Please visit this page once you have done things necessary here: https://mskcc.github.io/on-boarding/
The best place to start is to learn more about MSK-ACCESS and for that please read the paper:
Learn more about the current collapsing method Marianas
Learn more about the Quality Control V1
Understand the updated version for the above using these Quality Control V2
Learn about ACCESS Data analysis scripts that help with downstream analysis
Learn about IGV for viewing BAM files to distinguish real variants from artifacts
Below are resources that would be handy for you to learn more about all the tools described in the paper.
MSK-ACCESS
CMO-CH
CMO Cell-Free Informatics (CCI)
MSK-ACCESS V1 (Marianas)
CCI organization on Github
cBioPortal DMP data
Quality Control for ACCESS V1
Downstream analysis of ACCESS Data
Fingerpriting using Biometrics
High Performance Computing
Nucleo (Fgbio)
Quality Control for ACCESS V2
BAM
/juno/work/access/production/data/bams/{cmo_patient_id}/{cmo_sample_id}/current/
Small Variant (SNV’s/INDEL’s)
/juno/work/access/production/data/small_variants/{cmo_patient_id}/{cmo_sample_id}/current/
Microsatellite Instability(MSI)
/juno/work/access/production/data/microsatellite_instability/{cmo_patient_id}/{cmo_sample_id}/current/
Structural Variant (SV)
/juno/work/access/production/data/structural_variants/{cmo_patient_id}/{cmo_sample_id}/current/
Copy Number Variants (CNV)
/juno/work/access/production/data/copy_number_variants/{cmo_patient_id}/{cmo_sample_id}/current/
NYS validation data
/work/access/production/runs/NYS_validation/current
CMO-ACCESS
/work/access/production/
/work/access/production/resources/
CMO-CH
/work/ch/
Berger Lab
/work/bergerm1/bergerlab
admie
- Files used for microsatellite instability detection tool ADMIE for MSK-ACCESS
cosmic
- VCF file of cosmic used in MSK-ACCESS workflows
dbSNP
- VCF file of dbSNP used in MSK-ACCESS workflows
exac
- VCF file of ExAC used in MSK-ACCESS workflows
mills-and-1000g
- VCF file of mills-and-1000g used in MSK-ACCESS
reference
- reference genome file used in MSK-ACCESS workflows
tools
- general packages used in MSK-ACCESS workflows
msk-access
- Data-specific resources for MSK-ACCESS workflows. This includes the following:
hiseq4000_curated_duplex_bams_dmp
- curated DMP duplex BAMS from HiSeq 4000
novaseq_curated_simplex_bams_dmp
- curated DMP simplex BAM from NovaSeq.
hiseq4000_curated_simplex_bams_dmp
- curated DMP simplex BAM from HiSeq 4000
novaseq_curated_standard_bams_dmp
- curated DMP standard BAM from NovaSeq
hiseq4000_curated_standard_bams_dmp
- curated DMP standard BAM from HiSeq 4000
novaseq_curated_unfiltered_bams_dmp
- curated DMP unfiltered BAM from NovaSeq
hiseq4000_curated_unfiltered_bams_dmp
- curated DMP unfiltered BAM from HiSeq 4000
novaseq_unmatched_normal_plasma_duplex_bams_dmp
- DMP unmatched normal plasma duplex BAM from NovaSeq
hiseq4000_unmatched_normal_plasma_duplex_bams_dmp
- DMP unmatched normal plasma duplex BAM from HiSeq 4000
novaseq_unmatched_normal_plasma_standard_bams_dmp
- DMP unmatched normal plasma standard BAM from NovaSeq
hiseq4000_unmatched_normal_plasma_standard_bams_dmp
- DMP unmatched normal plasma standard BAM from HiSeq 4000
novaseq_curated_duplex_bams_dmp
- curated DMP duplex BAMS from NovaSeq
regions_of_interest
- Different interval files describing regions of interest for MSK-ACCESS assay
If we can justify adding data/tools to the above-mentioned location please contact Ronak Shah.
- Request access once you have your msk email id
InternalLink:
This wiki explains the CMO-CH V1 assay
CMO-CH is offered by the Center for Molecular Oncology (CMO) to MSK researchers for profiling white blood cell DNA to detect mutations in the most commonly altered clonal hematopoiesis (CH) associated genes.
596 targets capturing 58% of CH and 90.4% of CH-PD mutations identified in the latest CH dataset from 40K patients
Total size = 1,143 probes (0.14 Mb)
Full gene coverage for TP53, TET2, ASXL1, DNMT3A, PPM1D, CHEK2, ASXL1, ATM, SF3B1, SRSF2, U2AF1, and U2AF2•Additional targets with hotspot positions from IMPACT heme assay
SNP tiling around TP53, CBL, MPL, JAK2, EZH2, TET2, RUNX1, and ATM (+/-10kb) to identify allelic-imbalances
40 fingerprint SNPs that are shared with all other NGS assays (IMPACT, ACCESS, WES etc.) to detect sample mismatches
This is a wiki for analysis of MSK-ACCESS data
This pages
Things to know for MSK-ACCESS V1 for Research
It is a hybrid capture panel designed for Analysis of Circulating cfDNA to Evaluate Somatic Status using the Unique Molecular Index (UMIs) for high sensitivity. MSK-ACCESS is 13% as large, captures 47% of all mutations detected by MSK-IMPACT.
Selected exons of 129 genes for mutation detection
OncoKB Level 1-4
High rates of mutations
SNPs of zygosity & copy number of 12 genes
Common SNPs for genome-wide copy number
Introns for structural variants of 10 genes
Clonal hematopoiesis genes
Matched cfDNA-WBC (”tumor-normal”) assay to detect somatic alterations
Sensitivity for mutation calling depends on ‘duplex’ collapsed coverage
Different sensitivities for different classes of alterations
Genotyping +++++
De novo mutations, indels ++++
MSI +++
Rearrangements +++
Copy number ++
Tumor mutation burden ○
+ -> sensitivity for that event type
○ -> cannot be calculated
Workflows associated with version 1 of the Assay
Github Location -> https://github.com/mskcc/ACCESS-Pipeline/blob/master/workflows/ACCESS_pipeline.cwl
Tools Used:
Github Location -> https://github.com/mskcc/ACCESS-Pipeline/blob/master/workflows/subworkflows/snps_and_indels.cwl
Tools Used:
Github Location -> https://github.com/mskcc/ACCESS-Pipeline/blob/master/workflows/subworkflows/call_cnv.cwl
Refer to Bioinformatics Pipeline to Detect CNA's section in this paper for details:
Github Location -> https://github.com/mskcc/ACCESS-Pipeline/blob/master/workflows/subworkflows/manta.cwl
Tool Used:
Github Location -> https://github.com/mskcc/ACCESS-Pipeline/blob/master/workflows/subworkflows/msi.cwl
Tool Used:
Voyager has all our configurations in the jinja template, it includes all the paths for various files and tools associated with the workflows, all location are on JUNO: