BS-Seeker2

A versatile aligning pipeline for bisulfite sequencing data

Documents | Release Log | Q&A | Source Code | Tutorial ㊥ | Jan. 3rd, 2018 Updated

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Archived versions:

V2.1.5 | V2.1.3 | V2.1.2

NOTICE
The newest version (V2.1.0) has been tested on python v2.7 and pysam v0.9+/v0.8; and python v2.7 and pysam v0.75
For BS-Seeker2 older versions, if you notice pysam related problem, please try a older pysam version, such as pysam v0.6.

News
A new software package CGmapTools is now recommended, for the seamless downstream analysis following BS-Seeker2.

Features

  • WGBS / RRBS
  • single-end / paired-end
  • Local / gapped alignment
  • Galaxy
  • Input formats
    • Fasta
    • Fastq
    • qseq
    • pure sequence
  • Output formats
    • BAM
    • SAM
    • BS_Seeker
See more from here

"How can I use BS-Seeker2?"

"Can you give me some examples to start with BS-Seeker2?"

Sure! But you should know that our BS-Seeker2 is very versatile, and you can make a better use of it by reading more about the help information.

1. Build the index

# WGBS, using bowtie2 (path of bowtie should be included in $PATH)

python bs_seeker2-build.py -f genome.fa

# RRBS, using bowtie

python bs_seeker2-build.py -f genome.fa --aligner=bowtie -p ~/install/bowtie/ -r

# RRBS, with fragment lengths ranging [40bp, 400bp]

python bs_seeker2-build.py -f genome.fa -r -l 40 -u 400

# RRBS for double-enzyme : MspI (C'CGG) and ApeKI (G'CWGC)

python bs_seeker2-build.py -f genome.fa -r -c C-CGG,G-CWGC

2. Map the reads

# WGBS, FASTA, bowtie2 (local alignment), allowing 3 mismatches

python bs_seeker2-align.py -i WGBS.fa -m 3 --aligner=bowtie2 -o WGBS.bam -f bam -g genome.fa

# RRBS, FASTQ, bowtie, output as SAM

python bs_seeker2-align.py -i RRBS.fq --aligner=bowtie -o RRBS.sam -f sam -g genome.fa -r -a adapter.txt

# RRBS, QSEQ, bowtie2 (end-to-end alignment), fragment lengths ranging [40bp, 400bp]

python bs_seeker2-align.py -i RRBS.qseq --aligner=bowtie2 --bt2--end-to-end -o RRBS.bam -f bam -g genome.fa -r --low=40 --up=400 -a adapter.txt

# Paired-end, QSEQ, bowtie, report concordant reads, and remap the unmapped reads in single-end mode

# Output the unmapped reads in PE mode
bs_seeker2-align.py -1 FN1 -2 FN2 -g genome.fa -o PE.bam -u unmapped
# Map the unmapped reads in mate 1
bs_seeker2-align.py -i unmapped_1.fa -g genome.fa -o unmapped_1.bam
# Convert the unmapped reads in mate 2 to their reverse complementaries
Antisense.py -i unmapped_2.fa -o unmapped_2_antisense.fa
# Map the unmapped reads in mate 2
bs_seeker2-align.py -i unmapped_2_antisense.fa -g mm9_phage.fa -o unmapped_2.bam # Merge all the mapped results
samtools merge merge.bam PE.bam unmapped_[12].bam

3. Call the methylation levels

# WGBS, bowtie

python bs_seeker2-call_methylation.py -i WGBS.bam -o output --db /path/to/BSseeker2/bs_utils/reference_genomes/genome.fa_bowtie/

# RRBS, bowtie2, fragment lengths ranging [40bp, 400bp]

python bs_seeker2-call_methylation.py -i RRBS.bam -o output --db /path/to/BSseeker2/bs_utils/reference_genomes/genome.fa_rrbs_40_400_bowtie2/

# RRBS, bowtie2, removing the incomplete bisulfite converted reads

python bs_seeker2-call_methylation.py -x -i RRBS.bam -o output --db /path/to/BSseeker2/bs_utils/reference_genomes/genome.fa_rrbs_40_500_bowtie2/

# RRBS, only show sites covered by at least 10 reads in WIG file

python bs_seeker2-call_methylation.py -r 10 -i RRBS.bam -o output --db /path/to/BSseeker2/bs_utils/reference_genomes/genome.fa_rrbs_40_500_bowtie2/

     

Need more information?

- Document of BS-Seeker2 .

- Question and Answer (Q&A).

- Output formats o of BS-Seeker2.

- The LOGS for releases

Do a fast test using BS-Seeker2?

We provide a small Data set for fast testing purpose, which is in the "test_data" folder. Or you can download them from here .

Contact:

Please contact Weilong Guo if you have any question.
Email : guoweilong[aite]126.com ( Please replace "[aite]" by @ )

Citation:

Guo W, Fiziev P, Yan W, Cokus S, Sun X, Zhang MQ, Chen P, Pellegrini M. (2013). BS-Seeker2: a versatile aligning pipeline for bisulfite sequencing data. BMC Genomics, 14(1), 774. doi:10.1186/1471-2164-14-774

Datasets for paper:

  1. DS1_WGBS_simu_perfect.fa
  2. DS2_PE_simu_perfect_end1.fa and DS2_PE_simu_perfect_end2.fa
  3. DS3_RRBS_simu_perfect.fa
  4. DS5_PE_simu_error_end1.fa and DS5_PE_simu_error_end2.fa
  5. DS4_WGBS_simu_error.fa
  6. DS6_RRBS_simu_error.fa
  7. DS7_WGBS_real.fa
  8. DS8_PE_real_end1.fa and DS8_PE_real_end2.fa
  9. DS9_RRBS_real.fa
  10. DS10_Phage_spikein.qseq
  11. DS11_Sample_A.qseq
  12. DS12_Sample_B.qseq

Other link :

BS Seeker

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