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select_contig_regions.py 2017-10-12 3.6 kB
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parse_blast_hits_aves.py 2017-10-12 4.5 kB
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parse_blast_hits_genome.py 2017-10-12 2.1 kB
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parse_blast_hits_mammals.py 2017-10-12 3.8 kB
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parse_db_seqids.py 2017-10-12 753 Bytes
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extract_nonannotated_genes.py 2017-10-12 739 Bytes
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extract_unassigned_contigs.py 2017-10-12 729 Bytes
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extract_unmapped_contigs.py 2017-10-12 980 Bytes
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get_gene_symbols.py 2017-10-12 1.5 kB
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extract_gene_coordinates.py 2017-10-12 986 Bytes
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extract_gene_isoforms.py 2017-10-12 1.5 kB
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extract_genome_coordinates.py 2017-10-12 522 Bytes
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extract_longest_isoforms.py 2017-10-12 2.4 kB
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concatenate_gene_sequences.py 2017-10-12 2.2 kB
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convert_tids_into_gids.py 2017-10-12 673 Bytes
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create_gene_transcript_map.py 2017-10-12 366 Bytes
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create_taxid_map.py 2017-10-12 428 Bytes
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assign_contigs_to_genes.py 2017-10-12 3.3 kB
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build_consensus_sequences.py 2017-10-12 6.7 kB
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build_scaffolds.py 2017-10-12 7.9 kB
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assign_unassigned_contigs_to_genes.py 2017-10-12 609 Bytes
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Totals: 21 Items   46.4 kB 0 
These Python scripts are usable for a dual transcript-discovery approach that improves the delimitation of gene features from RNA-seq data in the chicken model.
http://bio.biologists.org/content/7/1/bio028498
https://www.ncbi.nlm.nih.gov/pubmed/?term=29183907

Full documentation is provided as supplementary information:
http://bio.biologists.org/content/biolopen/suppl/2018/01/17/bio.028498.DC1/BIO028498supp.pdf

Scripts are compatible with Python 2.7.

Supplementary files:
* galGal4_gene_annotation_model.gtf: Gene annotation model in GTF format associated with the galGal4 version of the chicken genome.
* galGal4_artificial_chromosome.fasta: Artificial chromosome in FASTA format containing the unique contig sequences generated from the de novo transcript discovery. Unique contig sequences are separated to each other by 250 bp.
* galGal4_artificial_chromosome.gtf: Gene annotation model in GTF format associated with the artificial chromosome generated from the de novo transcript discovery.

If you use any of these scripts/files, please cite:
Orgeur M., Martens M., Börno S. T., Timmermann B., Duprez D. and Stricker S. (2018). A dual transcript-discovery approach to improve the delimitation of gene features from RNA-seq data in the chicken model. Biology Open 7(1): bio028498. doi: 10.1242/bio.028498 PMID: 29183907.
Source: README.txt, updated 2018-02-01