, infile_paths): """Main logical control of the script occurs within""" taxon_dict = get_taxa_dict(db_inspection) for infile in infile_paths: f = open(infile, 'r') reads = f.readlines() f.close() create_outfile(reads, taxon_dict, infile) """ # ============================================================================= """ def get_taxa_dict(db_ins): """Produce a taxonomy dictionary with taxids as keys and lineage strings as values""" # get database inspection file as list of lines with open(db_ins, 'r') as f: inspection_lines = f.readlines() # create the taxon tree root = create_tree(inspection_lines) # create the taxid/lineage dictionary taxa_dict = {} build_taxa_dict(taxa_dict, root) return taxa_dict def create_tree(inspection_lines): """Create the taxonomy tree and return the root node""" # make deque for leftpopping of inspection lines inspection_lines = deque(inspection_lines) # create root node root_line = inspection_lines.popleft().split('\t') root_node = TaxonNode(*root_line[1:]) # stack for tracking nodes with more subtaxa to add stack = [] stack.append(root_node) # while there are still lines to make nodes from while inspection_lines: # get the node at the top of the stack curr_node = stack[-1] new_node = TaxonNode(*inspection_lines.popleft().split('\t')[1:]) # if current node has full subtaxa list, pop stack until otherwise if curr_node.has_full_subtaxa(): curr_node = find_next_parent(stack) # add the new node to the parent node curr_node.add_child(new_node) # put new node on top of stack if it still needs subtaxa if not new_node.has_full_subtaxa(): stack.append(new_node) return root_node def find_next_parent(stack): """Recursively pops stack until a node that still needs children is found""" node = stack[-1] if not node.has_full_subtaxa(): return stack[-1] else: stack.pop() return find_next_parent(stack) def build_taxa_dict(t_dict, node): """Recursively add taxid/lineage from tree to taxa dictionary""" # add current node if it has lineage if node.lineage: t_dict[str(node.taxid)] = node.lineage else: # if it has no lineage, it is root or subroot t_dict[str(node.taxid)] = 'root' for sub in node.subtaxa: build_taxa_dict(t_dict, sub) def create_outfile(reads, t_dict, filename): """Creates the formatted output table file""" with open(filename.replace('filtered', 'translated'), 'w') as f: for line in reads: columns = line.split('\t') # data to be first entry in output file datum = columns[1] # find the taxid tax_search = re.search('(?<=taxid )(\d*)', columns[2]) taxid = tax_search.group(1) if taxid in t_dict.keys(): #print(datum + '\t' + t_dict[taxid]) if line == reads[-1]: f.write(datum + '\t' + t_dict[taxid]) else: f.write(datum + '\t' + t_dict[taxid] + '\n') #else: # l.debug('Unable to translate: {}'.format(columns[2])) def print_tree(root): """Prints out tree top down""" print(root) for sub in root.subtaxa: print_tree(sub) return if __name__ == '__main__': main() |
48 49 | shell: 'fastp -i {input.fwd} -I {input.rev} -o {output.fwd} -O {output.rev} --html {output.html} --json {output.json} --thread {threads}' |
63 64 | shell: '(bowtie2 -p {threads} -x phiX -1 {input.fwd} -2 {input.rev} --un-conc-gz results/unmapped/{wildcards.sample}_R%_unmapped.fastq.gz) > /dev/null 2> {log}' |
75 76 | shell: 'fastqc {input} --outdir=results/fastqc' |
83 84 | shell: "multiqc -o results -n multiqc_report.html {input}" |
100 101 102 103 104 105 106 107 108 109 110 111 | shell: "kraken2 " "--db {params.db} " "--threads {threads} " "--output {output.kraken_class} " "--confidence {params.confidence} " "--minimum-base-quality {params.base_qual} " "--report {output.kraken_report} " "--paired " "--use-names " "--gzip-compressed " "{input.fwd} {input.rev}" |
119 120 121 | shell: """ktUpdateTaxonomy.sh ktImportTaxonomy -m 3 -t 5 {input} -o {output}""" |
136 137 | shell: "cat {input} | grep -v \"{params.filter_string}\" > {output}" |
147 148 | shell: "kraken2-inspect --db {input} > {output}" |
158 159 | script: "scripts/kraken2-translate.py" |
168 169 | shell: "krakefaction -u {input.untrans} -t {input.trans} -o {output}" |
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Created: 1yr ago
Updated: 1yr ago
Maitainers:
public
URL:
https://github.com/BeeCSI-Microbiome/taxonomic_profiling_pipeline
Name:
taxonomic_profiling_pipeline
Version:
1
Downloaded:
0
Copyright:
Public Domain
License:
None
Keywords:
- Future updates
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