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In Detail: WGBS pipeline

  • Updated

Description

The current Methyl-seq pipeline available on Genialis Expressions uses WALT (Wildcard ALignment Tool) aligner. Methylation levels at each genomic cytosine is calculated using methcounts. Finally, hypo-methylated regions are identified using hmr. Both methcounts and hmr are part of the MethPipe package. 

Analysis steps include trimming (BBDuk), mapping (WALT), and methylation level quantification (methcound and hmr). Reference genomes for mouse, rat, or human (Ensembl, version 100 and 92) are extended with references for common spike-in standards (ERCC and SIRV). Results are reported in the summary table of the MultiQC report.

 

Pipeline Details - Tools and Parameters

Unless stated otherwise, all parameter values are set to tool defaults.

 

Reads a trimmed using BBDuk (BBMap 37.90, Bushnell, 2018)

Read alignment using WALT (1.01)

Clicking on the WALT (Wildcard Alignment Tool) object will take you to the data details page. There, you will see the inputs that were used in the process and the outputs that were generated:

  1. Alignment file (BAM)
  2. Index BAI
  3. Statistics 
  4. BigWig file
  5. Alignment file (MR)
  6. Unmapped reads
  7. Alignment file of unmethylated control reads
  8. Species
  9. Build

Methylation using Mathcounts (Methpipe 3.4.3)

The methcounts process, (part of Methpipe) takes the mapped reads and produces the methylation level at each genomic cytosine, with the option to produce only levels for CpG-context cytosines. Clicking on the methcounts object will take you to the data details page. There you will see the inputs that were used in the process as well as the outputs that were generated:

  1. Methylation levels
  2. Statistics
  3. Methylation levels BigWig file
  4. Species
  5. Build

Hypomethylation using Hmr (Methpipe 3.4.3)

Clicking on the hmr object, you will see the inputs that were used in the process as well as the outputs that were generated:

  1. Hypo-methylated regions
  2. Bed file index for Jbrowse
  3. Species
  4. Build

Statistics using Picard tools (2.8.1+dfsg-3)

Picard AlignmentSummary 

The Picard AlignmentSummary process outputs statistics to assess the alignment.

  1. Alignment metrics

Picard WGS Metrics

The Picard WGS metrics process outputs statistics for evaluating the performance of whole genome sequencing experiments. This collects metrics about % of reads that pass base- and mapping- quality filters as well as coverage levels. 

  1. WGS metrics report

Picard CollectRrbsMetrics

The CollectRrbsMetrics process produces metrics for RRBS data based on the methylation status. This tool uses reduced representation bisulfite sequencing (Rrbs) data to determine cytosine methylation status across all reads of a genomic DNA sequence.

  1. RRBS summary metrics
  2. Detailed RRBS report
  3. QC plots
  4. Species
  5. Build

Picard InsertSizeMetrics

The Picard InsertSizeMetrics process collects metrics about the insert size and read orientation of a paired-end library. 

  1. Insert size metrics
  2. Insert size histogram 

References

Bushnell, B. (2018) https://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/bbduk-guide/ (accessed on  2018-06-20). Joint Genome Institute

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