Base Caller Summaries

Standard Illumina Base Caller

Sequencing-by-Synthesis (SBS)

• DNA sample obtained, containing many copies of same sequences and randomly fragmented
• Single-stranded DNA fragments attached to slide and amplified so there is a cluster of each fragment
• DNA polymerase and 4 terminal bases (with distinct fluorescent markers) added
• Clusters excited by lasers and photos taken in optimal wavelengths for 4 fluorophores
• Fluorophores and terminators removed and process repeated for L cycles

Image Analysis

• Corrects for imperfect repositioning of camera and aberrations of lens by aligning images to reference from original cycle
• Signal for each cluster characterized as time series data of fluorescence intensities and noise

Base Calling

• Converts fluorescence signals into actual sequence data with quality scores
• Takes intensities of four channels for every cluster in each cycle and determines concentration of each base
• Renormalizes concentrations by multiplying by ratio of average concentrations in first cycle and current cycle
• Uses Markov model to determine transition matrix modeling probability of phasing (no new base synthesized), prephasing (two new bases synthesized), and normal incorporation
• Uses transition matrix and observed concentrations of each base to determine concentrations in absence of phasing and reports these as base calls

General Noise Factors

• Phasing
  • Failures in nucleotide incorporation or block removal or incorporation of more than one nucleotide in a particular cycle
• Fading
  • Decay in fluorescent signal intensity with each cycle
  • Likely attributable to material loss during sequencing
• Crosstalk
  • C channel illumination overlaps with A: a C label fluoresces in A channel (similarly G and T overlap)
  • Likely caused by overlap in dye emission frequencies

Alta-Cyclic

Training Stage

• Learns run-specific noise patterns according to model and finds optimized solution reducing affect of noise sources using a Support Vector Machine (SVM)
• Half of training set used for cross-validation

Base Calling Stage

• Reports all sequences from run with optimized parameters

Differences from Standard Illumina Base Caller

• Calling parameters optimized empirically and tested to enhance accuracy of each run
• Calculates phasing parameters based on parametric model
• Dynamically tracks changes in crosstalk, which disrupt signals in later cycles

Ibis

(To be added soon.)

References

Erlich, Y., Mitra, P.P., delaBastide, M., McCombie, W.R., Hannon, G.J. (2008) Alta-Cyclic: A self-optimizing base caller for next-generation sequencing. Nature Methods 5:679-682

Kao, W.-C., Stevens, K., Song, Y.S. (2009) BayesCall: A model-based base-calling algorithm for high-throughput short-read sequencing. Genome Research 19:1884-1895

Rougemont, J., Amzallag, A., Iseli, C., Farinelli, L., Xenarios, I., Naef, F. (2008) Probabilistic base calling of Solexa sequencing data. BMC Bioinformatics 9:Article 431

Whiteford, N., Skelly, T., Curtis, C., Ritchie, M.E., Löhr, A., Zaranek, A.W., Abnizova, I., Brown, C. (2009) Swift: Primary data analysis for the Illumina Solexa sequencing platform. Bioinformatics 25:2194-2199