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{
    "count": 9362,
    "next": "?page=2",
    "previous": null,
    "list": [
        {
            "name": "Stitch",
            "description": "Stitch is a software tool that performs template-based assembly of proteomics short reads for de novo antibody sequencing and repertoire profiling.",
            "homepage": "https://github.com/snijderlab/stitch",
            "biotoolsID": "stitch-snijderlab",
            "biotoolsCURIE": "biotools:stitch-snijderlab",
            "version": [
                "1.5.0"
            ],
            "otherID": [],
            "relation": [],
            "function": [
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_0310",
                            "term": "Sequence assembly"
                        }
                    ],
                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_1233",
                                "term": "Sequence set (protein)"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_1929",
                                    "term": "FASTA"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1964",
                                    "term": "plain text format (unformatted)"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3752",
                                    "term": "CSV"
                                },
                                {
                                    "uri": "http://edamontology.org/format_1477",
                                    "term": "mmCIF"
                                }
                            ]
                        }
                    ],
                    "output": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_1233",
                                "term": "Sequence set (protein)"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_1929",
                                    "term": "FASTA"
                                },
                                {
                                    "uri": "http://edamontology.org/format_2331",
                                    "term": "HTML"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3752",
                                    "term": "CSV"
                                }
                            ]
                        }
                    ],
                    "note": "Assembles de novo peptide sequences against known antibody gene segments to reconstruct complete antibody sequences.\nFor batch file (job file) specifications, see https://github.com/snijderlab/stitch/blob/master/BatchFiles.md.\nOptions:\n--expect - The expected result(s) of the run as the final sequence(s) by separated commas, used for automated testing;\n--open - Open the HTML report (if available) automatically in the browser;\n--live - Prepare the HTML report for use with VS Code Live Server on the given port, -1 turns it off;\n--quiet - Turns off any output on the command line in normal operation.",
                    "cmd": "stitch run [OPTIONS] <batchfile>"
                },
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_2425",
                            "term": "Optimisation and refinement"
                        }
                    ],
                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0943",
                                "term": "Mass spectrum"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_3752",
                                    "term": "CSV"
                                }
                            ]
                        }
                    ],
                    "output": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0943",
                                "term": "Mass spectrum"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_3752",
                                    "term": "CSV"
                                }
                            ]
                        }
                    ],
                    "note": "Utilizes a mass-based alignment algorithm to handle mass coincidence errors and differentiates between isoleucine and leucine residues using secondary fragments. Generates two CSV files: one with refined reads and another with positional information.\nOptions:\n--output - The filename of the refined reads, the extension will be added automatically;\n--peaks-version - The version of the Peaks file format to use.",
                    "cmd": "stitch refine [OPTIONS] <input> <raw-data-dir>"
                },
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_1812",
                            "term": "Parsing"
                        }
                    ],
                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_1233",
                                "term": "Sequence set (protein)"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_2331",
                                    "term": "HTML"
                                }
                            ]
                        }
                    ],
                    "output": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_1233",
                                "term": "Sequence set (protein)"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_1929",
                                    "term": "FASTA"
                                }
                            ]
                        }
                    ],
                    "note": "Parses the sequences from an IMGT HTML file and creates annotated fasta files (also cleans data).\nOptions:\n--output - The output file name, if missing will overwrite the input file.",
                    "cmd": "stitch annotate [OPTIONS] <input>"
                },
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_2409",
                            "term": "Data handling"
                        }
                    ],
                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_1233",
                                "term": "Sequence set (protein)"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_1929",
                                    "term": "FASTA"
                                }
                            ]
                        }
                    ],
                    "output": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_1233",
                                "term": "Sequence set (protein)"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_1929",
                                    "term": "FASTA"
                                }
                            ]
                        }
                    ],
                    "note": "Removes duplicates and incomplete sequences from fasta. \nOptions: \n--output - The output file name, if missing will overwrite the input file.",
                    "cmd": "stitch clean [OPTIONS] <input>"
                }
            ],
            "toolType": [
                "Command-line tool"
            ],
            "topic": [],
            "operatingSystem": [
                "Windows",
                "Linux",
                "Mac"
            ],
            "language": [
                "C#"
            ],
            "license": "MIT",
            "collectionID": [],
            "maturity": "Mature",
            "cost": "Free of charge",
            "accessibility": "Open access",
            "elixirPlatform": [],
            "elixirNode": [],
            "elixirCommunity": [],
            "link": [
                {
                    "url": "https://github.com/snijderlab/stitch",
                    "type": [
                        "Repository"
                    ],
                    "note": null
                }
            ],
            "download": [
                {
                    "url": "https://github.com/snijderlab/stitch/releases/tag/v1.5.0",
                    "type": "Downloads page",
                    "note": null,
                    "version": "1.5.0"
                }
            ],
            "documentation": [],
            "publication": [
                {
                    "doi": "10.1021/acs.jproteome.4c00188",
                    "pmid": "38932690",
                    "pmcid": null,
                    "type": [],
                    "version": "1.5.0",
                    "note": null,
                    "metadata": {
                        "title": "A Handle on Mass Coincidence Errors in De Novo Sequencing of Antibodies by Bottom-up Proteomics",
                        "abstract": "Antibody sequences can be determined at 99% accuracy directly from the polypeptide product by using bottom-up proteomics techniques. Sequencing accuracy at the peptide level is limited by the isobaric residues leucine and isoleucine, incomplete fragmentation spectra in which the order of two or more residues remains ambiguous due to lacking fragment ions for the intermediate positions, and isobaric combinations of amino acids, of potentially different lengths, for example, GG = N and GA = Q. Here, we present several updates to Stitch (v1.5), which performs template-based assembly of de novo peptides to reconstruct antibody sequences. This version introduces a mass-based alignment algorithm that explicitly accounts for mass coincidence errors. In addition, it incorporates a postprocessing procedure to assign I/L residues based on secondary fragments (satellite ions, i.e., w-ions). Moreover, evidence for sequence assignments can now be directly evaluated with the addition of an integrated spectrum viewer. Lastly, input data from a wider selection of de novo peptide sequencing algorithms are allowed, now including Casanovo, PEAKS, Novor.Cloud, pNovo, and MaxNovo, in addition to flat text and FASTA. Combined, these changes make Stitch compatible with a larger range of data processing pipelines and improve its tolerance to peptide-level sequencing errors.",
                        "date": "2024-01-01T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Schulte D."
                            },
                            {
                                "name": "Snijder J."
                            }
                        ],
                        "journal": "Journal of Proteome Research"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Douwe Schulte",
                    "email": null,
                    "url": null,
                    "orcidid": "https://orcid.org/0000-0003-0594-0993",
                    "gridid": null,
                    "rorid": null,
                    "fundrefid": null,
                    "typeEntity": "Person",
                    "typeRole": [
                        "Primary contact"
                    ],
                    "note": "Software Engineer"
                },
                {
                    "name": "Joost Snijder",
                    "email": null,
                    "url": null,
                    "orcidid": "https://orcid.org/0000-0002-9310-8226",
                    "gridid": null,
                    "rorid": null,
                    "fundrefid": null,
                    "typeEntity": "Person",
                    "typeRole": [],
                    "note": "Principal Investigator"
                },
                {
                    "name": "Bastiaan de Graaf",
                    "email": null,
                    "url": null,
                    "orcidid": null,
                    "gridid": null,
                    "rorid": null,
                    "fundrefid": null,
                    "typeEntity": "Person",
                    "typeRole": [],
                    "note": "Code Reviews"
                },
                {
                    "name": "Wei Wei Peng",
                    "email": null,
                    "url": null,
                    "orcidid": null,
                    "gridid": null,
                    "rorid": null,
                    "fundrefid": null,
                    "typeEntity": "Person",
                    "typeRole": [],
                    "note": "Testing and Analysis"
                },
                {
                    "name": "Biomolecular Mass Spectrometry and Proteomics",
                    "email": null,
                    "url": "https://www.uu.nl/en/research/biomolecular-mass-spectrometry-and-proteomics",
                    "orcidid": null,
                    "gridid": null,
                    "rorid": null,
                    "fundrefid": null,
                    "typeEntity": "Division",
                    "typeRole": [],
                    "note": "Group at Utrecht University"
                }
            ],
            "community": null,
            "owner": "thatmariia",
            "additionDate": "2024-07-17T13:27:56.256529Z",
            "lastUpdate": "2024-07-18T14:56:47.152424Z",
            "editPermission": {
                "type": "public",
                "authors": []
            },
            "validated": 0,
            "homepage_status": 0,
            "elixir_badge": 0,
            "confidence_flag": null
        },
        {
            "name": "scTE",
            "description": "scTE builds genome indices for the fast alignment of reads to genes and Transposable elements (TEs).",
            "homepage": "https://github.com/JiekaiLab/scTE",
            "biotoolsID": "scte",
            "biotoolsCURIE": "biotools:scte",
            "version": [
                "1.0.0"
            ],
            "otherID": [],
            "relation": [],
            "function": [
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_3800",
                            "term": "RNA-Seq quantification"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0361",
                            "term": "Sequence annotation"
                        }
                    ],
                    "input": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_1383",
                                "term": "Nucleic acid sequence alignment"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_2572",
                                    "term": "BAM"
                                }
                            ]
                        },
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_1276",
                                "term": "Nucleic acid features"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_2306",
                                    "term": "GTF"
                                }
                            ]
                        },
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_3002",
                                "term": "Annotation track"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_3003",
                                    "term": "BED"
                                }
                            ]
                        }
                    ],
                    "output": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_3112",
                                "term": "Gene expression matrix"
                            },
                            "format": [
                                {
                                    "uri": "http://edamontology.org/format_3590",
                                    "term": "HDF5"
                                },
                                {
                                    "uri": "http://edamontology.org/format_3752",
                                    "term": "CSV"
                                }
                            ]
                        }
                    ],
                    "note": null,
                    "cmd": "scTE_build -te TEs.bed -gene Genes.gtf -o custome\nscTE -i inp.bam -o out -x mm10.exclusive.idx --hdf5 True"
                }
            ],
            "toolType": [
                "Command-line tool"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_0659",
                    "term": "Functional, regulatory and non-coding RNA"
                },
                {
                    "uri": "http://edamontology.org/topic_0798",
                    "term": "Mobile genetic elements"
                },
                {
                    "uri": "http://edamontology.org/topic_3170",
                    "term": "RNA-Seq"
                }
            ],
            "operatingSystem": [
                "Linux"
            ],
            "language": [
                "Python"
            ],
            "license": "MIT",
            "collectionID": [],
            "maturity": null,
            "cost": "Free of charge",
            "accessibility": "Open access",
            "elixirPlatform": [],
            "elixirNode": [],
            "elixirCommunity": [],
            "link": [
                {
                    "url": "https://github.com/JiekaiLab/scTE",
                    "type": [
                        "Repository"
                    ],
                    "note": null
                },
                {
                    "url": "https://zenodo.org/records/4420937",
                    "type": [
                        "Repository"
                    ],
                    "note": null
                }
            ],
            "download": [
                {
                    "url": "https://github.com/JiekaiLab/scTE/releases/tag/scTE.v1.0.0",
                    "type": "Downloads page",
                    "note": null,
                    "version": "v1.0.0"
                },
                {
                    "url": "https://anaconda.org/bioconda/scte",
                    "type": "Software package",
                    "note": null,
                    "version": null
                }
            ],
            "documentation": [],
            "publication": [
                {
                    "doi": "10.1038/s41467-021-21808-x",
                    "pmid": "33674594",
                    "pmcid": null,
                    "type": [
                        "Primary"
                    ],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "Identifying transposable element expression dynamics and heterogeneity during development at the single-cell level with a processing pipeline scTE",
                        "abstract": "Transposable elements (TEs) make up a majority of a typical eukaryote’s genome, and contribute to cell heterogeneity in unclear ways. Single-cell sequencing technologies are powerful tools to explore cells, however analysis is typically gene-centric and TE expression has not been addressed. Here, we develop a single-cell TE processing pipeline, scTE, and report the expression of TEs in single cells in a range of biological contexts. Specific TE types are expressed in subpopulations of embryonic stem cells and are dynamically regulated during pluripotency reprogramming, differentiation, and embryogenesis. Unexpectedly, TEs are expressed in somatic cells, including human disease-specific TEs that are undetectable in bulk analyses. Finally, we apply scTE to single-cell ATAC-seq data, and demonstrate that scTE can discriminate cell type using chromatin accessibly of TEs alone. Overall, our results classify the dynamic patterns of TEs in single cells and their contributions to cell heterogeneity.",
                        "date": "2021-12-01T00:00:00Z",
                        "citationCount": 64,
                        "authors": [
                            {
                                "name": "He J."
                            },
                            {
                                "name": "Babarinde I.A."
                            },
                            {
                                "name": "Sun L."
                            },
                            {
                                "name": "Xu S."
                            },
                            {
                                "name": "Chen R."
                            },
                            {
                                "name": "Shi J."
                            },
                            {
                                "name": "Wei Y."
                            },
                            {
                                "name": "Li Y."
                            },
                            {
                                "name": "Ma G."
                            },
                            {
                                "name": "Zhuang Q."
                            },
                            {
                                "name": "Hutchins A.P."
                            },
                            {
                                "name": "Chen J."
                            }
                        ],
                        "journal": "Nature Communications"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Jiangping He",
                    "email": null,
                    "url": null,
                    "orcidid": "http://orcid.org/0000-0002-1425-3530",
                    "gridid": null,
                    "rorid": null,
                    "fundrefid": null,
                    "typeEntity": "Person",
                    "typeRole": [
                        "Developer"
                    ],
                    "note": null
                },
                {
                    "name": "Jiekai Chen",
                    "email": "chen_jiekai@gibh.ac.cn",
                    "url": null,
                    "orcidid": "http://orcid.org/0000-0001-5168-7074",
                    "gridid": null,
                    "rorid": null,
                    "fundrefid": null,
                    "typeEntity": "Person",
                    "typeRole": [
                        "Primary contact"
                    ],
                    "note": null
                }
            ],
            "community": null,
            "owner": "billsfriend",
            "additionDate": "2024-07-18T11:34:53.652671Z",
            "lastUpdate": "2024-07-18T11:36:30.859044Z",
            "editPermission": {
                "type": "private",
                "authors": []
            },
            "validated": 0,
            "homepage_status": 0,
            "elixir_badge": 0,
            "confidence_flag": null
        },
        {
            "name": "PyPop",
            "description": "Mature open-source software pipeline for population genomics.",
            "homepage": "http://pypop.org/",
            "biotoolsID": "pypop",
            "biotoolsCURIE": "biotools:pypop",
            "version": [],
            "otherID": [],
            "relation": [],
            "function": [
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_3196",
                            "term": "Genotyping"
                        },
                        {
                            "uri": "http://edamontology.org/operation_3436",
                            "term": "Aggregation"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0488",
                            "term": "Linkage disequilibrium calculation"
                        },
                        {
                            "uri": "http://edamontology.org/operation_0252",
                            "term": "Peptide immunogenicity prediction"
                        }
                    ],
                    "input": [],
                    "output": [],
                    "note": null,
                    "cmd": null
                }
            ],
            "toolType": [
                "Command-line tool"
            ],
            "topic": [
                {
                    "uri": "http://edamontology.org/topic_2830",
                    "term": "Immunoproteins and antigens"
                },
                {
                    "uri": "http://edamontology.org/topic_3796",
                    "term": "Population genomics"
                },
                {
                    "uri": "http://edamontology.org/topic_3056",
                    "term": "Population genetics"
                },
                {
                    "uri": "http://edamontology.org/topic_0102",
                    "term": "Mapping"
                },
                {
                    "uri": "http://edamontology.org/topic_3930",
                    "term": "Immunogenetics"
                }
            ],
            "operatingSystem": [
                "Mac",
                "Linux",
                "Windows"
            ],
            "language": [
                "Python"
            ],
            "license": "GPL-2.0",
            "collectionID": [],
            "maturity": null,
            "cost": "Free of charge",
            "accessibility": null,
            "elixirPlatform": [],
            "elixirNode": [],
            "elixirCommunity": [],
            "link": [
                {
                    "url": "https://github.com/alexlancaster/pypop",
                    "type": [
                        "Repository"
                    ],
                    "note": null
                }
            ],
            "download": [
                {
                    "url": "https://pypi.org/project/pypop-genomics/",
                    "type": "Binaries",
                    "note": null,
                    "version": null
                }
            ],
            "documentation": [],
            "publication": [
                {
                    "doi": "10.3389/fimmu.2024.1378512",
                    "pmid": "38629078",
                    "pmcid": "PMC11019567",
                    "type": [],
                    "version": null,
                    "note": null,
                    "metadata": {
                        "title": "PyPop: a mature open-source software pipeline for population genomics",
                        "abstract": "Python for Population Genomics (PyPop) is a software package that processes genotype and allele data and performs large-scale population genetic analyses on highly polymorphic multi-locus genotype data. In particular, PyPop tests data conformity to Hardy-Weinberg equilibrium expectations, performs Ewens-Watterson tests for selection, estimates haplotype frequencies, measures linkage disequilibrium, and tests significance. Standardized means of performing these tests is key for contemporary studies of evolutionary biology and population genetics, and these tests are central to genetic studies of disease association as well. Here, we present PyPop 1.0.0, a new major release of the package, which implements new features using the more robust infrastructure of GitHub, and is distributed via the industry-standard Python Package Index. New features include implementation of the asymmetric linkage disequilibrium measures and, of particular interest to the immunogenetics research communities, support for modern nomenclature, including colon-delimited allele names, and improvements to meta-analysis features for aggregating outputs for multiple populations. Code available at: https://zenodo.org/records/10080668 and https://github.com/alexlancaster/pypop.",
                        "date": "2024-01-01T00:00:00Z",
                        "citationCount": 0,
                        "authors": [
                            {
                                "name": "Lancaster A.K."
                            },
                            {
                                "name": "Single R.M."
                            },
                            {
                                "name": "Mack S.J."
                            },
                            {
                                "name": "Sochat V."
                            },
                            {
                                "name": "Mariani M.P."
                            },
                            {
                                "name": "Webster G.D."
                            }
                        ],
                        "journal": "Frontiers in Immunology"
                    }
                }
            ],
            "credit": [
                {
                    "name": "Alexander K. Lancaster",
                    "email": "alancaster@amberbiology.com",
                    "url": null,
                    "orcidid": null,
                    "gridid": null,
                    "rorid": null,
                    "fundrefid": null,
                    "typeEntity": "Person",
                    "typeRole": [],
                    "note": null
                },
                {
                    "name": "Richard M. Single",
                    "email": "richard.single@uvm.edu",
                    "url": null,
                    "orcidid": null,
                    "gridid": null,
                    "rorid": null,
                    "fundrefid": null,
                    "typeEntity": "Person",
                    "typeRole": [],
                    "note": null
                },
                {
                    "name": "Steven J. Mack",
                    "email": "steven.mack@ucsf.edu",
                    "url": null,
                    "orcidid": null,
                    "gridid": null,
                    "rorid": null,
                    "fundrefid": null,
                    "typeEntity": "Person",
                    "typeRole": [],
                    "note": null
                }
            ],
            "community": null,
            "owner": "Pub2Tools",
            "additionDate": "2024-07-18T11:03:30.172275Z",
            "lastUpdate": "2024-07-18T11:04:50.715341Z",
            "editPermission": {
                "type": "public",
                "authors": []
            },
            "validated": 0,
            "homepage_status": 0,
            "elixir_badge": 0,
            "confidence_flag": "tool"
        },
        {
            "name": "PySmooth",
            "description": "Python tool for the removal and correction of genotyping errors.",
            "homepage": "https://github.com/lncRNAAddict/PySmooth",
            "biotoolsID": "pysmooth",
            "biotoolsCURIE": "biotools:pysmooth",
            "version": [],
            "otherID": [],
            "relation": [],
            "function": [
                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_3196",
                            "term": "Genotyping"
                        },
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                        "abstract": "There is a need to better understand and handle the 'dark matter' of proteomics-the vast diversity of post-translational and chemical modifications that are unaccounted in a typical mass spectrometry-based analysis and thus remain unidentified. We present a fragment-ion indexing method, and its implementation in peptide identification tool MSFragger, that enables a more than 100-fold improvement in speed over most existing proteome database search tools. Using several large proteomic data sets, we demonstrate how MSFragger empowers the open database search concept for comprehensive identification of peptides and all their modified forms, uncovering dramatic differences in modification rates across experimental samples and conditions. We further illustrate its utility using protein-RNA cross-linked peptide data and using affinity purification experiments where we observe, on average, a 300% increase in the number of identified spectra for enriched proteins. We also discuss the benefits of open searching for improved false discovery rate estimation in proteomics.",
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