extract_features {cellity} | R Documentation

## Extracts biological and technical features for given dataset

### Description

Extracts biological and technical features for given dataset

### Usage

    extract_features(counts_nm, read_metrics, prefix = "", output_dir = "",
      common_features = NULL, GO_terms = NULL, extra_genes = NULL,
      organism = "mouse")

### Arguments

`counts_nm` | Gene expression counts dataframe (genes x cells). Either normalised by library size or TPM values
`read_metrics` | Dataframe with mapping statistics produced by python pipeline
`prefix` | Prefix of outputfiles
`output_dir` | Output directory of files
`common_features` | Subset of features that are applicable within one species, but across cell types
`GO_terms` | DataFrame with gene ontology term IDs, that will be used in feature extraction
`extra_genes` | Additional genes used for feature extraction
`organism` | The target organism to generate the features for

### Details

This function takes a combination of gene counts and mapping statistics to extract biological and technical features, which than can be used for quality data analysis

### Value

a list with two elements, one providing all features, and one providing common features.

### Examples

    data(sample_counts)
    data(sample_stats)
    sample_counts_nm <- normalise_by_factor(sample_counts, colSums(sample_counts))
    sample_features <- extract_features(sample_counts_nm, sample_stats)

[Package cellity version 1.18.0 Index]