SC_multiom

Description of the work done and to be done

DESCRIPTION

SAMPLES: one normal SCRNAseq, and 5 multiom; 1 fresh and 4 frozen. One of the frozens is working good(MM_HR_297353). MM_HR_907052 used the RE sample

ANALYSIS DONE:

1. preprocessing of each individual and filter the data. The data use filtered first based on the fresh sample and then with the standar filters (check sc_multiom.R script)
2. check cluster markers and most variable 2000 genes of each of the samples (fresh and frozen)
3. Integrate the samples using Seurat
4. Integrate the samples using harmony
5. Check ambient RNA with dropletQC, but not very good results
6. Start with soupX, also a tool to check ambient RNA

NEXT STEPS:

1. Check soupX
2. Run findoublets pipeline to check doublets
3. Check data of bruno in the folder /mnt/resultados/oncohematologia/resultados/mlagasag/SC_MIREN.tar.gz

SCRIPTS

01_demultiplexing.sh: script to demultiplex and create fastq files

02_counts.sh: script to create counts matrix

dropletQC: dropletQC library to eliminate ambient RNA

integration.R : integration pipeline to integrate all the frozen and the fresh sample with seurat pipeline

integration.sh: to run the integration.R in the server

QC_merge: different plots and approches done in the quality control steps

RefGenome.sh: script to create the reference genome for the multiom case

SC_multiom.R: the preprocessing step of each of the sample individually. Here the filters are defined

SC_multiom.sh: script to run the sc_multiom in the server

soupX: soupX pipeline to correct ambient RNA

Scripts are located in: /mnt/resultados/oncohematologia/resultados/mlagasag/Riney_SC_analysis/SCRIPTS

DATA

fastq_files: /mnt/resultados/oncohematologia/resultados/mlagasag/Riney_SC_fastq/

count_matrix: /mnt/resultados/oncohematologia/resultados/mlagasag/Riney_SC_counts/

analysis carried out: /mnt/resultados/oncohematologia/resultados/mlagasag/Riney_SC_analysis/