biobricks_assembly.biobricks10.bbinput

biobricks

biobricks(output_folder: str, construct_path: List[str], part_path: List[str], thermocycle: bool = True, p10_mount: str = 'right', p300_mount: str = 'left', p10_type: str = 'p10_single', p300_type: str = 'p300_single', well_plate: str = 'biorad_96_wellplate_200ul_pcr', tube_rack: str = 'opentrons_24_tuberack_nest_1.5ml_snapcap', soc_plate: str = 'usascientific_96_wellplate_2.4ml_deep', transformation_plate: str = 'corning_96_wellplate_360ul_flat') -> List[str]

Main function, creates scripts and metainformation Can take specific args or just **labware_dict for all labware

Arguments:

  • output_folder - the full file path of the intended output folder for files generated
  • construct_path - a one element list with the full path of the construct csv
  • part_path - a list of full paths to part csv(s) (one or more)
  • thermocyle - True or False, indicating whether the user has and would like to use the Opentrons Thermocycler see labware_dict for rest of arguments

Returns:

List of output paths If there is an exception, the list of output paths will contain only one element = the error path Otherwise the list of output paths will contain: OT-2 script paths (assembly, transformation), metainformation

get_constructs

get_constructs(path: str) -> Tuple[pd.DataFrame, List[str]]

Returns construct dataframe from constructs csv Args: path = path of construct csv

Returns:

  • merged_constructs_list - dataframe of constructs
  • dest_well_list - list of wells in construct plate that are used

process_construct

process_construct(construct_entry: List) -> Dict[str, List[str]]

Returns construct dictionary from row in csv file Used in get_constructs() Args: construct_entry = construct row from csv in list Returns: Dictionary of construct info

get_parts

get_parts(paths: List[str], constructs_list: pd.DataFrame) -> pd.DataFrame

Returns a dataframe of parts from part csv file. Uses constructs_list to record the number of times the part is used in the constructs and the roles it plays.

Arguments:

  • paths - list of paths to part csvs
  • constructs_list - dataframe of constructs

Returns:

  • merged_parts_list - dataframe of parts

process_part

process_part(part: List, constructs_list: pd.DataFrame, plate: str) -> Dict[str, List]

Returns a part dataframe with detailed information. Used in get_parts()

Arguments:

  • part - row of part csv file
  • constructs_list - constructs dataframe
  • plate - source plate of part

Returns:

Dataframe of individual part

get_reagents_wells

get_reagents_wells(constructs_list: pd.DataFrame, parts: pd.DataFrame) -> Tuple[pd.DataFrame, List[str], pd.DataFrame]

Arguments:

  • constructs_list - dataframe of constructs
  • parts - dataframe of parts

Returns:

Dataframe with rows as reagent names and cols as the reagent well and the volume of the reagent required. List of wells used for reagents in reagents tube rack Master mix dataframe giving volumes of each reagent

get_digests

get_digests(constructs_list: pd.DataFrame, parts: pd.DataFrame, reagents: pd.DataFrame) -> Tuple[pd.DataFrame, pd.DataFrame]

Creates a dataframe of digests, the intermediate step in assembly BioBricks constructs.

Arguments:

  • constructs_list - dataframe of constructs
  • parts - dataframe of parts
  • reagents - dataframe of reagents

Returns:

dataframe of digests updated parts dataframe with digest well column

next_well

next_well(wells_used: List[str]) -> str

Finds the next available well from a list of used wells for a 96 well plate

Arguments:

List of wells used in 96 well plate

Returns:

Next unused well in 96 well plate

next_well_reagent

next_well_reagent(wells_used: List[str]) -> str

Finds the next available well from a list of used wells for a 24 well plate/tube rack

Arguments:

List of wells used in 24 well plate/tube rack

Returns:

Next unused well in 24 well plate/tube rack

count_part_occurences

count_part_occurences(constructs_list: pd.DataFrame, part: List) -> Tuple[List[int], List[List[int]]]

Counts the number of times a part is used in the constructs. Differentiates between upstream uses, downstream uses, and plasmid uses: all require different digests.

Arguments:

  • constructs_list - dataframe of constructs
  • part - row in part csv file as list

Returns:

  • counts - list where 0th element = upstream counts, 1st element = downstream counts, 2nd element = plasmid counts
  • constructs_in_upstream - index of constructs a part appears in as the upstream part
  • constructs_in_downstream - index of constructs a part appears in as the downstream part
  • constructs_in_plasmid - index of constructs a part appears in as the plasmid part

create_assembly_dicts

create_assembly_dicts(constructs: pd.DataFrame, parts: pd.DataFrame, digests: pd.DataFrame, reagents: pd.DataFrame) -> Tuple[Dict, Dict, Dict, Dict, Dict]

Returns assembly dictionaries to be used in the assembly protocol, instructing which transfers need to be made.

Arguments:

  • constructs - dataframe of constructs
  • parts - dataframe of parts
  • digests - dataframe of digests
  • reagents - dataframe of reagents

Returns:

  • source_to_digest - dictionary with key = source (part) well, key = list of tuples in format (digest well, volume to transfer)
  • reagent_to_digest - dictionary with key = reagent well, key = list of tuples in format (digest well, volume to transfer)
  • digest_to_construct - dictionary with key = digest well, key = list of tuples in format (construct well, volume to transfer)
  • reagent_to_construct - dictionary with key = reagent well, key = list of tuples in format (construct well, volume to transfer)
  • reagents_dict - dictionary with key = reagent name, key = reagent well

create_tranformation_dicts

create_tranformation_dicts(constructs: pd.DataFrame, water_well: str = 'A1', controls_per_cons: bool = False) -> Tuple[Dict[str, List[Tuple[str, int]]], Dict[str, List[Tuple[str, int]]],
Dict[str, List[Tuple[str, int]]], Dict[str, List[Tuple[str, int]]],
pd.DataFrame]

Creates transformation dictionaries to be used in the transformation protocol, instructing which transfers need to be made. Creates transform_df for metainformation Competent wells + construct wells -> same well for transformation. Control wells + water well -> same well for transformation.

Arguments:

  • Constructs - dataframe of constructs
  • water_well - well that water is stored in
  • controls_per_cons - create three controls per construct if True create three controls total if False

Returns:

  • competent_source_to_dest - dictionary with key = competent cell well, value = tuple of destination well + transfer vol
  • control_source_to_dest - dictionary with key = control cell well, value = tuple of destination well + transfer vol
  • assembly_source_to_dest - dictionary with key = construct well, value = tuple of destination well + transfer vol,
  • water_source_to_dest - dictionary with key = water well, value = tuple of destination well + transfer vol
  • transform_df - dataframe of transformation reactions

create_assembly_protocol

create_assembly_protocol(template_path: str, output_path: str, source_to_digest: Dict[str, List[Tuple[str, int]]], reagent_to_digest: Dict[str, List[Tuple[str, int]]], digest_to_construct: Dict[str, List[Tuple[str, int]]], reagent_to_construct: Dict[str, List[Tuple[str, int]]], reagents_dict: Dict[str, str], p10_mount: str, p10_type: str, well_plate_type: str, tube_rack_type: str, thermocycle: bool) -> str

Generates the assembly protocol used by opentrons. Returns the path of the assembly script.

Arguments:

  • template_path - absolute path of the Opentrons script template
  • output_path - absolute path of the output folder to save protocol in
  • source_to_digest - dictionary of form Dict[str, List[Tuple(str, int)]], dictionary key (string) gives source (part) well to transfer from, the 0th element of each tuple gives well to transfer to (digest well in this case), with the 1st element of the tuple giving the volume to transfer.
  • reagent_to_digest - dictionary of same form as source_to_digest (Dict[str, List[Tuple(str, int)]]), instructing transfers from reagent wells to digest wells
  • digest_to_storage - dictionary of same form as source_to_digest (Dict[str, List[Tuple(str, int)]]), instructing transfers from digest wells to storage wells (wells where digest not used in construct is stored after assembly)
  • digest_to_construct - dictionary of same form as source_to_digest (Dict[str, List[Tuple(str, int)]]), instructing transfers from digest wells to construct wells
  • reagent_to_construct - dictionary of same form as source_to_digest (Dict[str, List[Tuple(str, int)]]), instructing transfers from reagent wells to construct wells
  • p10_mount - "left" or "right", the Opentrons pipette mount options
  • p10_type - the name of the p10 pipette, e.g. "p10_single"
  • well_plate_type - the name of the well plate type used as the source plate and construct plate
  • tube_rack_type - the name of the tube rack type used for holding the reagents
  • thermocycle - True or False, True = run thermocycle module in scripts, False = use benchtop thermocycler

Returns:

path of assembly protocol script

create_transformation_protocol

create_transformation_protocol(template_path: str, output_path: str, competent_source_to_dest: Dict[str, List], control_source_to_dest: Dict[str, List], assembly_source_to_dest: Dict[str, List], water_source_to_dest: Dict[str, List], p10_mount: str, p300_mount: str, p10_type: str, p300_type: str, well_plate_type: str, transformation_plate_type: str, tube_rack_type: str, soc_plate_type: str) -> str

Generates the transformation protocol used by opentrons.

Arguments:

  • template_path - absolute path of the Opentrons script template
  • output_path - absolute path of the output folder to save protocol in
  • competent_source_to_digest - dictionary of form Dict[str, List[Tuple(str, int)]], dictionary key (string) gives competent cell well to transfer from, the 0th element of each tuple gives well to transfer to (transformation well), with the 1st element of the tuple giving the volume to transfer.
  • control_source_to_digest - dictionary of same form as competent_source_to_digest (Dict[str, List[Tuple(str, int)]]), instructing transfers from control wells to transformation wells
  • assembly_source_to_digest - dictionary of same form as competent_source_to_digest (Dict[str, List[Tuple(str, int)]]), instructing transfers from construct wells to transformation wells
  • water_source_to_digest - dictionary of same form as competent_source_to_digest (Dict[str, List[Tuple(str, int)]]), instructing transfers from water well to transformation wells
  • p10_mount - "left" or "right", the Opentrons pipette mount options
  • p300_mount - "left" or "right", the Opentrons pipette mount options
  • p10_type - the name of the p10 pipette, e.g. "p10_single"
  • p300_type - the name of the p300 pipette, e.g. "p300_single"
  • well_plate_type - the name of the well plate type used as the construct plate
  • transformation_plate_type - the name of the well plate type used as the transformation plate
  • tube_rack_type - the name of the tube rack type used to store cells
  • soc_plate_type - the name of the plate type used to store soc

Returns:

path of transform protocol script

dfs_to_csv

dfs_to_csv(path, index=True, **kw_dfs)

Generates a csv file defined by path, where kw_dfs are written one after another with each key acting as a title. If index=True, df indexes are written to the csv file.

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