Releases: broadinstitute/carmen-analysis
v4.4.4
v4.4.3
v4.4.2
v4.4.1
Highlights of the 4.4.1 release
- Software updated for compatibility with latest Python version 3.13.1. All packages in requirements.txt file have been updated to their latest version.
- For user’s convenience, the software version is now appended to the output folder of the analyzed results.
v4.4.0
Highlights of the 4.4.0 release:
Two issues resolved:
- Previously, the RESULTS spreadsheet was generated only if the Legend was generated to flag any NTC contamination, sample invalidity, or RNaseP negativity. Now, the RESULTS spreadsheet is generated consistently, regardless of whether any flags have been added to the results.
- The no_crRNA negative viral assay control has been modified to no longer be flagged as an INVALID assay.
v4.3.9
Highlights of the 4.3.9 release:
This release includes an updated version of the README, which informs the user that the Google Drive folder containing the Assignment Sheet templates also now contains a SAMPLE Assignment Sheet denoting the required controls and panel-specific formatting.
v4.3.8
Official 4.3.4 Release Notes
Highlights of the 4.3.4 release:
This release introduces several key updates to the quality control (QC) tests and output files, specifically to ensure that the flags from the QC tests are easily interpretable when reviewing the output files. The goal of these updates is to improve data readability in the Results files, allowing for more effective quality control checks and better-informed decision-making.
The results spreadsheets (found in the RESULTS sub-folder in pipeline outputs) now contains a single Excel file with five sheets containing the following results: ‘CARMEN_Hit_Results’, ‘NTC_Normalized_Quant_Results’, ‘Summary_of_Positive_Samples’, ‘NTC_thresholds’, and ‘Binary_Results’. Specific flags for quality control have been incorporated into these results files: * denote invalid assays, ** denote invalid samples, *** denote samples which test negative for the human internal control RNaseP assay, and † denote No Target Control samples which are removed from the analysis due to appearing as potentially contaminated.
Assays are invalidated based on failing the CPC QC Test (#3). CPC (Combined Positive Control) failure testing has been improved to accommodate testing of RVP, BBP Panel #1, and BBP Panel #2 on the same chip. Users are now asked to denote “_RVP”, “_P1”, or “_P2” to the suffix of each assay and each CPC sample in the Assignment Sheet.
Samples are invalidated based on testing positive for the no-crRNA (negative control) assay.
The NTC Normalized heatmap has been enhanced for better visibility and also contains QC flags, NTC contamination, invalid assays, and invalid samples.
Full list of changes:
RESULTS_{IFC Barcode #}.xlsx:
A single Excel spreadsheet called RESULTS_{IFC Barcode #}.xlsx contains 5 sheets called ‘CARMEN_Hit_Results’, ‘NTC_Normalized_Quant_Results’, ‘Summary_of_Positive_Samples’, ‘NTC_thresholds’, and ‘Binary_Results’. The sheet ‘CARMEN_Hit_Results’ now is color-coded, where negative results are in GREEN and positive results are both in RED and bold. The sheets ‘NTC_Normalized_Quant_Results’ and ‘Binary_Results’ show the results for the positive samples both in RED and bold.
NTC Normalized Heatmap Updates:
Gridlines have been added to the heatmap between samples for improved visibility. Given the improved CPC test (described below), results for each CPC sample are plotted only for their relevant panel (i.e. Results for CPC sample for BBP Panel #1 are only plotted for BBP Panel #1 assays).
NTC Contamination Handling:
A detailed explanation of what happens when NTCs are contaminated has been included in the Quality Control Report. If an NTC probe signal exceeds 0.5 au, it is considered contaminated and removed from the analysis. Contaminated NTCs are marked with hashes on the heatmap. If all NTCs in a run are contaminated, the last NTC’s signal is replaced with 0.5 au and marked with an asterisk.
The files affected by this edit are listed below. These files have been modified to include a dagger symbol (†) indicating that the NTC sample was removed due to contamination, with an explanation below.
- ‘CARMEN_Hit_Results’
- ‘NTC_Normalized_Quant_Results’
- ‘Binary_Results’
CPC Failures:
Modifications made to ensure that the CPC validity check works when running multiple panels on the same chip. The CPC test now checks each panel-specific CPC if users have labeled them as CPC_RVP, CPC_P1, and CPC_P2 in their Assignment Sheet. This ensures that the CPC test works as expected even when running multiple panels simultaneously on a chip. If an assay fails the CPC check, it is considered invalid marked with a single asterisk () followed by an explanation below.
The files affected by this edit are listed below. These files have been modified such that invalid assays that fail the CPC check are marked with single asterisk () followed by an explanation below.
- ‘CARMEN_Hit_Results’
- ‘NTC_Normalized_Quant_Results’
- ‘Summary_of_Positive_Samples’
- ‘NTC_thresholds’
- ‘Binary_Results’
No-crRNA Check:
This is a new test added to assess sample validity. Thus, a column called “Sample Valid? Y/N” to the relevant Results files indicating whether a sample has passed or failed the no-crRNA test. A sample is considered invalid if it has tested negative for the included negative control no-crRNA assay.
The files affected by this edit are listed below. These files have been modified such that invalid samples are marked with triple asterisks (***) with a No in the “Sample Valid? Y/N” column, followed by an explanation below.
- ‘CARMEN_Hit_Results’
- ‘NTC_Normalized_Quant_Results’
- ‘Summary_of_Positive_Samples’
- ‘Binary_Results’
RNaseP Check:
Samples that are negative for the human internal control RNaseP are now flagged with two asterisks (**) followed by an explanation below. Users are directed to read the Quality Control Report.
The files affected by this edit are listed below.
- ‘CARMEN_Hit_Results’
- ‘NTC_Normalized_Quant_Results’
- ‘Summary_of_Positive_Samples’
- ‘Binary_Results’
NTC Thresholds for Normalized Results:
The pipeline now outputs both NTC threshold and NTC normalized thresholds, which are reflected in the sheet “NTC Thresholds” in the RESULT Excel file.
v4.1.0
Highlights of the 4.1.0 release:
Previously, the 3_SD threshold did not account for potential NTC contamination. In this release, this issue has been resolved and the standard deviation is calculated, per assay, for only the NTCs that have passed the contamination check.
Previously, the Negative & Positive Quality Control Checks produced empty csv files as the output upon the absence of sample or assay flags. In this release, in the absence of a sample or assay-level flag, the Check produces a csv file containing a message informing the users of this conclusion.
Previously, the outputs folder contained all outputs in one location. In this release, the outputs folder has been re-organized into three sub-folders - RESULTS_{IFC_barcode}, R&D_{IFC_barcode}, and QUALITY_CONTROL_{IFC_barcode). The user can explore the desired output based on their analysis needs.
Full list of changes:
- Fixed input to threshold.py to be assigned_signal_norm_with_NTC_check.csv
- Built Assay-Level QC Test Explanation file
- Built PDF generator when running the quality control fags for the Positive and Negative Controls
v3.3.1
v3.3.0
Highlights of the 3.3.0 release:
Previously, the quality control flags produced a single text file that described the samples which had failed to test positive for RNaseP, the assays which had failed to test positive for the CPC positive control, and the assays which had failed to test negative for the NTC and NDC negative controls. In this release, the quality control flags have been converted into tabular outputs in the form of four additional csv files that contain the list of flagged samples (for the RNaseP evaluation) and flagged assays (for the CPC, NDC, and NTC evaluations). A text file describing the results and their initial interpretation is still produced. This modification enables streamlined comparison of results across experiments to fortify diagnostic surveillance in point-of-need capacities.