Aggregate annotations per alignment to annotations per query.
    step#10

    :param cfg: configuration dict

def dalignbedannot2daggbyquery(cfg):
    """
    Aggregate annotations per alignment to annotations per query.
    step#10

    :param cfg: configuration dict
    """
    datatmpd=cfg['datatmpd']

    dalignbedannot=del_Unnamed(pd.read_csv(cfg['dalignbedannotp'],sep='\t',low_memory=False))
    
    daggbyqueryp=f'{datatmpd}/10_daggbyquery.tsv'      
    logging.info(basename(daggbyqueryp))
    if not exists(daggbyqueryp) or cfg['force']:
        dalignbedannot=dfliststr2dflist(dalignbedannot,
                                ['type', 'gene name', 'gene id', 'transcript id', 'protein id', 'exon id'],
                                colfmt='tuple')    
        dalignbedannot['alternate alignments count']=1
        import itertools
        from rohan.dandage.io_sets import unique
        def unique_dropna(l): return unique(l,drop='nan')
        def merge_unique_dropna(l): return unique(list(itertools.chain(*l)),drop='nan')
        cols2aggf={'id':unique_dropna,
         'type':merge_unique_dropna,
         'gene name':merge_unique_dropna,
         'gene id':merge_unique_dropna,
         'transcript id':merge_unique_dropna,
         'protein id':merge_unique_dropna,
         'exon id':merge_unique_dropna,
         'region':unique_dropna,
         'alternate alignments count':sum,
        }
        daggbyquery=dalignbedannot.groupby('query id').agg(cols2aggf)
        daggbyquery.to_csv(daggbyqueryp,sep='\t')
        daggbyquery.to_csv(cfg['dalignannotedp'],sep='\t')
    return cfg