Closed Krutik6 closed 1 year ago
Hi @Krutik6
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The DESCRIPTION file for this package is:
Package: SARC
Type: Package
Title: Statistical Analysis of Regions with CNVs
Version: 0.99.0
Authors@R: person(given = "Krutik", family = "Patel", role = c("aut", "cre"), email = "nkp68@newcastle.ac.uk", comment=c(ORCID="0000-0001-6806-8675"))
Description: Imports .cov files and .bed files from WES/ WGS CNV (copy number variation) detection pipelines and utilises several metrics to weigh the likelihood of a sample containing a detected CNV being a true CNV or a false positive. Highly useful for diagnostic testing to filter out false positives to provide clinicians with fewer variants to interpret. SARC uniquely only used COV and BED files which are the most common CNV pipeline calling filetypes, and can be used as an alternative to the Interactive Genome Browser (IGV), which can be especially helpful in large cohorts with 100s-1000s of patients.
Encoding: UTF-8
RoxygenNote: 7.2.3
License: GPL-3
Imports: tidyverse,
utils,
reshape2,
DescTools,
metap,
multtest,
plyranges,
data.table,
scales,
RColorBrewer,
grid,
gtable,
gridExtra,
GenomicFeatures,
stats,
ggplot2,
plotly,
IRanges,
GenomicRanges
Depends: R (>= 4.3),
MultiAssayExperiment
Suggests: TxDb.Hsapiens.UCSC.hg38.knownGene,
Homo.sapiens,
knitr,
kableExtra,
testthat
biocViews: Software,
CopyNumberVariation,
Visualization,
DNASeq,
Sequencing
VignetteBuilder: knitr
URL: https://github.com/Krutik6/SARC/
BugReports: https://github.com/Krutik6/SARC/issues
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Dear Package contributor,
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Congratulations! The package built without errors or warnings on all platforms.
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Overall, the package implementation is good but there are some issues which need to be addressed.
> test_bed # Why is second and third row exactly the same?
SAMPLE CHROM START END TYPE VALUE TOOL
1 Sample_616 chr1 161487763 161565521 DUP 1 exomeDepth
2 Sample_617 chr1 17034387 17090909 DEL 0 exomeDepth
3 Sample_617 chr1 17034387 17090909 DEL 0 exomeDepth
data
directory should contain .bed files, not .rda files of data frames claiming to be BED format.> SARC <- regionSet(bed = test_bed, test_cov)
> SARC
A MultiAssayExperiment object of 0 listed
experiments with no user-defined names and respective classes.
Containing an ExperimentList class object of length 0:
Please redesign it to use RaggedExperiment instead.
This package provides a flexible representation of copy number, mutation, and other data that fit into the ragged array schema for genomic location data.
The cov file should comprise of coverage from BAM files. These can be retrieved using SAMTOOLS or BCFTOOLs.
Please replace this by runnable code using coverage
function from GenomicAlignments applied to a BAM file in data folder.
The package advocates for comparing read coverage between different samples directly. This is not sensible. What if sample A has 50 million reads in total but sample B has 200 million reads in total? Read coverage is not a valid indicator of copy number unless it is scaled by the library size.
Function examples should not use library(packageName)
but check for presence of package installed. Please see Suggested Packages instructions for how to best load a package in an Examples section.
It is not clear if test data 1 and 2 are simulated data or experimental biological data. Please state the source of the data.
Unit tests are inadequate. For example, test_stats.R tests the number of columns and column names but not whether the expected genes are significantly different or not. Please test that the calculations of your algorithm are correct.
expect_equal(ncol(x), 13)
expect_equal(names(x)[12], "CNV.SCORE")
expect_equal(names(x)[13], "CNV.TIER")
All of the examples use data packages such as TxDb.Hsapiens.UCSC.hg38.knownGene
. Please comment on the applicability of SARC to other species such as Mus musculus. The generalisability of it should be explained in the vignette.
Cheers @DarioS. Will aim to address each point within 2-weeks. Krutik
Please remember to push to git.bioconductor.org to trigger a new build
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Received a valid push on git.bioconductor.org; starting a build for commit id: d62045379755eabe7fc3aade6a06a3bcfee3d3cc
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The following are build products from R CMD build on the Bioconductor Build System: macOS 12.6.5 Monterey: SARC_0.99.21.tar.gz Linux (Ubuntu 22.04.2 LTS): SARC_0.99.21.tar.gz
Links above active for 21 days.
Remember: if you submitted your package after July 7th, 2020,
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Dear Package contributor,
This is the automated single package builder at bioconductor.org.
Your package has been built on the Bioconductor Build System.
Congratulations! The package built without errors or warnings on all platforms.
Please see the build report for more details.
The following are build products from R CMD build on the Bioconductor Build System: Linux (Ubuntu 22.04.2 LTS): SARC_0.99.22.tar.gz macOS 12.6.5 Monterey: SARC_0.99.22.tar.gz
Links above active for 21 days.
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Dear @DarioS ,
Thank you for your comments, and apologies in the delay in resubmission - had github issues (thanks @lshep for helping with them). I believe this tool has been improved for the better of the users and the research community. I have listed the suggestions along with a response. Any minor additional changes have bee listed in the end of this response.
Please choose a more informative title for the vignette than "SARC_guide". See DESeq2 and batchelor for examples. Yes, this would be for the best. The title has been renamed to "Tutorial of the SARC R Package. Flagging the confidence of CNVs from WES/ WGS cohorts."
There are duplicate rows in test data file. Sorry this was a mistake - third row was from the tool clinCNV. This has been corrected for test_cnv and test_cnv2.
The example BED files do not conform to the BED file standard. Please do not redefine widely used bioinformatics file formats. Also, the data directory should contain .bed files, not .rda files of data frames claiming to be BED format.
You are correct - this would have just caused confusion. Instead, I have renamed these to cnv
files. I have mentioned that they are inspired by, and perform the same function as CNV .BED files, but are a different entity. I thought it would be simpler to create a specific class of file, rather than continue with claiming I had used .bed files - when I hadn't. Furthermore, I did prefer to keep .rda files because they could be compressed and were simple to call with data(x), so this was an all-round better solution I think.
The package only works with copy number variants. Why is MultiAssayExperiment used as the main data container? Please redesign it to use RaggedExperiment instead. I had used MAE because I was used to them - I have completely changed to RaggedExperiments now. This has also been explained in the vignette. I have altered the DESCRIPTION file to be dependant on RaggedExperiment instead and removed any mention of MultiAssayExperiments.
Please replace this by runnable code using coverage function from GenomicAlignments applied to a BAM file in data folder. I have added a small .bam and bam.bai file in the /inst/extdata folder and provided a small indication of how this could be used in the vignette. I did not wish to overburden the SARC vignette with another tool - so I have added the tutorials of GenomicAlignments. I have also added a link for bamsignals as I thought this was another good Bioconductor tool to perform a similair job.
The package advocates for comparing read coverage between different samples directly. This is not sensible. What if sample A has 50 million reads in total but sample B has 200 million reads in total? Read coverage is not a valid indicator of copy number unless it is scaled by the library size. I agree - at first I avoided normalisation as I thought this would skew very small variants, but after running some comparisons, this was a very useful comment. I have given an example in the vignette on how to normalise to RPM also, and mention several times that the data has been normalsed - and removed any mention of raw coverage.
Function examples should not use library(packageName) but check for presence of package installed. Please see Suggested Packages instructions for how to best load a package in an Examples section. I have altered this in the examples and the vignettes to instead use require or if (requireNamespace("X", quietly = TRUE)) {}
It is not clear if test data 1 and 2 are simulated data or experimental biological data. Please state the source of the data. Sorry - this was clinical data from our cohort. I have further anonymised this data and added some citations.
Unit tests are inadequate. For example, test_stats.R tests the number of columns and column names but not whether the expected genes are significantly different or not. Please test that the calculations of your algorithm are correct. Appologies - I have added further unit tests to check the maths and functions of the statistical functions.
All of the examples use data packages such as TxDb.Hsapiens.UCSC.hg38.knownGene. Please comment on the applicability of SARC to other species such as Mus musculus. The generalisability of it should be explained in the vignette. This is fair enough. I had intended this to be a clinical tool, but if it can help researchers working with model organisms, then I am happy to promote this. I have added a section at the end of the vignette to do just this.
Minor updates
New csv
dataframes will be stored as nested lists within the RaggedExperiment object. To avoid removing older dataframes, users will have the option to rename the new dataframes that are being nested.
Added new parameter to fix a plotting bug where the log flag not having a logbase as a parameter.
Thank you for your comments, again this tool has been improved for the better I think. Please communicate any other issues - or indadequate changes and I will try to respond promptly.
Thank you for the significant updates to SARC. I have a few minor remaining issues to raise.
Don't use require
in the vignette for code users will run, but do use library
. require()
is usually only used if you are loading packages inside a function so that the function will continue to execute after warning, if a package doesn’t exist.
RStudio automatically does spell-check and underlines potential mistakes. Please fix whichever underlining is relevant.
x <- coverage(x = "../inst/extdata/test.bam")
is error unless user's working directory is the package directory. Please do it more robustly, such as system.file("extdata", "test.bam", package="SARC")
The paths elsewhere also need updating for robustness.
load(file ="../inst/extdata/test_cov_raw.rda")
load(file ="../inst/extdata/librarySizes.rda")
The for
loop in the vignette is unnecessary and can be done with vectorisation. Please verify that
t(t(test_cov[, 5:ncol(test_cov)]) / libsizes$PerMillion)
gives the same result as the for
loop, but does it more concisely and is vectorised.
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The following are build products from R CMD build on the Bioconductor Build System: macOS 12.6.5 Monterey: SARC_0.99.23.tar.gz Linux (Ubuntu 22.04.2 LTS): SARC_0.99.23.tar.gz
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Hi @DarioS, I have made some more updates on the package which I will list here.
Sorry I could not find the function library. require()
, so instead just used library()
in the vignette. Hope this is sufficient.
Thanks - I have done this now on the vignette, all R function scripts and test scripts.
You were right to comment on this - thanks for catching the potential bugs that would occur. All calls from extdata
are now called using system.file()
.
Yes it gave almost the same result, minus a few columns which were easily re-added. I used this instead of the forloop.
The package has been substantially improved and will be good member of the Bioconductor ecosystem.
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Thanks for all the help @DarioS and @lshep :) Hopefully it will help bioinformaticians with CNV data.
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