Пример #1
0
def link_genes(
    ensembl_lines,
    hgnc_lines,
    exac_lines,
    hpo_lines,
    mim2gene_lines=None,
    genemap_lines=None,
):
    """Gather information from different sources and return a gene dict

    Extract information collected from a number of sources and combine them
    into a gene dict with HGNC symbols as keys.

    hgnc_id works as the primary symbol and it is from this source we gather
    as much information as possible (hgnc_complete_set.txt)

    Coordinates are gathered from ensemble and the entries are linked from hgnc
    to ensembl via ENSGID.

    From exac the gene intolerance scores are collected, genes are linked to hgnc
    via hgnc symbol. This is a unstable symbol since they often change.


        Args:
            ensembl_lines(iterable(str)): Strings with ensembl gene information
            hgnc_lines(iterable(str)): Strings with hgnc gene information
            exac_lines(iterable(str)): Strings with exac PLi score info
            mim2gene_lines(iterable(str))
            genemap_lines(iterable(str))
            hpo_lines(iterable(str)): Strings with hpo gene information

        Yields:
            gene(dict): A dictionary with gene information
    """
    genes = {}
    LOG.info("Linking genes")
    # HGNC genes are the main source, these define the gene dataset to use
    # Try to use as much information as possible from hgnc
    for hgnc_gene in parse_hgnc_genes(hgnc_lines):
        hgnc_id = hgnc_gene["hgnc_id"]
        genes[hgnc_id] = hgnc_gene

    add_ensembl_info(genes, ensembl_lines)

    symbol_to_id = genes_by_alias(genes)

    add_exac_info(genes, symbol_to_id, exac_lines)

    add_incomplete_penetrance(genes, symbol_to_id, hpo_lines)

    if mim2gene_lines and genemap_lines:
        add_omim_info(genes, symbol_to_id, genemap_lines, mim2gene_lines)

    return genes
Пример #2
0
def link_genes(ensembl_lines, hgnc_lines, exac_lines, mim2gene_lines,
               genemap_lines, hpo_lines):
    """Gather information from different sources and return a gene dict

    Extract information collected from a number of sources and combine them
    into a gene dict with HGNC symbols as keys.

    hgnc_id works as the primary symbol and it is from this source we gather
    as much information as possible (hgnc_complete_set.txt)

    Coordinates are gathered from ensemble and the entries are linked from hgnc
    to ensembl via ENSGID.

    From exac the gene intolerance scores are collected, genes are linked to hgnc
    via hgnc symbol. This is a unstable symbol since they often change.


        Args:
            ensembl_lines(iterable(str)): Strings with ensembl gene information
            hgnc_lines(iterable(str)): Strings with hgnc gene information
            exac_lines(iterable(str)): Strings with exac PLi score info
            mim2gene_lines(iterable(str))
            genemap_lines(iterable(str))
            hpo_lines(iterable(str)): Strings with hpo gene information

        Yields:
            gene(dict): A dictionary with gene information
    """
    genes = {}
    LOG.info("Linking genes")
    # HGNC genes are the main source, these define the gene dataset to use
    # Try to use as much information as possible from hgnc
    for hgnc_gene in parse_hgnc_genes(hgnc_lines):
        hgnc_id = hgnc_gene['hgnc_id']
        genes[hgnc_id] = hgnc_gene

    add_ensembl_info(genes, ensembl_lines)

    symbol_to_id = genes_by_alias(genes)

    add_exac_info(genes, symbol_to_id, exac_lines)

    add_omim_info(genes, symbol_to_id, genemap_lines, mim2gene_lines)

    add_incomplete_penetrance(genes, symbol_to_id, hpo_lines)

    return genes
Пример #3
0
def link_genes(ensembl_lines, hgnc_lines, exac_lines, mim2gene_lines,
               genemap_lines, hpo_lines):
    """Gather information from different sources and return a gene dict

    Extract information collected from a number of sources and combine them
    into a gene dict with HGNC symbols as keys.

    hgnc_id works as the primary symbol and it is from this source we gather
    as much information as possible (hgnc_complete_set.txt)

    Coordinates are gathered from ensemble and the entries are linked from hgnc
    to ensembl via ENSGID.

    From exac the gene intolerance scores are collected, genes are linked to hgnc
    via hgnc symbol. This is a unstable symbol since they often change.


        Args:
            ensembl_lines(iterable(str))
            hgnc_lines(iterable(str))
            exac_lines(iterable(str))

        Yields:
            gene(dict): A dictionary with gene information
    """
    genes = {}
    log.info("Linking genes and transcripts")
    # HGNC genes are the main source, these define the gene dataset to use
    # Try to use as much information as possible from hgnc
    for hgnc_gene in parse_hgnc_genes(hgnc_lines):
        hgnc_id = hgnc_gene['hgnc_id']
        hgnc_gene['transcripts'] = []
        genes[hgnc_id] = hgnc_gene

    symbol_to_id = genes_by_alias(genes)
    # Parse and add the ensembl gene info
    all_genes = {'ensembl': {}, 'symbol': {}}
    for transcript in parse_ensembl_transcripts(ensembl_lines):
        ensg_symbol = transcript['hgnc_symbol']
        ensgid = transcript['ensembl_gene_id']
        for id_type, gene_id in [('symbol', ensg_symbol), ('ensembl', ensgid)]:
            if gene_id in all_genes[id_type]:
                all_genes[id_type][gene_id].append(transcript)
            else:
                all_genes[id_type][gene_id] = [transcript]

    log.info("Add ensembl info")
    # Add gene coordinates and transcript info for hgnc genes:
    for gene_info in genes.values():
        ensgid = gene_info['ensembl_gene_id']
        ensg_symbol = gene_info['hgnc_symbol']

        for id_type, gene_id in [('ensembl', ensgid), ('symbol', ensg_symbol)]:
            if gene_id:
                if gene_id in all_genes[id_type]:
                    add_ensembl_info(gene_info, all_genes[id_type][gene_id])
                    ensgid = 'ADDED'
                    break

    log.info("Add exac pli scores")
    for exac_gene in parse_exac_genes(exac_lines):
        hgnc_symbol = exac_gene['hgnc_symbol'].upper()
        pli_score = exac_gene['pli_score']

        if hgnc_symbol in symbol_to_id:
            hgnc_id_info = symbol_to_id[hgnc_symbol]

            # If we have the true id we know ot os correct
            if hgnc_id_info['true_id']:
                hgnc_id = hgnc_id_info['true_id']
                genes[hgnc_id]['pli_score'] = pli_score

            # Otherwise we loop over the ids and add pli score if it
            # is not already added
            else:
                for hgnc_id in hgnc_id_info['ids']:
                    gene_info = genes[hgnc_id]
                    if not gene_info.get('pli_score'):
                        gene_info['pli_score'] = pli_score

    log.info("Add omim info")
    omim_genes = get_mim_genes(genemap_lines, mim2gene_lines)
    for hgnc_symbol in omim_genes:
        omim_info = omim_genes[hgnc_symbol]
        inheritance = omim_info.get('inheritance', set())
        if hgnc_symbol in symbol_to_id:
            hgnc_id_info = symbol_to_id[hgnc_symbol]

            # If we have the true id we know it is correct
            if hgnc_id_info['true_id']:
                hgnc_id = hgnc_id_info['true_id']
                gene_info = genes[hgnc_id]

                # Update the omim id to the one found in omim
                gene_info['omim_id'] = omim_info['mim_number']

                gene_info['inheritance_models'] = list(inheritance)
                gene_info['phenotypes'] = omim_info.get('phenotypes', [])
            else:
                for hgnc_id in hgnc_id_info['ids']:
                    gene_info = genes[hgnc_id]
                    if not gene_info.get('omim_id'):
                        gene_info['omim_id'] = omim_info['mim_number']
                    if not gene_info.get('inheritance_models'):
                        gene_info['inheritance_models'] = list(inheritance)
                    if not gene_info.get('phenotypes'):
                        gene_info['phenotypes'] = omim_info.get('phenotypes', [])

    log.info("Add incomplete penetrance info")
    for hgnc_symbol in get_incomplete_penetrance_genes(hpo_lines):
        if hgnc_symbol in symbol_to_id:
            hgnc_id_info = symbol_to_id[hgnc_symbol]

            # If we have the true id we know ot os correct
            if hgnc_id_info['true_id']:
                hgnc_id = hgnc_id_info['true_id']
                genes[hgnc_id]['incomplete_penetrance'] = True

            # Otherwise we loop over the ids and add incomplete penetrance if it
            # is not already added
            else:
                for hgnc_id in hgnc_id_info['ids']:
                    gene_info = genes[hgnc_id]
                    if not 'incomplete_penetrance' in gene_info:
                        gene_info['incomplete_penetrance'] = True

    return genes
Пример #4
0
def test_parse_hgnc_genes(hgnc_handle):
    """Test to parse the hgnc genes"""
    genes = parse_hgnc_genes(lines=hgnc_handle)
    for gene in genes:
        if gene:
            assert gene['hgnc_id']
Пример #5
0
def hgnc_genes(request, hgnc_handle):
    """Get a dictionary with hgnc genes"""
    print('')
    return parse_hgnc_genes(hgnc_handle)
Пример #6
0
def test_parse_hgnc_genes(hgnc_handle):
    """Test to parse the hgnc genes"""
    genes = parse_hgnc_genes(lines=hgnc_handle)
    for gene in genes:
        if gene:
            assert gene['hgnc_id']