diff options
Diffstat (limited to 'gn2/wqflask/snp_browser')
| -rw-r--r-- | gn2/wqflask/snp_browser/__init__.py | 0 | ||||
| -rw-r--r-- | gn2/wqflask/snp_browser/snp_browser.py | 934 |
2 files changed, 934 insertions, 0 deletions
diff --git a/gn2/wqflask/snp_browser/__init__.py b/gn2/wqflask/snp_browser/__init__.py new file mode 100644 index 00000000..e69de29b --- /dev/null +++ b/gn2/wqflask/snp_browser/__init__.py diff --git a/gn2/wqflask/snp_browser/snp_browser.py b/gn2/wqflask/snp_browser/snp_browser.py new file mode 100644 index 00000000..2d17f82b --- /dev/null +++ b/gn2/wqflask/snp_browser/snp_browser.py @@ -0,0 +1,934 @@ +import string +from PIL import (Image) + +from gn2.base import species +from gn2.base import webqtlConfig + +from gn2.wqflask.database import database_connection + +from gn2.utility.tools import get_setting + + +class SnpBrowser: + + def __init__(self, db_cursor, start_vars): + self.strain_lists = get_browser_sample_lists() + self.initialize_parameters(db_cursor, start_vars) + + if self.first_run == "false": + self.filtered_results = self.get_browser_results() + self.table_rows = self.get_table_rows() + self.rows_count = len(self.table_rows) + + del self.filtered_results + + if 'sEcho' not in start_vars: + self.table_rows = [] + + if self.limit_strains == "true": + self.header_fields, self.empty_field_count, self.header_data_names = get_header_list( + variant_type=self.variant_type, strains=self.chosen_strains, empty_columns=self.empty_columns) + else: + self.header_fields, self.empty_field_count, self.header_data_names = get_header_list( + variant_type=self.variant_type, strains=self.strain_lists, species=self.species_name, empty_columns=self.empty_columns) + + def initialize_parameters(self, db_cursor, start_vars): + if 'first_run' in start_vars: + self.first_run = "false" + else: + self.first_run = "true" + self.allele_list = [] + + self.variant_type = "SNP" + if 'variant' in start_vars: + self.variant_type = start_vars['variant'] + + self.species_name = "Mouse" + self.species_id = 1 + if 'species' in start_vars: + self.species_name = start_vars['species'] + if self.species_name.capitalize() == "Rat": + self.species_id = 2 + + self.mouse_chr_list = [] + self.rat_chr_list = [] + mouse_species_ob = species.TheSpecies(species_name="Mouse") + for key in mouse_species_ob.chromosomes.chromosomes(db_cursor): + self.mouse_chr_list.append( + mouse_species_ob.chromosomes.chromosomes(db_cursor)[key].name) + rat_species_ob = species.TheSpecies(species_name="Rat") + for key in rat_species_ob.chromosomes.chromosomes(db_cursor): + self.rat_chr_list.append( + rat_species_ob.chromosomes.chromosomes(db_cursor)[key].name) + + if self.species_id == 1: + self.this_chr_list = self.mouse_chr_list + else: + self.this_chr_list = self.rat_chr_list + + if self.first_run == "true": + self.chr = "19" + self.start_mb = 30.1 + self.end_mb = 30.12 + else: + if 'gene_name' in start_vars: + if start_vars['gene_name'] != "": + self.gene_name = start_vars['gene_name'] + else: + self.gene_name = "" + self.chr = start_vars['chr'] + try: + self.start_mb = float(start_vars['start_mb']) + self.end_mb = float(start_vars['end_mb']) + except: + self.start_mb = 0.0 + self.end_mb = 0.0 + else: + try: + self.chr = start_vars['chr'] + self.start_mb = float(start_vars['start_mb']) + self.end_mb = float(start_vars['end_mb']) + except: + self.chr = "1" + self.start_mb = 0.0 + self.end_mb = 0.0 + + self.limit_strains = "true" + if self.first_run == "false": + if 'limit_strains' not in start_vars: + self.limit_strains = "false" + else: + if start_vars['limit_strains'] == "false": + self.limit_strains = "false" + + self.chosen_strains_mouse = ["C57BL/6J", + "DBA/2J", + "A/J", + "129S1/SvImJ", + "NOD/ShiLtJ", + "NZO/HlLtJ", + "WSB/EiJ", + "PWK/PhJ", + "CAST/EiJ"] + self.chosen_strains_rat = ["BN", "F344", "WLI", "WMI"] + if 'chosen_strains_mouse' in start_vars: + self.chosen_strains_mouse = start_vars['chosen_strains_mouse'].split( + ",") + if 'chosen_strains_rat' in start_vars: + self.chosen_strains_rat = start_vars['chosen_strains_rat'].split( + ",") + + if self.species_id == 1: + self.chosen_strains = self.chosen_strains_mouse + else: + self.chosen_strains = self.chosen_strains_rat + + self.domain = "All" + if 'domain' in start_vars: + self.domain = start_vars['domain'] + self.function = "All" + if 'function' in start_vars: + self.function = start_vars['function'] + self.source = "All" + if 'source' in start_vars: + self.source = start_vars['source'] + self.criteria = ">=" + if 'criteria' in start_vars: + self.criteria = start_vars['criteria'] + self.score = 0.0 + if 'score' in start_vars: + self.score = start_vars['score'] + + self.redundant = "false" + if self.first_run == "false" and 'redundant' in start_vars: + self.redundant = "true" + self.diff_alleles = "true" + if self.first_run == "false": + if 'diff_alleles' not in start_vars: + self.diff_alleles = "false" + else: + if start_vars['diff_alleles'] == "false": + self.diff_alleles = "false" + + def get_browser_results(self): + self.snp_list = None + __query = "" + __vars = None + with database_connection(get_setting("SQL_URI")) as conn, conn.cursor() as cursor: + if self.gene_name != "": + if self.species_id != 0: + __query = ("SELECT geneSymbol, chromosome, txStart, " + "txEnd FROM GeneList WHERE SpeciesId = %s " + "AND geneSymbol = %s") + __vars = (self.species_id, self.gene_name,) + else: + __query = ("SELECT geneSymbol, chromosome, txStart, " + "txEnd FROM GeneList WHERE geneSymbol = %s") + __vars = (self.gene_name,) + cursor.execute(__query, __vars) + + if result := cursor.fetchone(): + self.gene_name, self.chr, self.start_mb, self.end_mb = result + else: + if self.variant_type in ["SNP", "InDel"]: + result_snp = None + __vars = (self.gene_name,) + if self.variant_type == "SNP": + if self.gene_name[:2] == "rs": + __query = ("SELECT Id, Chromosome, Position, " + "Position+0.000001 FROM SnpAll " + "WHERE Rs = %s") + else: + if self.species_id != 0: + __query = ( + "SELECT Id, Chromosome, Position, " + "Position+0.000001 FROM SnpAll WHERE " + "SpeciesId = %s AND SnpName = %s") + __vars = (self.species_id, self.gene_name,) + else: + __query = ( + "SELECT Id, Chromosome, Position, " + "Position+0.000001 FROM SnpAll " + "WHERE SnpName = %s") + cursor.execute(__query, __vars) + result_snp = cursor.fetchall() + else: # variant_type == InDel + if self.gene_name[0] == "I": + if self.species_id != 0: + __query = ( + "SELECT Id, Chromosome, Mb_start, " + "Mb_end FROM IndelAll WHERE " + "SpeciesId = %s AND Name = %s") + __vars = (self.species_id, self.gene_name,) + else: + __query = ( + "SELECT Id, Chromosome, Mb_start, " + "Mb_end FROM IndelAll WHERE Name = %s",) + __vars = (self.gene_name,) + cursor.execute(__query, __vars) + result_snp = cursor.fetchall() + if result_snp: + self.snp_list = [item[0] for item in result_snp] + self.chr = result_snp[0][1] + self.start_mb = result_snp[0][2] + self.end_mb = result_snp[0][3] + else: + return [] + + if self.variant_type == "SNP": + __vars = (self.species_id, self.chr, + f"{self.start_mb:.6f}", + f"{self.end_mb:.6f}",) + if self.species_id == 1: # Mouse + __query = ("SELECT a.*, b.* FROM SnpAll a, SnpPattern b " + "WHERE a.SpeciesId = %s AND a.Chromosome = %s " + "AND a.Position >= %s AND a.Position < %s " + "AND a.Id = b.SnpId ORDER BY a.Position") + elif self.species_id == 2: # Rat + __query = ( + "SELECT a.*, b.* FROM SnpAll a, RatSnpPattern b " + "WHERE a.SpeciesId = %s AND a.Chromosome = %s " + "AND a.Position >= %s AND a.Position < %s " + "AND a.Id = b.SnpId ORDER BY a.Position") + + elif self.variant_type == "InDel": + if self.species_id != 0: + __query = ( + "SELECT DISTINCT a.Name, a.Chromosome, a.SourceId, " + "a.Mb_start, a.Mb_end, a.Strand, a.Type, a.Size, " + "a.InDelSequence, b.Name FROM IndelAll a, " + "SnpSource b WHERE a.SpeciesId = %s AND " + "a.Chromosome = %s AND a.Mb_start >= %s " + "AND a.Mb_start < %s AND b.Id = a.SourceId " + "ORDER BY a.Mb_start") + __vars = (self.species_id, + self.chr, f"{self.start_mb:2.6f}", + f"{self.end_mb+0.0010:2.6f}",) + cursor.execute(__query, __vars) + else: + __query = ( + "SELECT DISTINCT a.Name, a.Chromosome, a.SourceId, " + "a.Mb_start, a.Mb_end, a.Strand, a.Type, a.Size, " + "a.InDelSequence, b.Name FROM IndelAll a, " + "SnpSource b WHERE a.Chromosome = %s AND " + "a.Mb_start >= %s AND a.Mb_start < %s " + "AND b.Id = a.SourceId ORDER BY a.Mb_start") + __vars = (self.chr, f"{self.start_mb+0.0010:2.6f}", + f"{self.end_mb+0.0010:2.6f}",) + cursor.execute(__query, __vars) + return self.filter_results(cursor.fetchall()) + + def filter_results(self, results): + filtered_results = [] + strain_index_list = [] # ZS: List of positions of selected strains in strain list + last_mb = -1 + + if self.limit_strains == "true" and len(self.chosen_strains) > 0: + for item in self.chosen_strains: + index = self.strain_lists[self.species_name.lower()].index( + item) + strain_index_list.append(index) + + for seq, result in enumerate(results): + result = list(result) + + if self.variant_type == "SNP": + display_strains = [] + snp_id, species_id, snp_name, rs, chr, mb, mb_2016, alleles, snp_source, conservation_score = result[ + :10] + effect_list = result[10:28] + if self.species_id == 1: + self.allele_list = result[30:] + elif self.species_id == 2: + self.allele_list = result[31:] + + if self.limit_strains == "true" and len(self.chosen_strains) > 0: + for index in strain_index_list: + if self.species_id == 1: + display_strains.append(result[29 + index]) + elif self.species_id == 2: + display_strains.append(result[31 + index]) + self.allele_list = display_strains + + effect_info_dict = get_effect_info(effect_list) + coding_domain_list = ['Start Gained', 'Start Lost', + 'Stop Gained', 'Stop Lost', 'Nonsynonymous', 'Synonymous'] + intron_domain_list = ['Splice Site', 'Nonsplice Site'] + + for key in effect_info_dict: + if key in coding_domain_list: + domain = ['Exon', 'Coding'] + elif key in ['3\' UTR', '5\' UTR']: + domain = ['Exon', key] + elif key == "Unknown Effect In Exon": + domain = ['Exon', ''] + elif key in intron_domain_list: + domain = ['Intron', key] + else: + domain = [key, ''] + + if 'Intergenic' in domain: + if self.gene_name != "": + gene_id = get_gene_id( + self.species_id, self.gene_name) + gene = [gene_id, self.gene_name] + else: + gene = check_if_in_gene(species_id, chr, mb) + transcript = exon = function = function_details = '' + if self.redundant == "false" or last_mb != mb: # filter redundant + if self.include_record(domain, function, snp_source, conservation_score): + info_list = [snp_name, rs, chr, mb, alleles, gene, transcript, exon, domain, + function, function_details, snp_source, conservation_score, snp_id] + info_list.extend(self.allele_list) + filtered_results.append(info_list) + last_mb = mb + else: + gene_list, transcript_list, exon_list, function_list, function_details_list = effect_info_dict[ + key] + for index, item in enumerate(gene_list): + gene = item + transcript = transcript_list[index] + if exon_list: + exon = exon_list[index] + else: + exon = "" + + if function_list: + function = function_list[index] + if function == "Unknown Effect In Exon": + function = "Unknown" + else: + function = "" + + if function_details_list: + function_details = "Biotype: " + \ + function_details_list[index] + else: + function_details = "" + + if self.redundant == "false" or last_mb != mb: + if self.include_record(domain, function, snp_source, conservation_score): + info_list = [snp_name, rs, chr, mb, alleles, gene, transcript, exon, domain, + function, function_details, snp_source, conservation_score, snp_id] + info_list.extend(self.allele_list) + filtered_results.append(info_list) + last_mb = mb + + elif self.variant_type == "InDel": + # The order of variables is important; this applies to anything from the variant table as indel + indel_name, indel_chr, source_id, indel_mb_start, indel_mb_end, indel_strand, indel_type, indel_size, indel_sequence, source_name = result + + indel_type = indel_type.title() + if self.redundant == "false" or last_mb != indel_mb_start: + gene = "No Gene" + domain = conservation_score = snp_id = snp_name = rs = flank_3 = flank_5 = ncbi = function = "" + if self.include_record(domain, function, source_name, conservation_score): + filtered_results.append([indel_name, indel_chr, indel_mb_start, indel_mb_end, + indel_strand, indel_type, indel_size, indel_sequence, source_name]) + last_mb = indel_mb_start + + else: + filtered_results.append(result) + + return filtered_results + + def get_table_rows(self): + """ Take results and put them into the order and format necessary for the tables rows """ + + if self.variant_type == "SNP": + gene_name_list = [] + for item in self.filtered_results: + if item[5] and item[5] != "": + gene_name = item[5][1] + # eliminate duplicate gene_name + if gene_name and (gene_name not in gene_name_list): + gene_name_list.append(gene_name) + if len(gene_name_list) > 0: + gene_id_name_dict = get_gene_id_name_dict( + self.species_id, gene_name_list) + + # ZS: list of booleans representing which columns are entirely empty, so they aren't displayed on the page; only including ones that are sometimes empty (since there's always a location, etc) + self.empty_columns = { + "snp_source": "false", + "conservation_score": "false", + "gene_name": "false", + "transcript": "false", + "exon": "false", + "domain_2": "false", + "function": "false", + "function_details": "false" + } + + the_rows = [] + for i, result in enumerate(self.filtered_results): + this_row = {} + if self.variant_type == "SNP": + snp_name, rs, chr, mb, alleles, gene, transcript, exon, domain, function, function_details, snp_source, conservation_score, snp_id = result[ + :14] + allele_value_list = result[14:] + if rs: + snp_url = webqtlConfig.DBSNP % (rs) + snp_name = rs + else: + rs = "" + start_bp = int(mb * 1000000 - 100) + end_bp = int(mb * 1000000 + 100) + position_info = "chr%s:%d-%d" % (chr, start_bp, end_bp) + if self.species_id == 2: + snp_url = webqtlConfig.GENOMEBROWSER_URL % ( + "rn6", position_info) + else: + snp_url = webqtlConfig.GENOMEBROWSER_URL % ( + "mm10", position_info) + + mb = float(mb) + mb_formatted = "%2.6f" % mb + + if snp_source == "Sanger/UCLA": + source_url_1 = "http://www.sanger.ac.uk/resources/mouse/genomes/" + source_url_2 = "http://mouse.cs.ucla.edu/mousehapmap/beta/wellcome.html" + source_urls = [source_url_1, source_url_2] + self.empty_columns['snp_source'] = "true" + else: + source_urls = [] + + if not conservation_score: + conservation_score = "" + else: + self.empty_columns['conservation_score'] = "true" + + if gene: + gene_name = gene[1] + # if gene_name has related gene_id, use gene_id for NCBI search + if (gene_name in gene_id_name_dict) and (gene_id_name_dict[gene_name] != None and gene_id_name_dict[gene_name] != ""): + gene_id = gene_id_name_dict[gene[1]] + gene_link = webqtlConfig.NCBI_LOCUSID % gene_id + else: + gene_link = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?CMD=search&DB=gene&term=%s" % gene_name + + self.empty_columns['gene_name'] = "true" + else: + gene_name = "" + gene_link = "" + + if transcript: + transcript_link = webqtlConfig.ENSEMBLETRANSCRIPT_URL % ( + transcript) + self.empty_columns['transcript'] = "true" + else: + transcript_link = "" + + if exon: + exon = exon[1] # exon[0] is exon_id, exon[1] is exon_rank + self.empty_columns['exon'] = "true" + else: + exon = "" + + if domain: + domain_1 = domain[0] + domain_2 = domain[1] + if domain_1 == "Intergenic" and gene != "": + domain_1 = gene_name + else: + if domain_1 == "Exon": + domain_1 = domain_1 + " " + exon + + if domain_2 != "": + self.empty_columns['domain_2'] = "true" + + if function: + self.empty_columns['function'] = "true" + + function_list = [] + if function_details: + function_list = function_details.strip().split(",") + function_list = [item.strip() for item in function_list] + function_list[0] = function_list[0].title() + function_details = ", ".join( + item for item in function_list) + function_details = function_details.replace("_", " ") + function_details = function_details.replace("/", " -> ") + if function_details == "Biotype: Protein Coding": + function_details = function_details + ", Coding Region Unknown" + + self.empty_columns['function_details'] = "true" + + #[snp_href, chr, mb_formatted, alleles, snp_source_cell, conservation_score, gene_name_cell, transcript_href, exon, domain_1, domain_2, function, function_details] + + base_color_dict = {"A": "#C33232", "C": "#1569C7", "T": "#CFCF32", "G": "#32C332", + "t": "#FF6", "c": "#5CB3FF", "a": "#F66", "g": "#CF9", ":": "#FFFFFF", "-": "#FFFFFF", "?": "#FFFFFF"} + + the_bases = [] + for j, item in enumerate(allele_value_list): + if item and isinstance(item, str): + this_base = [str(item), base_color_dict[item]] + else: + this_base = "" + + the_bases.append(this_base) + + this_row = { + "index": i + 1, + "rs": str(rs), + "snp_url": str(snp_url), + "snp_name": str(snp_name), + "chr": str(chr), + "mb_formatted": mb_formatted, + "alleles": str(alleles), + "snp_source": str(snp_source), + "source_urls": source_urls, + "conservation_score": str(conservation_score), + "gene_name": str(gene_name), + "gene_link": str(gene_link), + "transcript": str(transcript), + "transcript_link": str(transcript_link), + "exon": str(exon), + "domain_1": str(domain_1), + "domain_2": str(domain_2), + "function": str(function), + "function_details": str(function_details), + "allele_value_list": the_bases + } + + elif self.variant_type == "InDel": + indel_name, indel_chr, indel_mb_s, indel_mb_e, indel_strand, indel_type, indel_size, indel_sequence, source_name = result + this_row = { + "index": i, + "indel_name": str(indel_name), + "indel_chr": str(indel_chr), + "indel_mb_s": str(indel_mb_s), + "indel_mb_e": str(indel_mb_e), + "indel_strand": str(indel_strand), + "indel_type": str(indel_type), + "indel_size": str(indel_size), + "indel_sequence": str(indel_sequence), + "source_name": str(source_name) + } + #this_row = [indel_name, indel_chr, indel_mb_s, indel_mb_e, indel_strand, indel_type, indel_size, indel_sequence, source_name] + + the_rows.append(this_row) + + return the_rows + + def include_record(self, domain, function, snp_source, conservation_score): + """ Decide whether to add this record """ + + domain_satisfied = True + function_satisfied = True + different_alleles_satisfied = True + source_satisfied = True + + if domain: + if len(domain) == 0: + if self.domain != "All": + domain_satisfied = False + else: + domain_satisfied = False + if domain[0].startswith(self.domain) or domain[1].startswith(self.domain) or self.domain == "All": + domain_satisfied = True + else: + if self.domain != "All": + domain_satisfied = False + + if snp_source: + if len(snp_source) == 0: + if self.source != "All": + source_satisfied = False + else: + source_satisfied = False + if snp_source.startswith(self.source) or self.source == "All": + source_satisfied = True + else: + if self.source != "All": + source_satisfied = False + + if function: + if len(function) == 0: + if self.function != "All": + function_satisfied = False + else: + function_satisfied = False + if self.function != "All": + if function.startswith(self.function): + function_satisfied = True + else: + function_satisfied = True + else: + if self.function != "All": + function_satisfied = False + + if conservation_score: + score_as_float = float(conservation_score) + try: + input_score_float = float(self.score) # the user-input score + except: + input_score_float = 0.0 + + if self.criteria == ">=": + if score_as_float >= input_score_float: + score_satisfied = True + else: + score_satisfied = False + elif self.criteria == "==": + if score_as_float == input_score_float: + score_satisfied = True + else: + score_satisfied = False + elif self.criteria == "<=": + if score_as_float <= input_score_float: + score_satisfied = True + else: + score_satisfied = False + else: + try: + if float(self.score) > 0: + score_satisfied = False + else: + score_satisfied = True + except: + score_satisfied = True + + if self.variant_type == "SNP" and self.diff_alleles == "true": + this_allele_list = [] + + for item in self.allele_list: + if item and isinstance(item, str) and (item.lower() not in this_allele_list) and (item != "-"): + this_allele_list.append(item.lower()) + + total_allele_count = len(this_allele_list) + if total_allele_count <= 1: + different_alleles_satisfied = False + else: + different_alleles_satisfied = True + else: + different_alleles_satisfied = True + + return domain_satisfied and function_satisfied and source_satisfied and score_satisfied and different_alleles_satisfied + + def snp_density_map(self, query, results): + + canvas_width = 900 + canvas_height = 200 + snp_canvas = Image.new("RGBA", size=(canvas_width, canvas_height)) + left_offset, right_offset, top_offset, bottom_offset = (30, 30, 40, 50) + plot_width = canvas_width - left_offset - right_offset + plot_height = canvas_height - top_offset - bottom_offset + y_zero = top_offset + plot_height / 2 + + x_scale = plot_width / (self.end_mb - self.start_mb) + + # draw clickable image map at some point + n_click = 80.0 + click_step = plot_width / n_click + click_mb_step = (self.end_mb - self.start_mb) / n_click + + +def get_browser_sample_lists(species_id=1): + strain_lists = {} + mouse_strain_list = [] + rat_strain_list = [] + with database_connection(get_setting("SQL_URI")) as conn: + with conn.cursor() as cursor: + cursor.execute("SHOW COLUMNS FROM SnpPattern") + _mouse_snp_pattern = cursor.fetchall() + cursor.execute("SHOW COLUMNS FROM RatSnpPattern") + _rats_snp_pattern = cursor.fetchall() + for result in _mouse_snp_pattern[1:]: + mouse_strain_list.append(result[0]) + for result in _rats_snp_pattern[2:]: + rat_strain_list.append(result[0]) + strain_lists['mouse'] = mouse_strain_list + strain_lists['rat'] = rat_strain_list + return strain_lists + + +def get_header_list(variant_type, strains, species=None, empty_columns=None): + if species == "Mouse": + strain_list = strains['mouse'] + elif species == "Rat": + strain_list = strains['rat'] + else: + strain_list = strains + + empty_field_count = 0 # ZS: This is an awkward way of letting the javascript know the index where the allele value columns start; there's probably a better way of doing this + + header_fields = [] + header_data_names = [] + if variant_type == "SNP": + header_fields.append(['Index', 'SNP ID', 'Chr', 'Mb', 'Alleles', 'Source', 'ConScore', + 'Gene', 'Transcript', 'Exon', 'Domain 1', 'Domain 2', 'Function', 'Details']) + header_data_names = ['index', 'snp_name', 'chr', 'mb_formatted', 'alleles', 'snp_source', 'conservation_score', + 'gene_name', 'transcript', 'exon', 'domain_1', 'domain_2', 'function', 'function_details'] + + header_fields.append(strain_list) + header_data_names += strain_list + + if empty_columns != None: + if empty_columns['snp_source'] == "false": + empty_field_count += 1 + header_fields[0].remove('Source') + if empty_columns['conservation_score'] == "false": + empty_field_count += 1 + header_fields[0].remove('ConScore') + if empty_columns['gene_name'] == "false": + empty_field_count += 1 + header_fields[0].remove('Gene') + if empty_columns['transcript'] == "false": + empty_field_count += 1 + header_fields[0].remove('Transcript') + if empty_columns['exon'] == "false": + empty_field_count += 1 + header_fields[0].remove('Exon') + if empty_columns['domain_2'] == "false": + empty_field_count += 1 + header_fields[0].remove('Domain 2') + if empty_columns['function'] == "false": + empty_field_count += 1 + header_fields[0].remove('Function') + if empty_columns['function_details'] == "false": + empty_field_count += 1 + header_fields[0].remove('Details') + + for col in empty_columns.keys(): + if empty_columns[col] == "false": + header_data_names.remove(col) + + elif variant_type == "InDel": + header_fields = ['Index', 'ID', 'Type', 'InDel Chr', + 'Mb Start', 'Mb End', 'Strand', 'Size', 'Sequence', 'Source'] + header_data_names = ['index', 'indel_name', 'indel_type', 'indel_chr', 'indel_mb_s', + 'indel_mb_e', 'indel_strand', 'indel_size', 'indel_sequence', 'source_name'] + + return header_fields, empty_field_count, header_data_names + + +def get_effect_details_by_category(effect_name=None, effect_value=None): + gene_list = [] + transcript_list = [] + exon_list = [] + function_list = [] + function_detail_list = [] + tmp_list = [] + + gene_group_list = ['Upstream', 'Downstream', + 'Splice Site', 'Nonsplice Site', '3\' UTR'] + biotype_group_list = ['Unknown Effect In Exon', 'Start Gained', + 'Start Lost', 'Stop Gained', 'Stop Lost', 'Nonsynonymous', 'Synonymous'] + new_codon_group_list = ['Start Gained'] + codon_effect_group_list = [ + 'Start Lost', 'Stop Gained', 'Stop Lost', 'Nonsynonymous', 'Synonymous'] + + effect_detail_list = effect_value.strip().split('|') + effect_detail_list = [item.strip() for item in effect_detail_list] + + for index, item in enumerate(effect_detail_list): + item_list = item.strip().split(',') + item_list = [item.strip() for item in item_list] + + gene_id = item_list[0] + gene_name = item_list[1] + gene_list.append([gene_id, gene_name]) + transcript_list.append(item_list[2]) + + if effect_name not in gene_group_list: + exon_id = item_list[3] + exon_rank = item_list[4] + exon_list.append([exon_id, exon_rank]) + + if effect_name in biotype_group_list: + biotype = item_list[5] + function_list.append(effect_name) + + if effect_name in new_codon_group_list: + new_codon = item_list[6] + tmp_list = [biotype, new_codon] + function_detail_list.append(", ".join(tmp_list)) + elif effect_name in codon_effect_group_list: + old_new_AA = item_list[6] + old_new_codon = item_list[7] + codon_num = item_list[8] + tmp_list = [biotype, old_new_AA, old_new_codon, codon_num] + function_detail_list.append(", ".join(tmp_list)) + else: + function_detail_list.append(biotype) + + return [gene_list, transcript_list, exon_list, function_list, function_detail_list] + + +def get_effect_info(effect_list): + domain = "" + effect_detail_list = [] + effect_info_dict = {} + + prime3_utr, prime5_utr, upstream, downstream, intron, nonsplice_site, splice_site, intergenic = effect_list[ + :8] + exon, non_synonymous_coding, synonymous_coding, start_gained, start_lost, stop_gained, stop_lost, unknown_effect_in_exon = effect_list[ + 8:16] + + if intergenic: + domain = "Intergenic" + effect_info_dict[domain] = "" + else: + # if not exon, get gene list/transcript list info + if upstream: + domain = "Upstream" + effect_detail_list = get_effect_details_by_category( + effect_name='Upstream', effect_value=upstream) + effect_info_dict[domain] = effect_detail_list + if downstream: + domain = "Downstream" + effect_detail_list = get_effect_details_by_category( + effect_name='Downstream', effect_value=downstream) + effect_info_dict[domain] = effect_detail_list + if intron: + if splice_site: + domain = "Splice Site" + effect_detail_list = get_effect_details_by_category( + effect_name='Splice Site', effect_value=splice_site) + effect_info_dict[domain] = effect_detail_list + if nonsplice_site: + domain = "Nonsplice Site" + effect_detail_list = get_effect_details_by_category( + effect_name='Nonsplice Site', effect_value=nonsplice_site) + effect_info_dict[domain] = effect_detail_list + # get gene, transcript_list, and exon info + if prime3_utr: + domain = "3\' UTR" + effect_detail_list = get_effect_details_by_category( + effect_name='3\' UTR', effect_value=prime3_utr) + effect_info_dict[domain] = effect_detail_list + if prime5_utr: + domain = "5\' UTR" + effect_detail_list = get_effect_details_by_category( + effect_name='5\' UTR', effect_value=prime5_utr) + effect_info_dict[domain] = effect_detail_list + + if start_gained: + domain = "Start Gained" + effect_detail_list = get_effect_details_by_category( + effect_name='Start Gained', effect_value=start_gained) + effect_info_dict[domain] = effect_detail_list + if unknown_effect_in_exon: + domain = "Unknown Effect In Exon" + effect_detail_list = get_effect_details_by_category( + effect_name='Unknown Effect In Exon', effect_value=unknown_effect_in_exon) + effect_info_dict[domain] = effect_detail_list + if start_lost: + domain = "Start Lost" + effect_detail_list = get_effect_details_by_category( + effect_name='Start Lost', effect_value=start_lost) + effect_info_dict[domain] = effect_detail_list + if stop_gained: + domain = "Stop Gained" + effect_detail_list = get_effect_details_by_category( + effect_name='Stop Gained', effect_value=stop_gained) + effect_info_dict[domain] = effect_detail_list + if stop_lost: + domain = "Stop Lost" + effect_detail_list = get_effect_details_by_category( + effect_name='Stop Lost', effect_value=stop_lost) + effect_info_dict[domain] = effect_detail_list + + if non_synonymous_coding: + domain = "Nonsynonymous" + effect_detail_list = get_effect_details_by_category( + effect_name='Nonsynonymous', effect_value=non_synonymous_coding) + effect_info_dict[domain] = effect_detail_list + if synonymous_coding: + domain = "Synonymous" + effect_detail_list = get_effect_details_by_category( + effect_name='Synonymous', effect_value=synonymous_coding) + effect_info_dict[domain] = effect_detail_list + + return effect_info_dict + + +def get_gene_id(species_id, gene_name): + query = ("SELECT geneId FROM GeneList WHERE " + "SpeciesId = %s AND geneSymbol = %s") + + with database_connection(get_setting("SQL_URI")) as conn: + with conn.cursor() as cursor: + cursor.execute(query, (species_id, gene_name)) + if (result := cursor.fetchone()): + return result[0] + return "" + + +def get_gene_id_name_dict(species_id, gene_name_list): + gene_id_name_dict = {} + if len(gene_name_list) == 0: + return "" + query = ("SELECT geneId, geneSymbol FROM " + "GeneList WHERE SpeciesId = %s AND " + f"geneSymbol in ({', '.join(['%s'] * len(gene_name_list))})") + with database_connection(get_setting("SQL_URI")) as conn: + with conn.cursor() as cursor: + cursor.execute(query, (species_id, *gene_name_list)) + results = cursor.fetchall() + if results: + for item in results: + gene_id_name_dict[item[1]] = item[0] + return gene_id_name_dict + + +def check_if_in_gene(species_id, chr_, mb): + with database_connection(get_setting("SQL_URI")) as conn: + with conn.cursor() as cursor: + if species_id != 0: # ZS: Check if this is necessary + cursor.execute( + "SELECT geneId, geneSymbol " + "FROM GeneList WHERE " + "SpeciesId = %s AND chromosome = %s " + "AND (txStart < %s AND txEnd > %s)", + (species_id, chr_, mb, mb)) + else: + cursor.execute( + "SELECT geneId,geneSymbol " + "FROM GeneList WHERE " + "chromosome = %s AND " + "(txStart < %s AND txEnd > %s)", + (chr_, mb, mb)) + if (result := cursor.fetchone()): + return [result[0], result[1]] + return "" |