About DICEseq¶

DICEseq (Dynamic Isoform spliCing Estimator via sequencing data) estimates the dynamics of isoform proportions jointly from time series RNA-seq experiments. DICEseq is a Bayesian method based on a mixture model whose mixing proportions represent isoform ratios. It incorporates the correlations from the temporal structure, by coupling the isoform proportions at different times through a latent Gaussian process (GP).

DICEseq provides following functions through command line:

1. diceseq:

• Estimate the isoform proportions and FPKM jointly or separately.
• Calculate the Bayes factor to detect the differential dynamics of splicing profile.

2. dice-count:

• Get the total reads counts of each gene.
• Get the specific reads counts, e.g., junction reads, for genes with exactly one intron. This is particularly design for yeast.

3. dice-bias:

• Estimate fragment length distribution.
• Estimate reads sequence and position bias parameter. The output file can be directly used for bias correction in diceseq.

In addition, DICEseq package also provides interface of a set of functions and attributes as an object-oriented python module. Therefore, you could use some of the module e.g., SampleFile to visualize the samples in gzip file in a Gaussian process way, or BiasFile to visualize the bias parameters. Also, the gtf_utils provides a set of ways to load gtf file, choose the genes, or customize the coordinates of exons and introns, add and remove of specific transcripts.

References¶

Yuanhua Huang and Guido Sanguinetti. Statistical modeling of isoform splicing dynamics from RNA-seq time series data. Bioinformatics(2016) 32 (19): 2965-2972.