Athurva Gore/LabNotes/2010-3-24
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Plan for Today[edit]
- Indel calling - run scripts
- CV-iF/CV-F and DF6/FS Exome data
- Nimblegen data (whatever is available)
- BSPP Neural Network
- Assemble Cpg97k data, BS_FirstExon data; see how this NN looks
IPS Mutation Paper[edit]
Indel Calling[edit]
Data to assemble[edit]
Flowcell
|
CV-F
|
CV-iF
|
DF6
|
FS
|
HL020 |
s3, s4 |
s1, s2 |
|
|
HL022 |
|
|
s1, s2 |
s3, s4
|
HL023 |
|
|
s5, s6 |
s7, s8
|
HL025 |
s6 |
s7 |
|
|
HL026 |
s1 |
s5 |
s6 |
s7
|
HL036 |
|
|
s1 (NimbleGen) |
s4 (NimbleGen)
|
HL037 |
|
|
s3 (NimbleGen) |
s8 (NimbleGen)
|
Procedure[edit]
- Merged CV-iF, CV-F, DF6, and FS
- Running mapping+velvet script on CV-iF and CV-F
- Still need to merge NimbleGen data
CNV-Seq[edit]
- Can we use Exome data to find CNV variation?
- Theoretically, bias in probeset should be uniform
- May not be true in practice
- Once CV-F and CV-iF data is finished sorting (should be a couple hours), try CNV algorithm on it
- Perhaps rather than trying to compare windows, we should compare the number of reads that map to each exon...
- Variable size, can we model it properly?
BSPP Neural Network[edit]