Update manta FILTER=='PASS' Part2 : gene annotated cnv file generation

[kgaonkar6]

Purpose/implementation Section

What scientific question is your analysis addressing?

Rerun for focal-cn-file-preparation after manta FILTER==PASS update in copy_number_consensus_call

What was your approach?

Rerun

What GitHub issue does your pull request address?

#1113

Directions for reviewers. Tell potential reviewers what kind of feedback you are soliciting.

Which areas should receive a particularly close look?

NA

Is there anything that you want to discuss further?

NA

Is the analysis in a mature enough form that the resulting figure(s) and/or table(s) are ready for review?

Yes

Results

What types of results are included (e.g., table, figure)?

tables

What is your summary of the results?

Since we are investigating chr XY in detail here's the distribution of status in each version of consensus_seg_annotated_cn_x_and_y.tsv.gz . We see that after updated for FILTER==PASS we drastically reduce the number of deep deletions:

# consensus_seg_annotated_cn_x_and_y.tsv.gz from this rerun
> anno_xy_consensus_cnv$status %>% table()
.
deep deletion          gain          loss 
          764          3314         39715 

# consensus_seg_annotated_cn_x_and_y.tsv.gz from master
> anno_xy_consensus_cnv_master$status %>% table()
.
deep deletion          gain          loss 
        10766          3946         42374 

Reproducibility Checklist

• The dependencies required to run the code in this pull request have been added to the project Dockerfile.
• This analysis has been added to continuous integration.

Documentation Checklist

• This analysis module has a README and it is up to date.
• This analysis is recorded in the table in analyses/README.md and the entry is up to date.
• The analytical code is documented and contains comments.

[jharenza]

looks good to me