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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,6 @@ | ||
| mouse: | ||
| annotation: 'http://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_mouse/release_M27/gencode.vM27.primary_assembly.annotation.gtf.gz' | ||
| genome: 'http://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_mouse/release_M27/GRCm39.primary_assembly.genome.fa.gz' | ||
| human: | ||
| annotation: 'http://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_38/gencode.v38.primary_assembly.annotation.gtf.gz' | ||
| genome: 'http://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_38/GRCh38.primary_assembly.genome.fa.gz' |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,205 @@ | ||
| import pandas as pd | ||
| import os | ||
| import yaml | ||
| import math | ||
| import argparse | ||
|
|
||
| class ProjectDF: | ||
| # default values of the project dataframe columns | ||
| project_df_default_values = { | ||
| "puck_id": "no_optical_puck", | ||
| "sample_sheet": "none", | ||
| "species": "none", | ||
| "demux_barcode_mismatch": 1, | ||
| "demux_dir": "none", | ||
| "basecalls_dir": "none", | ||
| "R1": "none", | ||
| "R2": "none", | ||
| "investigator": "unknown", | ||
| "sequencing_date": "unknown", | ||
| "experiment": "unknown", | ||
| "puck_barcode_file": "none", | ||
| "run_mode": ["default"], | ||
| "barcode_flavor": "default", | ||
| "is_merged":False} | ||
|
|
||
| def __init__( | ||
| self, | ||
| file_path, | ||
| puck_data = { | ||
| 'barcode_file': 'barcode_file.csv', | ||
| 'root': 'puck_data' | ||
| } | ||
| ): | ||
| self.file_path = file_path | ||
|
|
||
| if os.path.isfile(file_path): | ||
| self.df = pd.read_csv(file_path, | ||
| index_col=['project_id', 'sample_id']) | ||
| else: | ||
| index = pd.MultiIndex( | ||
| names=['project_id', 'sample_id'], | ||
| levels=[[],[]], | ||
| codes=[[],[]]) | ||
| self.df = pd.DataFrame(columns = self.project_df_default_values.keys(), | ||
| index=index) | ||
|
|
||
| self.puck_data = puck_data | ||
|
|
||
| def __compute_max_barcode_mismatch(self, indices): | ||
| """computes the maximum number of mismatches allowed for demultiplexing based | ||
| on the indices present in the sample sheet.""" | ||
| num_samples = len(indices) | ||
|
|
||
| if num_samples == 1: | ||
| return 4 | ||
| else: | ||
| max_mismatch = 3 | ||
| for i in range(num_samples - 1): | ||
| for j in range(i + 1, num_samples): | ||
| hd = self.__hamming_distance(indices[i], indices[j]) | ||
| max_mismatch = min(max_mismatch, math.ceil(hd / 2) - 1) | ||
| return max_mismatch | ||
|
|
||
| def __hamming_distance(self, string1, string2): | ||
| return sum(c1 != c2 for c1, c2 in zip(string1, string2)) | ||
|
|
||
| def __find_barcode_file(self, puck_id): | ||
| # first find directory of puck file | ||
|
|
||
| # return none or the path of the file | ||
| def get_barcode_file(path): | ||
| if os.path.isfile(path): | ||
| return path | ||
|
|
||
| return "none" | ||
|
|
||
| def find_dir(name, path): | ||
| for root, dirs, files in os.walk(path): | ||
| if name in dirs: | ||
| return os.path.join(root, name) | ||
|
|
||
| puck_dir = find_dir(puck_id, self.puck_data['root']) | ||
| path = None | ||
|
|
||
| if puck_dir is not None: | ||
| # puck dir exists, look for barcode file pattern | ||
| path = os.path.join(puck_dir, self.puck_data["barcode_file"]) | ||
|
|
||
| return get_barcode_file(path) | ||
| else: | ||
| return self.project_df_default_values['puck_barcode_file'] | ||
|
|
||
| def dump(self): | ||
| self.df.to_csv(self.file_path) | ||
|
|
||
| def add_sample_sheet(self, sample_sheet_path, basecalls_dir): | ||
| with open(sample_sheet_path) as sample_sheet: | ||
| ix = 0 | ||
| investigator = "none" | ||
| sequencing_date = "none" | ||
|
|
||
| for line in sample_sheet: | ||
| line = line.strip("\n") | ||
| if "Investigator" in line: | ||
| investigator = line.split(",")[1] | ||
| if "Date" in line: | ||
| sequencing_date = line.split(",")[1] | ||
| if "[Data]" in line: | ||
| # the counter ix stops here | ||
| break | ||
| else: | ||
| ix = ix + 1 | ||
|
|
||
| # read everything after [Data] | ||
| df = pd.read_csv(sample_sheet_path, skiprows=ix + 1) | ||
| # rename columns | ||
| to_rename={ | ||
| "Sample_ID": "sample_id", | ||
| "Sample_Name": "puck_id", | ||
| "Sample_Project": "project_id", | ||
| "Description": "experiment", | ||
| "index": "index" | ||
| } | ||
| df.rename( | ||
| columns=to_rename, | ||
| inplace=True, | ||
| ) | ||
| # select only renamed columns | ||
| df = df[to_rename.values()] | ||
| df["species"] = df["experiment"].str.split("_").str[-1] | ||
| df["investigator"] = investigator | ||
| df["sequencing_date"] = sequencing_date | ||
|
|
||
| # rename columns | ||
| df["basecalls_dir"] = basecalls_dir | ||
| df["demux_barcode_mismatch"] = self.__compute_max_barcode_mismatch(df["index"]) | ||
| df["sample_sheet"] = sample_sheet_path | ||
| df["demux_dir"] = df["sample_sheet"].str.split("/").str[-1].str.split(".").str[0] | ||
| df["puck_barcode_file"] = df.puck_id.apply(self.__find_barcode_file) | ||
| df.set_index(['project_id', 'sample_id'], inplace=True) | ||
|
|
||
| for ix, row in df.iterrows(): | ||
| self.add_update_sample(ix[0], ix[1], **row.to_dict()) | ||
|
|
||
| def add_update_sample(self, project_id = None, sample_id = None, | ||
| **kwargs): | ||
| """ | ||
| adds or updates a sample with a given project_id and sample_id | ||
| """ | ||
| if project_id is None or sample_id is None: | ||
| print(f'you need to provide a sample_id and project_id in order to add a sample') | ||
| return 0 | ||
|
|
||
| ix = (project_id, sample_id) | ||
|
|
||
| if ix in self.df.index: | ||
| print(f'sample with {ix} already exists in ProjectDF') | ||
| print(f'updating') | ||
| self.df.loc[ix].update(pd.Series(kwargs)) | ||
| else: | ||
| new_project = pd.Series(self.project_df_default_values) | ||
| new_project.name = ix | ||
| new_project.update(kwargs) | ||
|
|
||
| self.df = self.df.append(new_project) | ||
|
|
||
| def project_df_from_yaml(self, projects_yaml_file): | ||
| config = yaml.load(open(projects_yaml_file), | ||
| Loader=yaml.FullLoader) | ||
| demux_projects = config.get('projects', None) | ||
|
|
||
| if demux_projects is not None: | ||
| # if we have projects in the config file | ||
| # get the samples | ||
| for ip in demux_projects: | ||
| self.add_sample_sheet(ip['sample_sheet'], ip['basecalls_dir']) | ||
|
|
||
| # add additional samples from config.yaml, which have already been demultiplexed. | ||
| for project in config['additional_projects']: | ||
| self.add_update_sample(**project) | ||
|
|
||
| #project_df = df_assign_merge_samples(project_df) | ||
|
|
||
| @staticmethod | ||
| def get_add_sample_sheet_parser(): | ||
| parser = argparse.ArgumentParser( | ||
| description = 'add a new sample sheet to the samples', | ||
| add_help=False) | ||
|
|
||
| parser.add_argument('--sample_sheet', type = str, | ||
| help = 'the path to the Illumina sample sheet', | ||
| required=True) | ||
| parser.add_argument('--basecalls_dir', type = str, | ||
| help = 'path to the basecalls directory', | ||
| required=True) | ||
|
|
||
| return parser | ||
|
|
||
| @classmethod | ||
| def add_sample_sheet_cmdline(cls, args): | ||
| pdf = cls(args['sample_df_file']) | ||
| pdf.add_sample_sheet(args['sample_sheet'], | ||
| args['basecalls_dir']) | ||
|
|
||
| pdf.dump() |
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