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algorithms 2015-06-18
main.cpp 2015-06-18 2.1 kB
Makefile 2015-06-18 1.6 kB
public_func.cpp 2015-06-18 638 Bytes
public_func.h 2015-06-18 364 Bytes
public_parameters.h 2015-06-18 3.6 kB
ReferenceSeq.cpp 2015-06-18 2.6 kB
ReferenceSeq.h 2015-06-18 1.1 kB
SplicingJumper_1 2015-06-18 230.7 kB
TrainingSet.cpp 2015-06-18 3.0 kB
TrainingSet.h 2015-06-18 479 Bytes
Alignment.h 2015-06-18 954 Bytes
bam_alignment_record.h 2015-06-18 4.7 kB
bam_header_record.h 2015-06-18 3.7 kB
bam_parse.cpp 2015-06-18 6.7 kB
bam_parse.h 2015-06-18 1.6 kB
CandidateSitesCaller.cpp 2015-06-18 26.4 kB
CandidateSitesCaller.h 2015-06-18 3.6 kB
Coverage.cpp 2015-06-18 16.8 kB
Coverage.h 2015-06-18 1.3 kB
fai_parser.cpp 2015-06-18 1.4 kB
fai_parser.h 2015-06-18 557 Bytes
fasta_parser.cpp 2015-06-18 3.2 kB
fasta_parser.h 2015-06-18 812 Bytes
HardClipReads.cpp 2015-06-18 9.7 kB
HardClipReads.h 2015-06-18 229 Bytes
JunctionCaller.cpp 2015-06-18 2.8 kB
JunctionCaller.h 2015-06-18 876 Bytes
khash.h 2015-06-18 18.8 kB
kseq.h 2015-06-18 8.7 kB
Alignment.cpp 2015-06-18 5.2 kB
Totals: 31 Items   364.1 kB 1
Usage: ./SpliceJumper [options] 

Required options:
									-P/G        indicates collecting features / indicates output results 
                  -r FILE   reference file(indexed)
                  -b/i FILE   input bam/prediction file(index and sorted)
                  -o FILE   output file name
                  -l INT    read length
Optimal options
                  -c INT    slack value for split position with default 3
                  -m DOUBLE mean insert size
                  -v DOUBLE standard variation of insert size
                  
1.Feature collection:
./SpliceJumper -P -r ./human_g1k_v37.fasta -b ./simulated_data_input.bam -o test_sim.txt -l 100 -c 5

2. Training and prediction
2.1 Training
python easy.py training_data

2.2 Predicting
..\windows\svm-predict data.scale Trained.model predictResult

3. Output generated splicing junctions
./SpliceJumper -G -i prediction.txt -o result.txt
Source: readme.txt, updated 2015-06-18