Process SMRT sequencing kinetic summary to predict regional methylation on large genome
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Latest commit cd3745c Jul 18, 2018


This project was designed and tested with RSII platform, and does not have appropriate parameters working well with Sequel data currently. I'm planning to upgrade the whole project to catch up with the latest platform and reagents, as there is no reason to expect that the concept expanded here cannot applicable to them. If you want to analyse CpG methylome in large genomes using AgIn, I appreciate your patience. Thank you.


$ git clone git:// AgIn

Demo files are available at

Analyse your data

AgIn tries to detect CpG methylated/unmethylated regions on a specified reference genome from PacBio sequencing data of read coverage as low as 20x. The program requires a modification.csv file as a primary input, which is produced by P_ModificationDetection module of SMRT Pipe, with your intended reference file (use the same reference file throughout the analysis, for SMRT Pipe and for AgIn). Then run as:

$ target/dist/bin/launch -i path/to/modifications.csv -f path/to/reference.fasta -o output_prefix -b vector_specifier -g gamma -l min_length predict

It'll give three output files:


The program assumes the index file for the reference (.fai generated by samtools) is placed in the same directory as the reference.

The parameters for prediction

-b : File containing a vector for decision hyperplane. For P6-C4, use resource/P6C4.dat. For old data, either P5C3_HdrR (for P5-C3 sequencing), or LDAVector (for P4-C2 and C2-C2 sequencing).

-l : Minimum number of CpG sites the predicted regions must contain. Smaller value gives you better resolution with possibly worse accuracy. ()

-g : Decision threshold which controls the sensitivity/specificity trade-off.

Recommended (standard) combinations of parameters are: -b resource/P6C4.dat -g -0.55 -l 40 (for P6-C4) -b P5C3_HdrR -g -0.88 -l 40 (for P5-C3) -b LDAVector -g -1.80 -l 40 (for P4-C2 or C2-C2)

Output files

The GFF file reports all the predicted hypomethylated regions.

_class.wig file describes the predicted class (0 for unmethylated, 1 for methylated) of each CpG site.

_coverage.wig file describes the effective coverage used for making the prediction. (i.e., # of IPD ratio measurements on 21 bases around the CpG site / 21.0 )


Copyright of this program AgIn is held by Yuta Suzuki ( (effective to 3/31/2017), and is distributed under the (modified) BSD license.

Copyright of src/script/launch and some other scripts is held by Taro L. Saito( and licensed under Apache License Version 2.0 (