Skip to main content

EMIRGE reconstructs full length sequences from short sequencing reads

Project description

EMIRGE: Expectation-Maximization Iterative Reconstruction of Genes

from the Environment

EMIRGE reconstructs full length ribosomal genes from short read sequencing data. In the process, it also provides estimates of the sequences’ abundances.

EMIRGE uses a modification of the EM algorithm to iterate between estimating the expected value of the abundance of all SSU sequences present in a sample and estimating the probabilities for each read that a specific sequence generated that read. At the end of each iteration, those probabilities are used to re-calculate (correct) a consensus sequence for each reference SSU sequence, and the mapping is repeated, followed by the estimations of probabilities. The iterations should usually stop when the reference sequences no longer change from one iteration to the next. Practically, 40-80 iterations is usually sufficient for many samples. Right now EMIRGE uses Bowtie alignments internally, though in theory a different mapper could be used.

EMIRGE was designed for Illumina reads in FASTQ format, from pipeline version >= 1.3

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

EMIRGE-0.61.1.tar.gz (255.8 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page