Part1: Freec as default and neutral NA

[kgaonkar6]

⚠️ This is a re-do of #987

Purpose/implementation Section

What scientific question is your analysis addressing?

According to Bo's rationale since ploidy is based on ControlFREEC using its corresponding CN would probably result in a better estimate of overall CN.

What was your approach?

Just a change in

OpenPBTA-analysis/analyses/copy_number_consensus_call/scripts/bed_to_segfile.R

Lines 119 to 128 in 2c1f5fa

	# Calculate summary stats from merged CNV calls. \
	cnvs <- cnvs %>%
	dplyr::mutate(cnvkit_df = purrr::map(cnvkit_CNVs, segstrings_to_df),
	freec_df = purrr::map(freec_CNVs, segstrings_to_df),
	segmean = purrr::map_dbl(cnvkit_df, segmean_function),
	cnvkit_cn = purrr::map_dbl(cnvkit_df, copies_wmedian),
	freec_cn = purrr::map_dbl(freec_df, copies_wmedian),
	copynum = ifelse(is.finite(cnvkit_cn), # use cnvkit if available
	cnvkit_cn, freec_cn), #otherwise use freec
	num.mark = NA)

to use controlfreec if available if not use cnvkit:

                copynum = ifelse(is.finite(freec_cn), # use freec if available
                                 freec_cn, cnvkit_cn), #otherwise use cnvkit

What GitHub issue does your pull request address?

#964

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

Which areas should receive a particularly close look?

NA, it is just a 1 line code update

Is there anything that you want to discuss further?

Note: I have not added any downstream modules ( like I did in #987) in this PR since those downstream analysis are just re-runs and can come in after this PR is merged to master.

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?

Here I'm comparing ( consensus_seg_annotated_cn_autosomes.tsv.gz + consensus_seg_annotated_cn_x_and_y.tsv.gz ) from the following versions of the files

• controlfreec (default for copy number ) + neutral calls as NA
• cnvkit (default for copy number) + neutral calls as NA
• and v18 release
  

The changes between using controlfreec and cnvkit are mainly as follows:

• BS_ZSH09N84 and BS_CBMAWSAR are initial samples from the same participant PT_MNSEJCDM, controlfreec calls EGFR and MET gains in both samples, cnvkit only calls in BS_ZSH09N84
• BS_JRFVST47 and BS_3Z40EZHD are initial samples for PT_9GKVQ9QS, controlfreec calls MET gain in both samples , cnvkit only calls for BS_3Z40EZHD
• Other than the above calls being missed, we also see some copy change level changes in KIT,KDR and PDGFRA calls where ,controlfree calls amplification for BS_JRFVST47 and cnvkit shows as gains; for BS_3Z40EZHD cnvkit shows as amplification and controlfreec shows as gains.

My underdstanding is controlfreec helps identifying consistent calls for multiple samples from the same participant ids where as cnvkit seems to be missing the call for 1 of the 2 multiple samples in the participants mentioned above.

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.

[jaclyn-taroni]

👍🏻 approving on the basis of discussion #1010 + the code does what is described in #964 and #1010! (I did not look at the SEG file.)

[kgaonkar6]

I have not added any downstream modules ( like I did in #987) in this PR since those downstream analysis are just re-runs and can come in after this PR is merged to master.