| import datasets | |
| import pandas as pd | |
| _CITATION = """\ | |
| Feng Q, Liang S, Jia H, et al. Gut microbiome development along the colorectal adenoma-carcinoma sequence. Nat Commun. 2015;6:6528. Published 2015 Mar 11. doi:10.1038/ncomms7528 | |
| """ | |
| _DESCRIPTION = """\ | |
| The dataset contains 16S rRNA gene sequencing data from healthy controls and colorectal cancer patients. The dataset was used in the paper "Gut microbiome development along the colorectal adenoma-carcinoma sequence" by Feng et al. (2015). | |
| """ | |
| _HOMEPAGE = "https://pubmed.ncbi.nlm.nih.gov/25758642/" | |
| _URL = "https://huggingface.co/datasets/wwydmanski/colorectal-carcinoma-microbiome-fengq/raw/main/" | |
| class ColorectalCarcinomaMicrobiomeFengQConfig(datasets.GeneratorBasedBuilder): | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| name="presence-absence", | |
| description="Binary presence/absence of taxa", | |
| ), | |
| datasets.BuilderConfig( | |
| name="CLR", | |
| description="Relative abundance of taxa", | |
| ), | |
| ] | |
| DEFAULT_CONFIG_NAME = "presence-absence" | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| citation=_CITATION, | |
| homepage=_HOMEPAGE, | |
| version=datasets.Version("0.1.0"), | |
| ) | |
| def _split_generators(self, dl_manager): | |
| if self.config.name == "presence-absence": | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "filepath": "PA_train.csv", | |
| "split": "train", | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={ | |
| "filepath": "PA_test.csv", | |
| "split": "test", | |
| }, | |
| ), | |
| ] | |
| elif self.config.name == "CLR": | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "filepath": "CLR_train.csv", | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={ | |
| "filepath": "CLR_test.csv", | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, filepath, split=None): | |
| df = pd.read_csv(_URL+filepath) | |
| for i, row in df.iterrows(): | |
| target = row["target"] | |
| values = row.drop("target").values | |
| yield i, { | |
| "values": values, | |
| "target": target, | |
| } |