Pgen

Author: d | 2025-04-23

PGEN is an old Sega Genesis/Megadrive emulator for the PS2 based on Generator source code. - pgen/readme.txt at master ps2homebrew/pgen ECS Protector Nitrogen Generator PGEN-30 (PGEN-30E) June 2025 -Rev 5 Engineered Corrosion Solutions Lackland Road St. Louis, MO Phone www.ecscorrosion.com General Description Ordering Information Stock Number: PGEN-30 (PGEN-30E) Replacement Filters: PGEN-FKS - Annual Maintenance

PGEN - Stock Quotes for PGEN Ent Holdg, NASDAQ: PGEN

Of the script demands the overhead of processing a model. To compute the pgens of many sequences, it is suggested to read the sequences in from a file and use either mode 2 or 3.It is also possible to condition the Pgen computation on V and J identity by specifying the V or J usages as a mask. However, note that these V/J masks will be applied to ALL of the sequences provided as arguments. Read Options on v_mask and j_mask for more info.Example calls:Compute the pgen of an amino acid CDR3 sequence$ olga-compute_pgen --humanTRB CASSTGQANYGYTFPgen of the amino acid sequence CASSTGQANYGYTF: 5.26507446955e-08Compute the pgen of an in-frame nucleotide sequence and the amino acid sequence it translates to.$ olga-compute_pgen --humanTRB TGTGCCAGCAGTGACGCACAGGGGCGTAATCGTGGGACTGAAGCTTTCTTTPgen of the nucleotide sequence TGTGCCAGCAGTGACGCACAGGGGCGTAATCGTGGGACTGAAGCTTTCTTT: 1.31873701121e-17Pgen of the amino acid sequence nt2aa(TGTGCCAGCAGTGACGCACAGGGGCGTAATCGTGGGACTGAAGCTTTCTTT) = CASSDAQGRNRGTEAFF: 4.70599549953e-13Compute the pgen of a regular expression template of CDR3 amino acid sequences. Note, for a regular expression sequence, provided as an argument, backslashes may be needed to specify the characters {} for the sequence to be read in properly.$ olga-compute_pgen --humanTRB CASSTGX\{1,5\}QAN[YA]GYTFPgen of the regular expression sequence CASSTGX{1,5}QAN[YA]GYTF: 7.588241802e-08Compute the pgens of all three sequences.$ olga-compute_pgen --humanTRB CASSTGQANYGYTF CASSTGX\{1,5\}QAN[YA]GYTF TGTGCCAGCAGTGACGCACAGGGGCGTAATCGTGGGACTGAAGCTTTCTTTPgen of the amino acid sequence CASSTGQANYGYTF: 5.26507446955e-08Pgen of the regular expression sequence CASSTGX{1,5}QAN[YA]GYTF: 7.588241802e-08Pgen of the nucleotide sequence TGTGCCAGCAGTGACGCACAGGGGCGTAATCGTGGGACTGAAGCTTTCTTT: 1.31873701121e-17Pgen of the amino acid sequence nt2aa(TGTGCCAGCAGTGACGCACAGGGGCGTAATCGTGGGACTGAAGCTTTCTTT) = CASSDAQGRNRGTEAFF: 4.70599549953e-13Specify a comma delimited V or J mask to condition the pgen computation on V and/or J gene usage.$ olga-compute_pgen --humanTRB CASSTGQANYGYTF --v_mask TRBV2,TRBV14 --j_mask TRBJ1-2Pgen of the amino acid sequence CASSTGQANYGYTF: 1.39165562898e-09It is also possible to restrict the Pgen computation to specified V and/or J genes or alleles (to reflect any alignment outside of the CDR3 region) by using the options -v or -j (see example below). You can specify multiple V or J genes/alleles by using a comma as a delimiter.The only required inputs are the sequence and specifying the generative V(D)J model. Additional options can be found by using -h.Modes 2/3):These read in sequences from a file. The script has only minimal file parsing built in, so reading in sequences from a file

GitHub - ps2homebrew/pgen: PGEN is an old Sega

Requires the file to be structured with delimiter spaced values (i.e. the data is organized in columns separated by delimiter like a .tsv or .csv file). Read Options on delimiter for more info.To read in sequences, the index of column of CDR3 sequences is needed. The default is to assume that the sequences to be read in are in the first column (index 0), meaning that a text file with only a sequence on each line will be read in okay by default. Read Options on seq_in for more info.It is not recommended to read in regular expression sequences from a file. These sequences require enumerating out the amino acid sequences which correspond to them and computing pgen for each of them individually -- this can require a large time cost. Instead consider defining a custom 'amino acid' alphabet to define the symbols used in the regular expressions if possible. Furthermore, BE CAREFUL if reading in from a .csv file -- if commas are used in a regex sequence and comma is used as the delimiter of the .csv file, the sequence will not be read in properly.If nucleotide sequences are to be read in it is possible to specify if theoutput should be the nucleotide sequence Pgen and/or the translated amino acid sequence Pgen (the default is to compute and output both). See Options.It is also possible to condition the Pgen computation on V and J identity by specifying what index the column that V and J masks are stored for each line.Mode 2 does not have a specified output file and so will print the sequences and their pgens to stdout.Mode 3 does have a specified output file. By default in this mode there is a running display of the last few sequences/pgens written to the output file as well as time elapsed, current rate of computation, and estimated time remaining. This display can be disabled (see Options).As it is rare for datasets to have >> 1e4 unique sequences, parallelization is not built in to compute_pgen. However, there are options to skip N lines of the file and

pgen/readme.txt at master ps2homebrew/pgen - GitHub

COMMENT_DELIMITERcharacter or string to indicate comment or header lines to skip.generate_sequences.py (olga-generate_sequences)This program will generate a file of Monte Carlo sampling from a specified generative V(D)J model. The sequences generated will have NO ERRORS.It is required to specify the number of sequences to be generated. This is done with -n (see Options).If a file is specified to write to (using -o, see Options), the generated sequences are written to the file, otherwise they are printed to stdout.The default is to record both the nucleotide CDR3 sequence and the amino acid CDR3 sequence. This can be specified (see Options).The V/J genes used to generate each sequence can be recorded or not. Default is to record them, but this can be toggled off with --record_genes_off (see Options).Full options can be printed by: $ olga-generate_sequences -hExample calls:Print 20 generated sequences to stdout$ olga-generate_sequences --humanTRB -n 20Write 200 generated sequences to example_seqs.tsv$ olga-generate_sequences --humanTRB -o example_seqs.tsv -n 200Write 20,000 generated sequences to example_seqs.tsv$ olga-generate_sequences --humanTRB -o example_seqs.tsv -n 2e4Write only the amino acid sequences$ olga-generate_sequences --humanTRB -o example_seqs.tsv -n 200 --seq_type amino_acidSelected OptionsDescription-h, --helpshow full Options list and exit-o PATH/TO/FILEwrite CDR3 sequences to PATH/TO/FILE-n Nspecify the number of sequences to generate.--seed SEEDset seed for pseudorandom number generator. Default is to not set a seed.--seq_type SEQ_TYPEdeclare sequence type for output sequences. Choices: 'all' [default], 'ntseq', 'aaseq'--time_updates_offturn time updates off.--record_genes_offturn off recording V and J gene info.-d DELIMITERdeclare delimiter choice. Default is tab for .tsv output files, comma for .csv files, and tab for all others. Choices: 'tab', 'space', ',', ';', ':'--raw_delimiter DELIMITERdeclare delimiter choice as a raw string.Using the OLGA modules in a Python script (advanced users)In order to incorporate the core algorithm into an analysis pipeline (or to write your own script wrappers) all that is needed is to import the modules and load up a generative model. Each module defines some classes that only a few methods get called on.As the generative model structure is different between VDJ recombination and VJ recombination the algorithms to compute Pgen for the two are different. For this reason, different objects are defined for VDJ recombination models. PGEN is an old Sega Genesis/Megadrive emulator for the PS2 based on Generator source code. - pgen/readme.txt at master ps2homebrew/pgen

GitHub - ps2homebrew/pgen: PGEN is an old Sega Genesis

And VJ recombination models, however the methods that get called are the same.The modules are:Module nameClassesload_model.pyGenomicDataVDJ, GenomicDataVJ, GenerativeModelVDJ, GenerativeModelVJpreprocess_generative_model_and_data.pyPreprocessedParametersVDJ, PreProcessedParametersVJgeneration_probability.pyGenerationProbabilityVDJ, GenerationProbabilityVJsequence_generation.pySequenceGenerationVDJ, SequenceGenerationVJutils.pyN/A (contains util functions)The classes with methods that are of interest will be GenerationProbabilityV(D)J (to compute Pgens) and SequenceGenerationV(D)J (to generate sequences).There is a fair amount of parameter processing that must go on to call these methods, however this is generally all done by instantiating a particular class. An exception to this rule are the classes GenerativeModelV(D)J and GenomicDataV(D)J. Normally the genomic data and model parameters are read in from IGoR inference files (and prepared V and J anchor files that have been prepared), however this is not mandated in order to make it easier for people to adapt the code to read in models/genomic data from other sources.Instantiating GenerativeModelV(D)J and GenomicDataV(D)J leaves the attributes as dummies, and calling the methods load_and_process_igor_model and load_igor_genomic_data will load up IGoR files.If you want to load models/data from other sources, you will need to write your own methods to set the attributes in GenerativeModelV(D)J and GenomicDataV(D)J. Please see the documentation of load_model.py for more details.Here is an example of loading the default human TRB model to compute some sequence Pgens and to generate some random CDR3 sequences:>> import olga.load_model as load_model>>> import olga.generation_probability as pgen>>> import olga.sequence_generation as seq_gen>>>>>> #Define the files for loading in generative model/data... params_file_name = 'default_models/human_T_beta/model_params.txt'>>> marginals_file_name = 'default_models/human_T_beta/model_marginals.txt'>>> V_anchor_pos_file ='default_models/human_T_beta/V_gene_CDR3_anchors.csv'>>> J_anchor_pos_file = 'default_models/human_T_beta/J_gene_CDR3_anchors.csv'>>>>>> #Load data... genomic_data = load_model.GenomicDataVDJ()>>> genomic_data.load_igor_genomic_data(params_file_name, V_anchor_pos_file, J_anchor_pos_file)>>> #Load model... generative_model = load_model.GenerativeModelVDJ()>>> generative_model.load_and_process_igor_model(marginals_file_name)>>>>>> #Process model/data for pgen computation by instantiating GenerationProbabilityVDJ... pgen_model = pgen.GenerationProbabilityVDJ(generative_model, genomic_data)>>>>>> #Compute some sequence pgens... pgen_model.compute_regex_CDR3_template_pgen('CASSAX{0,5}SARPEQFF')6.846877804096558e-10>>> pgen_model.compute_aa_CDR3_pgen('CAWSVAPDRGGYTF', 'TRBV30*01', 'TRBJ1-2*01')1.203646865765782e-10>>> pgen_model.compute_nt_CDR3_pgen('TGTGCCAGTAGTATAACAACCCAGGGCTTGTACGAGCAGTACTTC')3.9945642868171824e-14>>>>>>>>> #Process model/data for sequence generation by instantiating SequenceGenerationVDJ... seq_gen_model = seq_gen.SequenceGenerationVDJ(generative_model, genomic_data)>>>>>> #Generate some random sequences... seq_gen_model.gen_rnd_prod_CDR3()('TGTGCCAGCAGTGAAAAAAGGCAATGGGAAAGCGGGGAGCTGTTTTTT', 'CASSEKRQWESGELFF', 27, 8)>>> seq_gen_model.gen_rnd_prod_CDR3()('TGTGCCAGCAGTTTAGTGGGAAGGGCGGGGCCCTATGGCTACACCTTC', 'CASSLVGRAGPYGYTF', 14, 1)>>> seq_gen_model.gen_rnd_prod_CDR3()('TGTGCCAGCTGGACAGGGGGCAACTACGAGCAGTACTTC', 'CASWTGGNYEQYF', 55, 13)">>>> import olga.load_model as load_model>>> import olga.generation_probability as pgen>>> import olga.sequence_generation as seq_gen>>>>>> #Define the files for loading in generative model/data... params_file_name = 'default_models/human_T_beta/model_params.txt'>>> marginals_file_name = 'default_models/human_T_beta/model_marginals.txt'>>> V_anchor_pos_file ='default_models/human_T_beta/V_gene_CDR3_anchors.csv'>>> J_anchor_pos_file = 'default_models/human_T_beta/J_gene_CDR3_anchors.csv'>>>>>> #Load data... genomic_data = load_model.GenomicDataVDJ()>>> genomic_data.load_igor_genomic_data(params_file_name, V_anchor_pos_file, J_anchor_pos_file)>>> #Load model... generative_model = load_model.GenerativeModelVDJ()>>> generative_model.load_and_process_igor_model(marginals_file_name)>>>>>> #Process model/data for pgen computation by

ECS Protector Nitrogen Generator PGEN 30 (PGEN 30E)

To load at most M sequences so, if wanted, one could build a parallelized wrapper around this script (though it would be recommended to instead just import the modules and build from there).Example calls (assuming a file example_seqs.tsv with the line structurentseq aaseq V_mask J_mask):Read in the ntseqs and print the ntseq, aaseq = nt2aa(ntseq) and their pgens to stdout$ olga-compute_pgen -i example_seqs.tsv --humanTRBOnly read in the first 10 sequences$ olga-compute_pgen -i example_seqs.tsv --humanTRB -m 10Read in the ntseqs, write the ntseq, aaseq = nt2aa(ntseq), and their pgens to example_pgens.tsv$ olga-compute_pgen -i example_seqs.tsv --humanTRB -o example_pgens.tsvSpecify the V/J mask indices$ olga-compute_pgen -i example_seqs.tsv --humanTRB -o example_pgens.tsv --v_in 2 --j_in 3Read in the aaseq column instead of the ntseq column$ olga-compute_pgen -i example_seqs.tsv --humanTRB -o example_pgens.tsv --seq_in 1Selected OptionsDescription-h, --helpshow full Options list and exit-i PATH/TO/FILEread in CDR3 sequences (and optionally V/J masks) from PATH/TO/FILE-o PATH/TO/FILEwrite CDR3 sequences and pgens to PATH/TO/FILE--seq_in INDEXspecifies sequences to be read in are in column INDEX. Default is index 0 (the first column).--v_in INDEXspecifies V_masks are found in column INDEX in the input file. Default is no V mask.--j_in INDEXspecifies J_masks are found in column INDEX in the input file. Default is no J mask.--v_mask V_MASKspecify V usage to condition Pgen on for seqs read in as arguments.--j_mask J_MASKspecify J usage to condition Pgen on for seqs read in as arguments.-m Ncompute Pgens for at most N sequences.--lines_to_skip Nskip the first N lines of the file. Default is 0.-a PATH/TO/FILEspecify PATH/TO/FILE defining a custom 'amino acid' alphabet. Default is no custom alphabet.--seq_type_out SEQ_TYPEif read in sequences are ntseqs, declare what type of sequence to compute pgen for. Default is all. Choices: 'all', 'ntseq', 'aaseq'--display_offturn the sequence display off (only applies in write-to-file mode). Default is on.-d DELIMITERdeclare infile delimiter. Default is tab for .tsv input files, comma for .csv files, and any whitespace for all others. Choices: 'tab', 'space', ',', ';', ':'--raw_delimiter DELIMITERdeclare infile delimiter as a raw string.--delimiter_out, --raw_delimiter_out, --gene_mask_delimiter, --raw_gene_mask_delimiterdeclare delimiters for the outfile and for gene masks (read in from the columns of v_mask_index and j_mask_index). Same syntax as the infile delimiter.--comment_delimiter

ECS PGEN-30 - PGEN-40 Spec Sheet - ECS Corrosion

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Reward76ers/SFInvincibleLakers/SGInvincibleBulls/SGInvincibleBucks/CInvincibleCeltics/SFGloriousJazz/SFGloriousClippers/PFGloriousBucks/SFGloriousKnicks/PGGloriousRaptors/SFGloriousJazz/SFGloriousLakers/SFGloriousJazz/PGGloriousHawks/SFAll-Time RewardNets/PFSeason 7 RewardsBulls/PFSeason 7 RewardsMavericks/SFAll-Time RewardNuggets/SGAll-Time RewardMavericks/PGAll-Time RewardPistons/CRushWizards/PGRushJazz/SGRushNets/PGRushLakers/CRushWarriors/SGAll-Time RewardRaptors/PGAll-Time RewardPacers/PFAll-Time RewardHeat/PGEnd GameThunder/SFInvincibleThunder/PGInvincibleKnicks/CInvincibleCeltics/SFInvincibleSpurs/SFEncoreGrizzlies/SFEncoreJazz/CEncoreJazz/PFEncoreCavaliers/PGEncoreCeltics/PGEncoreTrail Blazers/PFEncoreRaptors/SFEncoreHawks/SGAll-Time RewardKnicks/SGAll-Time RewardWarriors/SFAll-Time RewardGrizzlies/PFAll-Time RewardWizards/PGRushTimberwolves/SGRushGrizzlies/PFRushWizards/PFRushLakers/SFCard SeriesPlayersTeam/PositionRushSuns/PGAll-Time RewardCavaliers/CAll-Time RewardBulls/SGEnd GameMagic/PFInvinciblePFInvinciblePistons/PGInvincibleCavaliers/PFInvincibleRockets/PFInvincibleThunder/SFInvincibleJazz/CNextPFNextSFNextSGNextSGNextSFNextSGNextSFNextSGNextPGNextSGSeason 7 Rewards76ers/SGAll-Time RewardSpurs/PGAll-Time RewardClippers/PFAll-Time RewardHawks/PFAll-Time RewardJazz/PGAll-Time RewardLakers/SFAll-Time RewardRockets/SFAll-Time RewardTimberwolves/PFAll-Time RewardKings/SGAll-Time RewardTrail Blazers/PFEnd Game76ers/CEnd Game76ers/SGInvincibleRaptors/CInvinciblePistons/SGInvincibleClippers/PFInvinciblePelicans/SFInvincibleWarriors/PGInvincibleNets/PFInvincibleSuperSonics/SGEnd GameSuperSonics/SFInvinciblePistons/CSeason 8 RewardsPistons/PGEnd GameWarriors/PGEnd GameMavericks/PGEnd GameSpurs/CEnd GamePacers/SGInvincibleSuns/SGInvinciblePacers/SFInvincibleTimberwolves/SGInvincibleKings/CSeason 8 Knicks/SFSeason 8 Cavaliers/PGSeason 8 Wizards/SFEnd GameCeltics/CEnd GameLakers/CEnd GameHeat/SGEnd 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ECS PGEN-3 - PGEN-5 Spec Sheet - ECS Corrosion

List,of,amino,acids,or,codons,separated,by,commassymbolB: another,comma,delimited,listetc, where symbolA and symbolB are single characters and aren't one of the protected characters. Please see utils.py for more documentation, and the options of the console scripts to see how to call such alphabet files.In addition to allowing customization of the 'amino acid' alphabet, we include functions that can parse regular expressions with a limited vocabulary. In particular only [] and {} are supported (the symbol for a Kleene star, *, must be reserved for stop codons). The sequences corresponding to the regular expression can then be enumerated and their Pgens summed. Note, this can be slow as Pgen must be computed for each of the enumerated sequences independently. If a particular combination of amino acids is being used in a [] frequently you may consider defining a symbol for that combination and adding it to the alphabet. For example the regular expression 'CASS**[ACDEFGHIKLMNPQRSTVWY]SARPEQFF' will list out 20 sequences, but its Pgen could be computed by considering the single CDR3 sequence 'CASSX**SARPEQFF' Please see documentation in pgen.py for more info and examples. To prevent overflow, the arbitrary length repetition {x,} is cutoff at a maximum of 40 (if you want a higher number {x,y} will go higher than 40). Furthermore, if more than 10,000 sequences correspond to the template, the regular expression will be rejected.ContactAny issues or questions should be addressed to us.LicenseFree use of OLGA is granted under the terms of the GNU General Public License version 3 (GPLv3).. PGEN is an old Sega Genesis/Megadrive emulator for the PS2 based on Generator source code. - pgen/readme.txt at master ps2homebrew/pgen

PGEN 1.5.1 - The Tech Game

Generate_sequences.py │ generation_probability.py │ preprocess_generative_model_and_data.py │ load_model.py │ sequence_generation.py │ └───default_models/ └───human_T_alpha/ │ model_marginals.txt │ model_params.txt │ J_gene_CDR3_anchors.txt │ V_gene_CDR3_anchors.txt │ └───human_T_beta/ │ model_marginals.txt │ model_params.txt │ J_gene_CDR3_anchors.txt │ V_gene_CDR3_anchors.txt │ └───human_B_heavy/ │ model_marginals.txt │ model_params.txt │ J_gene_CDR3_anchors.txt │ V_gene_CDR3_anchors.txt │ └───mouse_T_beta/ model_marginals.txt model_params.txt J_gene_CDR3_anchors.txt V_gene_CDR3_anchors.txtCommand line console scripts and ExamplesThere are two command line console scripts (the scripts can still be called as executables if OLGA is not installed):olga-compute_pgencomputes the generation probability CDR3 sequences according to a generative V(D)J modelolga-generate_sequencesgenerates CDR3 sequences from a generative V(D)J modelFor any of them you can execute with the -h or --help flags to get the options.Quick DemoAfter installing OLGA, we offer a quick demonstration of the console scripts. This will demonstrate generating sequences and computing pgens from the default model for human TCR beta chains that ships with OLGA. This demo will generate two files, example_seqs.tsv and example_pgens.tsv, in the directory that these command line calls are made.$ olga-compute_pgen --humanTRB CASSLGRDGGHEQYFThis computes the pgen of the amino acid sequence CASSLGRDGGHEQYF (you should get ~7.25342176315e-10)$ olga-generate_sequences --humanTRB -n 5Generate 5 human TRB CDR3 sequences (both nucleotide and amino acid sequences) and print to stdout along with the V and J genes used to generate them.$ olga-generate_sequences --humanTRB -o example_seqs.tsv -n 1e2This generates a file example_seqs.tsv and writes 100 generated human TRB CDR3 sequences.$ olga-compute_pgen --humanTRB -i example_seqs.tsv -m 5This reads in the first 5 sequences from the file we just generated, example_seqs.tsv, and and computes both the nucleotide sequence and the amino acid sequence pgens for the 5 sequences and prints it to stdout.$ olga-compute_pgen --humanTRB -i example_seqs.tsv -o example_pgens.tsvThis reads in the full file example_seqs.tsv, and computes both the nucleotide sequence and the amino acid sequence pgen for each of the 100 sequences and writes them to the file example_pgens.tsv. A running display will be printed to stdout with the last few lines computed along with time/rate updates.Specifying a default V(D)J model (or a custom model folder)All of the console scripts require specifying a V(D)J generative model and genomic data. OLGA ships with 4 default models that can be indicated by flags,

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Or a custom model folder can be indicated.OptionsDescription--humanTRADefault human T cell alpha chain model (VJ)--humanTRBDefault human T cell beta chain model (VDJ)--mouseTRBDefault mouse T cell beta chain model (VDJ)--humanIGHDefault human B cell heavy chain model (VDJ)--set_custom_model_VJ PATH/TO/MODEL_FOLDER/Specifies the directory PATH/TO/MODEL_FOLDER/ of a custom VJ generative model--set_custom_model_VDJ PATH/TO/MODEL_FOLDER/Specifies the directory PATH/TO/MODEL_FOLDER/ of a custom VDJ generative modelNote, if specifying a folder for a custom VJ recombination model(e.g. an alpha or light chain model) or a custom VDJ recombination model(e.g. a beta or heavy chain model), the folder must contain the following fileswith the exact naming convention:model_params.txt (IGoR inference param file)model_marginals.txt (IGoR inference marginal file)V_gene_CDR3_anchors.csv (V anchor residue position and functionality file)J_gene_CDR3_anchors.csv (J anchor residue position and functionality file)The console scripts can only read files of the assumed anchor.csv/IGoR syntaxes. If the advanced user wants to read in models from files of other formats please read the discussion in the Python module section and the documentation of load_model.py.compute_pgen.py (olga-compute_pgen)This script will compute the generation probabilities (pgens) of sequences, as defined by a specified generative model. The sequences must be TRIMMED TO ONLY THE CDR3 region as defined by the V and J anchor files (default is to INCLUDE the conserved residues of the C in the V region and the F/W in the J region).Each sequence will be determined to be one of:'Amino acid' sequence including any ambiguous amino acid symbols (seeOptions for alphabet_file to specify custom symbols)Nucleotide sequence (in-frame)Regular expression template for 'amino acid sequences'This script can read in sequences and output pgens in one of three modes (determined automatically based on the input arguments):Pass CDR3 sequences as arguments, output is printed to stdout.Read in CDR3 sequences from a file, output is printed to stdout.Read in CDR3 sequences from a file, output to a file, dynamic display with time updates printed to stdout.Full options can be printed by: $ olga-compute_pgen -hMode 1):This mode is provided as a way to quickly compute pgen of just a single or couple of sequences. It is not advisable to use this method to set up a loop over a lot of sequences as each call. PGEN is an old Sega Genesis/Megadrive emulator for the PS2 based on Generator source code. - pgen/readme.txt at master ps2homebrew/pgen

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Precigen's Regulatory Milestone with PRGN-2012Precigen, Inc. shares have recently surged following the company's completion of a rolling submission for a biologics license application (BLA) to the FDA. This application is for PRGN-2012, also known as zopapogene imadenovec, which targets adult patients affected by recurrent respiratory papillomatosis (RRP).Understanding PRGN-2012PRGN-2012 represents an innovative approach as an investigational Gene Therapy aimed at addressing HPV 6 and HPV 11 infections, which are the primary causes of RRP. The therapy has already gained significant recognition, receiving both Breakthrough Therapy and Orphan Drug designations from the FDA, as well as Orphan Drug Designation from the European Commission, showcasing its potential as a pivotal treatment option.Challenges of Recurrent Respiratory PapillomatosisRRP is a rare and serious condition characterized by the growth of benign tumors in the respiratory tract, which can significantly impact patients’ quality of life. Currently, the standard treatment involves repeated surgeries, which only alleviate symptoms but do not address the underlying viral cause of the disease. This means patients often find themselves in a cycle of recurring treatment, highlighting the critical need for effective therapies.BLA Submission and Review ProcessThe biologics license application is now in the FDA's initial 60-day review phase. During this period, the FDA will evaluate whether to accept the application for a more in-depth review. The company has applied for a priority review, which could expedite the review timeline significantly, potentially condensing the typical approval period from 10 months down to 6 months.Supporting Evidence from Clinical StudiesSupport for the BLA comes from a Phase 1/2 study (NCT04724980) conducted with 38 RRP patients, where the primary safety and efficacy endpoints were successfully achieved. The findings from the pivotal study were also presented at the recent ASCO annual meeting, further underscoring the promising nature of PRGN-2012.Strategic Vision and Future OutlookHelen Sabzevari, PhD, President and CEO of Precigen, emphasized the urgency of advancing therapy options for RRP patients, stating, “There is currently no approved therapy for RRP patients, and the submission of our BLA represents an essential step towards providing a viable treatment for this devastating disease.” Her confidence also reflects the company's strategic efforts to enhance its financial stability, with recent announcements extending their cash runway into 2026 and beyond, aligning well with a potential commercial launch in the latter half of 2025.Market Response and Price MovementsIn light of these developments, shares of PGEN have witnessed a marked increase, rising 23.9% to reach $0.9000 in recent trading sessions. This upward momentum demonstrates strong market interest in Precigen’s advancements, particularly regarding their innovative therapy targeting RRP.Frequently Asked QuestionsWhat is PRGN-2012?PRGN-2012 is an investigational gene therapy developed by Precigen aimed at treating recurrent respiratory papillomatosis caused by HPV infections.What designations has PRGN-2012 received?The therapy has received Breakthrough Therapy and Orphan Drug designations from the FDA, along with Orphan Drug Designation from the European Commission.What is the current treatment for RRP?Current treatments mainly involve repeated surgeries, which address symptoms but do not tackle the root cause of the disease.How is PRGN-2012 progressing through the FDA process?The BLA for