Pheniqs 2.0: accurate, high-performance Bayesian decoding and confidence estimation for combinatorial barcode indexing

Pheniqs 2.0: accurate, high-performance Bayesian decoding and confidence estimation for combinatorial barcode indexing

Background: Systems biology increasingly relies on deep sequencing with combinatorial index tags to associate biological sequences with their sample, cell, or molecule of origin. Accurate data interpretation depends on the ability to classify sequences based on correct decoding of these combinatoria...

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Bibliographic Details
Main Authors: Galanti, L. (Author), Gunsalus, K.C (Author), Shasha, D. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
article
Bar codes
Barcode decoding confidence
Barcode noise filtering
Barcode simulation
Bayes theorem
Bayes Theorem
Benchmarking
Classification confidence
Combinatorial indexing
Computationally efficient
Confidence estimation
Continuous improvements
Decoding
DNA barcoding
DNA Barcoding, Taxonomic
DNA sequence
Electronic Data Processing
experimental design
filtration
genomics
high throughput sequencing
High-Throughput Nucleotide Sequencing
information processing
Maximum likelihood estimation
maximum likelihood method
memory
Minimum edit distance
Multi-threaded implementation
noise
pipeline
Posterior probability
probability
Quality control
Random errors
reproducibility
Reproducibility of Results
Scalable implementation
sequence alignment
Sequence Analysis, DNA
Sequence demultiplexing
sequencing error
simulation
Single-cell split-pooling
software
Software
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