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# MethodsTBS

Targeted Bisulfite Sequencing for Biomarker Discovery

## Processing Scripts

- Scripts for processing targeted bisuflite sequencing data written for use with SGE cluster environment
  - Adapter Trimming
  - Indexing
  - Read alignment
  - Methylation Calling

## Analysis Notebooks

- Jupyter notebook describing
  - Quality Control Pipeline
  - Fitting Epigenetic Clock Using Targeted Bisulfite Sequencing Data

## Targeted Bisulfite Sequencing QC

The code to produce the following graphs is contained in the QC jupyter notebook. The goal of the QC analysis is to
assess alignment performance by looking at general alignment statistics, the number of reads mapping to regions
targeted by the probes, and the observed duplication rate.

### Alignment QC

We can start assessing alignment quality by looking at the output logs generated by the alignment tool
[BSBolt](https://bsbolt.readthedocs.io/en/latest/). The alignment log give information on the total number of read pairs
observed, the bisulfite strand where reads mapped, and the number of unmapped reads / bisulfite ambiguous alignments. The
mappability is calculated as $mappability = 2 * total read pairs - unmapped reads$.



Using *bedtools multicov* we will investigate the average number of reads that map to the targeted regions. The coverage
shown is plotted for all mapped reads and mapped reads with duplicates removed.



Using *samtools flagstat* we can investigate the alignment file by looking at the sam flags set for each read. Sam flags are bitwise combination of different alignment attributes. Coverage information taken from the *bedtools multicov* has been combined
with the *flagstat* output to provide additional details.



	a/README.md		b/README.md
1	# MethodsTBS	1	# MethodsTBS
2		2
3	Targeted Bisulfite Sequencing for Biomarker Discovery	3	Targeted Bisulfite Sequencing for Biomarker Discovery
4		4
5	## Processing Scripts	5	## Processing Scripts
6		6
7	- Scripts for processing targeted bisuflite sequencing data written for use with SGE cluster environment	7	- Scripts for processing targeted bisuflite sequencing data written for use with SGE cluster environment
8	- Adapter Trimming	8	- Adapter Trimming
9	- Indexing	9	- Indexing
10	- Read alignment	10	- Read alignment
11	- Methylation Calling	11	- Methylation Calling
12		12
13	## Analysis Notebooks	13	## Analysis Notebooks
14		14
15	- Jupyter notebook describing	15	- Jupyter notebook describing
16	- Quality Control Pipeline	16	- Quality Control Pipeline
17	- Fitting Epigenetic Clock Using Targeted Bisulfite Sequencing Data	17	- Fitting Epigenetic Clock Using Targeted Bisulfite Sequencing Data
18		18
19	## Targeted Bisulfite Sequencing QC	19	## Targeted Bisulfite Sequencing QC
20		20
21	The code to produce the following graphs is contained in the QC jupyter notebook. The goal of the QC analysis is to	21	The code to produce the following graphs is contained in the QC jupyter notebook. The goal of the QC analysis is to
22	assess alignment performance by looking at general alignment statistics, the number of reads mapping to regions	22	assess alignment performance by looking at general alignment statistics, the number of reads mapping to regions
23	targeted by the probes, and the observed duplication rate.	23	targeted by the probes, and the observed duplication rate.
24		24
25	### Alignment QC	25	### Alignment QC
26		26
27	We can start assessing alignment quality by looking at the output logs generated by the alignment tool	27	We can start assessing alignment quality by looking at the output logs generated by the alignment tool
28	[BSBolt](https://bsbolt.readthedocs.io/en/latest/). The alignment log give information on the total number of read pairs	28	[BSBolt](https://bsbolt.readthedocs.io/en/latest/). The alignment log give information on the total number of read pairs
29	observed, the bisulfite strand where reads mapped, and the number of unmapped reads / bisulfite ambiguous alignments. The	29	observed, the bisulfite strand where reads mapped, and the number of unmapped reads / bisulfite ambiguous alignments. The
30	mappability is calculated as $mappability = 2 * total read pairs - unmapped reads$.	30	mappability is calculated as $mappability = 2 * total read pairs - unmapped reads$.
31		31
32	![png](imgs/bsb_alignment_log_stats.png)
33
34	Using bedtools multicov we will investigate the average number of reads that map to the targeted regions. The coverage	32	Using bedtools multicov we will investigate the average number of reads that map to the targeted regions. The coverage
35	shown is plotted for all mapped reads and mapped reads with duplicates removed.	33	shown is plotted for all mapped reads and mapped reads with duplicates removed.
36		34
37	![png](imgs/bedtools_multicov.png)
38
39	Using samtools flagstat we can investigate the alignment file by looking at the sam flags set for each read. Sam flags are bitwise combination of different alignment attributes. Coverage information taken from the bedtools multicov has been combined	35	Using samtools flagstat we can investigate the alignment file by looking at the sam flags set for each read. Sam flags are bitwise combination of different alignment attributes. Coverage information taken from the bedtools multicov has been combined
40	with the flagstat output to provide additional details.	36	with the flagstat output to provide additional details.
41
42	![png](imgs/sam_flagstat.png)