Pairing of alpha/beta TCR chains
2026-06-29
pairing_updated.RmdTutorial overview
This vignette shows how to generate paired TCR and single-chain “pseudo-bulk” data using TIRTL-seq TCR-alpha and TCR-beta read counts from half of a 384-well plate.
Study details
For this example, we use data from the St. Jude Tracking Study of Immune Responses Associated with COVID-19 (SJTRC), a clinical trial launched in 2020 to study the T-cell receptor repertoires of adults with naturally acquired COVID-19. This was a prospective, longitudinal cohort study involving adult employees (18 years and older) at St. Jude Children’s Research Hospital in Memphis, TN, USA.
Participants underwent weekly PCR screening for SARS-CoV-2 infection while on the St. Jude campus. Blood samples were collected in 8-ml cell preparation tubes, processed within 24 h into cellular and plasma components, aliquoted and then frozen for future analysis.
Here, we use samples from a healthy 33-year-old female donor with
naturally acquired mild SARS-CoV-2 infection and no prior history of
SARS-CoV-2 infection or vaccination. Samples were collected 143 days
before this donor’s first positive SARS-CoV-2 PCR test
(baseline or tp1 sample), 6 days after
(acute or tp2 sample) and 29 days after
(convalescent or tp3 sample).
Instructions
Select plate rows and columns
CD4+ and CD8+ T-cells were isolated from peripheral blood mononuclear cells (PBMCs) in each sample. For each timepoint, CD8+ cells were plated on the left half of wells in a 384-well plate and CD4+ cells were plated on the right half.
In this case, we will pair the CD8+ cells from the baseline timepoint (tp1), which were in columns 1 through 12 (the left half of the plate) and rows 1 through 16 (or A through P, all rows) of our 384-well plate.
## Loading required package: ggplot2
TIRTLtools:::download_data("exp3_tp1_cd8.tar.gz") ## download well-level data## ℹ Download skipped.
## File exp3_tp1_cd8.tar.gz already exists in /Users/nclark2/Library/Caches/org.R-project.R/R/TIRTLtools/data-v1.
## Use 'force = TRUE' to force download and overwrite existing file.
data_dir = file.path(TIRTLtools:::get_cache_dir(),"exp3_tp1_cd8") ## get the directory that data was downloaded and extracted to
print(data_dir)## [1] "/Users/nclark2/Library/Caches/org.R-project.R/R/TIRTLtools/data-v1/exp3_tp1_cd8"## [1] "MVP113_TIRTLseq_A1_S72.TCRa_ID02.clones_TRA.tsv.gz"
## [2] "MVP113_TIRTLseq_A1_S72.TCRb_ID02.clones_TRB.tsv.gz"
## [3] "MVP113_TIRTLseq_A10_S216.TCRa_ID02.clones_TRA.tsv.gz"
## [4] "MVP113_TIRTLseq_A10_S216.TCRb_ID02.clones_TRB.tsv.gz"
## [5] "MVP113_TIRTLseq_A11_S232.TCRa_ID02.clones_TRA.tsv.gz"
## [6] "MVP113_TIRTLseq_A11_S232.TCRb_ID02.clones_TRB.tsv.gz"
write_folder = tools::R_user_dir("TIRTLtools", which = "cache") ### change this to the folder you would like to save paired output in (if the folder does not exist it will be created)
wells = get_well_subset(row_range = 1:16, col_range = 1:12) ## wells on left half of plateRun pairing algorithms
The run_pairing() function will run the pairing scripts,
which implement the MAD-HYPE and T-SHELL algorithms. These algorithms
are implemented in Python using GPU-accelerated packages (with numpy as
a CPU-only backup) for fast calculation. The package should
automatically install a python environment with the necessary packages
and detect the GPU type (NVIDIA or Apple Silicon) of your machine, if it
has one available.
Each function call may take a few minutes to run.
The main arguments of the function are:
-
folder_path- the path of the folder with well-level data -
folder_out- the path of the folder to write results to (the function will create the folder if it does not exist) -
prefix- a prefix (e.g. the sample name) for the output file names -
well_filter_thres- a threshold on the number of unique clones found in a well, for quality control -
well_pos- the position of the well ID (e.g. “B5”) in the file names. -
wellset- a vector of wells to use for the pairing.
For more information, check the documentation with
?run_pairing.
The well-level data files in each folder are named something like
MVP113_TIRTLseq_P12_S263.TCRa_ID02.clones_TRA.tsv, so the
well ID (P12 in this case) is in the third position
(separate by underscores) so we use well_pos=3. We use the
get_well_subset() function above to generate the vector of
wells for the left side of the plate. With this, we run the
run_pairing() function, saving the output from CD8+ cells
in each plate to the same folder, with a different prefix for each:
<experiment>_<timepoint>_<marker>.
### This function will attempt to automatically install a Python environment with necessary packages for GPU computation
run_pairing(folder_path = data_dir, folder_out = write_folder, prefix = "exp3_tp1_cd8", wellset = wells)## [1] "Folder already exists: /Users/nclark2/Library/Caches/org.R-project.R/R/TIRTLtools"## Loading clone files (TCRalpha) for 192 wells...## 25 of 192 files loaded## 50 of 192 files loaded## 75 of 192 files loaded## 100 of 192 files loaded## 125 of 192 files loaded## 150 of 192 files loaded## 175 of 192 files loaded## 192 of 192 files loaded## Loading clone files (TCRbeta) for 192 wells...## 25 of 192 files loaded## 50 of 192 files loaded## 75 of 192 files loaded## 100 of 192 files loaded## 125 of 192 files loaded## 150 of 192 files loaded## 175 of 192 files loaded## 192 of 192 files loaded## Total number of TCRalpha reads: 6.86e+07## Total number of TCRbeta reads: 9.83e+07## Total number of unique TCRalpha chains: 937880## Total number of unique TCRbeta chains: 928782## Alpha clone threshold for QC: 3217## Beta clone threshold for QC: 3217## Alpha wells passing QC: 191## Beta wells passing QC: 191## Alpha wells failing QC: 1## Beta wells failing QC: 1## Wells passing alpha and beta QC: 191## 1 out of 192 wells removed by QC: P3## Using 'auto' T-SHELL settings, selecting 'pval_thres_tshell' and 'wij_thres_tshell' based on the number of wells passing QC## 191 wells passing: Using '384_well' T-SHELL settings## Tabulating TCRalpha pseudobulk counts## Writing TCRalpha pseudobulk file... exp3_tp1_cd8_pseudobulk_TRA.tsv## Tabulating TCRbeta pseudobulk counts## Writing TCRbeta pseudobulk file... exp3_tp1_cd8_pseudobulk_TRB.tsv## Pseudobulk done## Merging alpha clonesets...## Done! Unique alpha clones after filtering: 937875## Unique alpha clones in more than 2 wells: 36679## Done! Unique beta clones after filtering: 928777## Unique beta clones and wells in more than 2 wells: 36080## Pre-computing look-up table:## | | | 0% | | | 1% | |= | 1% | |= | 2% | |== | 3% | |=== | 4% | |=== | 5% | |==== | 5% | |==== | 6% | |===== | 7% | |===== | 8% | |====== | 8% | |====== | 9% | |======= | 9% | |======= | 10% | |======== | 11% | |======== | 12% | |========= | 13% | |========== | 14% | |========== | 15% | |=========== | 15% | |=========== | 16% | |============ | 17% | |============ | 18% | |============= | 18% | |============= | 19% | |============== | 19% | |============== | 20% | |=============== | 21% | |=============== | 22% | |================ | 23% | |================ | 24% | |================= | 24% | |================= | 25% | |================== | 25% | |================== | 26% | |=================== | 27% | |=================== | 28% | |==================== | 28% | |==================== | 29% | |===================== | 29% | |===================== | 30% | |====================== | 31% | |====================== | 32% | |======================= | 32% | |======================= | 33% | |======================= | 34% | |======================== | 34% | |======================== | 35% | |========================= | 35% | |========================= | 36% | |========================== | 37% | |========================== | 38% | |=========================== | 38% | |=========================== | 39% | |============================ | 40% | |============================= | 41% | |============================= | 42% | |============================== | 42% | |============================== | 43% | |=============================== | 44% | |=============================== | 45% | |================================ | 45% | |================================ | 46% | |================================= | 47% | |================================= | 48% | |================================== | 48% | |================================== | 49% | |=================================== | 50% | |==================================== | 51% | |==================================== | 52% | |===================================== | 52% | |===================================== | 53% | |====================================== | 54% | |====================================== | 55% | |======================================= | 55% | |======================================= | 56% | |======================================== | 57% | |======================================== | 58% | |========================================= | 58% | |========================================= | 59% | |========================================== | 60% | |=========================================== | 61% | |=========================================== | 62% | |============================================ | 62% | |============================================ | 63% | |============================================= | 64% | |============================================= | 65% | |============================================== | 65% | |============================================== | 66% | |=============================================== | 66% | |=============================================== | 67% | |=============================================== | 68% | |================================================ | 68% | |================================================ | 69% | |================================================= | 70% | |================================================= | 71% | |================================================== | 71% | |================================================== | 72% | |=================================================== | 72% | |=================================================== | 73% | |==================================================== | 74% | |==================================================== | 75% | |===================================================== | 75% | |===================================================== | 76% | |====================================================== | 76% | |====================================================== | 77% | |======================================================= | 78% | |======================================================= | 79% | |======================================================== | 80% | |======================================================== | 81% | |========================================================= | 81% | |========================================================= | 82% | |========================================================== | 82% | |========================================================== | 83% | |=========================================================== | 84% | |=========================================================== | 85% | |============================================================ | 85% | |============================================================ | 86% | |============================================================= | 87% | |============================================================== | 88% | |============================================================== | 89% | |=============================================================== | 90% | |=============================================================== | 91% | |================================================================ | 91% | |================================================================ | 92% | |================================================================= | 92% | |================================================================= | 93% | |================================================================== | 94% | |================================================================== | 95% | |=================================================================== | 95% | |=================================================================== | 96% | |==================================================================== | 97% | |===================================================================== | 98% | |===================================================================== | 99% | |======================================================================| 99% | |======================================================================| 100%## Running pairing algorithms...## Checking for available GPU...
##
## Apple Silicon GPU detected:
## Apple Silicon GPU (M1/M2/M3)
## Checking for GPU-related Python modules...
##
## 'mlx' is installed (for Apple Silicon GPUs).
## Loading mlx
## total number of chunks 73
## start time for MAD-HYPE: 2026-09-21 15:02:52
## Progress: 3500 (10%)
## Progress: 7000 (20%)
## Progress: 14500 (40%)
## Progress: 18000 (50%)
## Progress: 22000 (60%)
## Progress: 25500 (70%)
## Progress: 33000 (90%)
## Progress: 36500 (100%)
## end time for MAD-HYPE: 2026-09-21 15:02:55
## Number of pairs: 13379
## total number of chunks 73
## start processing time for T-Shell: 2026-09-21 15:02:55
## Progress: 3500 (10%)
## Progress: 7000 (20%)
## Progress: 14500 (40%)
## Progress: 18000 (50%)
## Progress: 22000 (60%)
## Progress: 25500 (70%)
## Progress: 33000 (90%)
## Progress: 36500 (100%)
## end time for T-Shell: 2026-09-21 15:02:56## Pairing is finished.## [1] "Filtering results, adding amino acid and V segment information..."
## [1] "Scoring unique pairs..."## Writing TCRalpha/beta pairs... exp3_tp1_cd8_TIRTLoutput.tsv## All pairing is finished!## Number of clones paired by MAD-HYPE algorithm: 13379## Number of clones paired by T-SHELL algorithm: 7304## Total number of unique TCRalpha/beta pairs: 14270## 81.117 sec elapsed## Key: <wi, wj, wij>
## wi wj wij alpha_nuc
## <num> <num> <num> <char>
## 1: 0 3 85 TGTGCAATGAGTTTTAACTTTGGAAATGAGAAATTAACCTTT
## 2: 1 0 56 TGTGCTGGACATACCGGCACTGCCAGTAAACTCACCTTT
## 3: 1 0 56 TGTGCAGGAGCGGAGGATGCTGGTGGTACTAGCTATGGAAAGCTGACATTT
## 4: 0 4 68 TGTGCCGTGGACGTGTACACCGGTAACCAGTTCTATTTT
## 5: 0 4 68 TGCGGCACAGAAAGCGGAGGTAGCAACTATAAACTGACATTT
## ---
## 20679: 40 0 86 TGTGCTCTGAGTGAGACCGGTAACCAGTTCTATTTT
## 20680: 0 1 190 TGTGCAGAGTTGAAGATCTTATAACACCGACAAGCTCATCTTT
## 20681: 0 0 191 TGTGCCGTGAAACAATAACCAGGGAGGAAAGCTTATCTTC
## 20682: 0 24 165 TGTGCAGGAGTTGGGGAGGAAGCCAAGGAAATCTCATCTTT
## 20683: 0 5 186 TGTGCTCTGAGTGACAAATAGGCTTTGGGAATGTGCTGCATTGC
## beta_nuc wa wb
## <char> <int> <int>
## 1: TGTGCCAGCAGTTTATCGTCCCTCGAGGGGGGCTACACCTTC 85 88
## 2: TGCGCCAGCAGCCGAGTCAGAAATCCCGACTACGAGCAGTACTTC 57 56
## 3: TGCGCCAGCAGCCGAGTCAGAAATCCCGACTACGAGCAGTACTTC 57 56
## 4: TGCGCCAGCAGCTTTGACAAGACCTATGGCTACACCTTC 68 72
## 5: TGCGCCAGCAGCTTTGACAAGACCTATGGCTACACCTTC 68 72
## ---
## 20679: TGTGCCAGCAGCCAGGGATCTGGCGGAGACAGTTCTTC 126 86
## 20680: TGTGCCTGGAGTAAGGGTGAGGCCAACGTCCTGACTTTC 190 191
## 20681: TGTGCCAGCAGCACAGGACTGCCAAGAGATACGCAGTATTTT 191 191
## 20682: TGCAGTGCTAGGGGGGACAGCTCCTACGAGCAGTACTTC 165 189
## 20683: TGTGCCAGCAGCTTTCAGGGCGGGGGAACGGTGGGCACAGATACGCAGTATTTT 186 191
## alpha_nuc_seq
## <char>
## 1: TGTGCAATGAGTTTTAACTTTGGAAATGAGAAATTAACCTTT
## 2: TGTGCTGGACATACCGGCACTGCCAGTAAACTCACCTTT
## 3: TGTGCAGGAGCGGAGGATGCTGGTGGTACTAGCTATGGAAAGCTGACATTT
## 4: TGTGCCGTGGACGTGTACACCGGTAACCAGTTCTATTTT
## 5: TGCGGCACAGAAAGCGGAGGTAGCAACTATAAACTGACATTT
## ---
## 20679: TGTGCTCTGAGTGAGACCGGTAACCAGTTCTATTTT
## 20680: TGTGCAGAGTTGAAGATCTTATAACACCGACAAGCTCATCTTT
## 20681: TGTGCCGTGAAACAATAACCAGGGAGGAAAGCTTATCTTC
## 20682: TGTGCAGGAGTTGGGGAGGAAGCCAAGGAAATCTCATCTTT
## 20683: TGTGCTCTGAGTGACAAATAGGCTTTGGGAATGTGCTGCATTGC
## beta_nuc_seq
## <char>
## 1: TGTGCCAGCAGTTTATCGTCCCTCGAGGGGGGCTACACCTTC
## 2: TGCGCCAGCAGCCGAGTCAGAAATCCCGACTACGAGCAGTACTTC
## 3: TGCGCCAGCAGCCGAGTCAGAAATCCCGACTACGAGCAGTACTTC
## 4: TGCGCCAGCAGCTTTGACAAGACCTATGGCTACACCTTC
## 5: TGCGCCAGCAGCTTTGACAAGACCTATGGCTACACCTTC
## ---
## 20679: TGTGCCAGCAGCCAGGGATCTGGCGGAGACAGTTCTTC
## 20680: TGTGCCTGGAGTAAGGGTGAGGCCAACGTCCTGACTTTC
## 20681: TGTGCCAGCAGCACAGGACTGCCAAGAGATACGCAGTATTTT
## 20682: TGCAGTGCTAGGGGGGACAGCTCCTACGAGCAGTACTTC
## 20683: TGTGCCAGCAGCTTTCAGGGCGGGGGAACGGTGGGCACAGATACGCAGTATTTT
## alpha_beta
## <char>
## 1: TGTGCAATGAGTTTTAACTTTGGAAATGAGAAATTAACCTTT_TGTGCCAGCAGTTTATCGTCCCTCGAGGGGGGCTACACCTTC
## 2: TGTGCTGGACATACCGGCACTGCCAGTAAACTCACCTTT_TGCGCCAGCAGCCGAGTCAGAAATCCCGACTACGAGCAGTACTTC
## 3: TGTGCAGGAGCGGAGGATGCTGGTGGTACTAGCTATGGAAAGCTGACATTT_TGCGCCAGCAGCCGAGTCAGAAATCCCGACTACGAGCAGTACTTC
## 4: TGTGCCGTGGACGTGTACACCGGTAACCAGTTCTATTTT_TGCGCCAGCAGCTTTGACAAGACCTATGGCTACACCTTC
## 5: TGCGGCACAGAAAGCGGAGGTAGCAACTATAAACTGACATTT_TGCGCCAGCAGCTTTGACAAGACCTATGGCTACACCTTC
## ---
## 20679: TGTGCTCTGAGTGAGACCGGTAACCAGTTCTATTTT_TGTGCCAGCAGCCAGGGATCTGGCGGAGACAGTTCTTC
## 20680: TGTGCAGAGTTGAAGATCTTATAACACCGACAAGCTCATCTTT_TGTGCCTGGAGTAAGGGTGAGGCCAACGTCCTGACTTTC
## 20681: TGTGCCGTGAAACAATAACCAGGGAGGAAAGCTTATCTTC_TGTGCCAGCAGCACAGGACTGCCAAGAGATACGCAGTATTTT
## 20682: TGTGCAGGAGTTGGGGAGGAAGCCAAGGAAATCTCATCTTT_TGCAGTGCTAGGGGGGACAGCTCCTACGAGCAGTACTTC
## 20683: TGTGCTCTGAGTGACAAATAGGCTTTGGGAATGTGCTGCATTGC_TGTGCCAGCAGCTTTCAGGGCGGGGGAACGGTGGGCACAGATACGCAGTATTTT
## method r ts pval pval_adj loss_a_frac
## <char> <num> <num> <num> <num> <num>
## 1: madhype NA NA NA NA 0.034090909
## 2: madhype NA NA NA NA 0.000000000
## 3: madhype NA NA NA NA 0.000000000
## 4: madhype NA NA NA NA 0.055555556
## 5: madhype NA NA NA NA 0.055555556
## ---
## 20679: tshell 0.5611333 9.319887 3.088615e-17 8.477475e-11 0.000000000
## 20680: tshell 0.5594879 9.280079 3.993057e-17 2.274191e-11 0.005235602
## 20681: tshell 0.5515199 9.089538 1.357749e-16 9.696026e-13 0.000000000
## 20682: tshell 0.5426992 8.882772 5.069335e-16 1.223313e-11 0.126984127
## 20683: tshell 0.5270523 8.526113 4.781799e-15 3.515918e-11 0.026178010
## loss_b_frac score cdr3a va ja
## <num> <num> <char> <char> <char>
## 1: 0.00000000 45.705465 CAMSFNFGNEKLTF TRAV14/DV4 TRAJ48
## 2: 0.01754386 42.204274 CAGHTGTASKLTF TRAV21 TRAJ44
## 3: 0.01754386 42.204274 CAGAEDAGGTSYGKLTF TRAV27 TRAJ52
## 4: 0.00000000 41.731629 CAVDVYTGNQFYF TRAV39 TRAJ49
## 5: 0.00000000 41.731629 CGTESGGSNYKLTF TRAV30 TRAJ53
## ---
## 20679: 0.31746032 17.460590 CALSETGNQFYF TRAV19 TRAJ49
## 20680: 0.00000000 -Inf CAELKIL_NTDKLIF TRAV5 TRAJ34
## 20681: 0.00000000 -4.560842 CAVKQ*P_GGKLIF TRAV12-2 TRAJ23
## 20682: 0.00000000 -3.815652 CAGVGEE_QGNLIF TRAV27 TRAJ42
## 20683: 0.00000000 -Inf CALSDK*_FGNVLHC TRAV19 TRAJ35
## cdr3b vb jb is_functional
## <char> <char> <char> <lgcl>
## 1: CASSLSSLEGGYTF TRBV27 TRBJ1-2 TRUE
## 2: CASSRVRNPDYEQYF TRBV4-1 TRBJ2-7 TRUE
## 3: CASSRVRNPDYEQYF TRBV4-1 TRBJ2-7 TRUE
## 4: CASSFDKTYGYTF TRBV5-1 TRBJ1-2 TRUE
## 5: CASSFDKTYGYTF TRBV5-1 TRBJ1-2 TRUE
## ---
## 20679: CASSQG_WRRQFF TRBV4-2 TRBJ2-1 FALSE
## 20680: CAWSKGEANVLTF TRBV30 TRBJ2-6 FALSE
## 20681: CASSTGLPRDTQYF TRBV5-8 TRBJ2-3 FALSE
## 20682: CSARGDSSYEQYF TRBV20-1 TRBJ2-7 FALSE
## 20683: CASSFQGGGTVGTDTQYF TRBV7-9 TRBJ2-3 FALSELoad paired TCR data
The output from each call to run_pairing() is 3
tab-separated text files (.tsv). If you would like to compress the
output files, you can use the option
gzip_output = TRUE.
-
<sample-name>_TIRTLoutput.tsv(.gz)– Paired TCRs – a table of computationally paired alpha/beta TCRs -
<sample-name>_pseudobulk_TRA.tsv(.gz)– Alpha chain “pseudo-bulk” data – a table of read count summary metrics for alpha-chains across all wells on a plate -
<sample-name>_pseudobulk_TRB.tsv(.gz)– Beta chain “pseudo-bulk” data – a table of read count summary metrics for beta-chains across all wells on a plate
The load_tirtlseq() function can be used to load all of
the data in a directory, whether it is in .tsv or
compressed .tsv.gz form.
This function loads the data into a “list”, which is an R data type
that can contain any type of unstructured data. Elements of a list can
be accessed by their name, e.g. your_list$meta, or their
index, e.g. your_list[[2]]. The list contains three slots:
meta, data, and info, and has the
following structure:
your_data_object (list, with class "TIRTLseqDataSet")
├───meta (a data frame of sample metadata)
├───info (a list of processing/pairing information)
└───data (a list containing paired and pseudobulk data for each sample)
└───sample_1 (list)
├───alpha (alpha pseudobulk dataframe)
├───beta (beta pseudobulk dataframe)
└───paired (paired pseudobulk dataframe)
...
└───sample_n (list)
├───alpha (alpha pseudobulk dataframe)
├───beta (beta pseudobulk dataframe)
└───paired (paired pseudobulk dataframe)Since we used
<experiment>_<timepoint>_<marker> for the
prefix for each set of output files, we add this in the
meta_columns argument, so that the function creates a data
frame of sample metadata with this information.
ts = load_tirtlseq(write_folder, sep = "_", verbose = FALSE,
meta_columns = c("experiment", "timepoint", "marker"))
ts ## list with class "TIRTLseqDataSet"## <TIRTLseqDataSet>
## Number of samples: 1
## Samples: exp3_tp1_cd8
summary(ts)## <TIRTLseqDataSet>
## Number of samples: 1
## Per-sample TCR counts (alpha / beta / paired):
## # A tibble: 1 × 5
## sample_id `Paired TCRs` `Unique Paired TCRs` `Alpha Chains` `Beta Chains`
## <chr> <int> <int> <int> <int>
## 1 exp3_tp1_cd8 20683 14270 937875 928777You can inspect the loaded object and view the data frames with paired TCRs and single-chain pseudobulk for each sample.
ts$meta ## sample metadata (data frame)## # A tibble: 1 × 5
## sample_id experiment timepoint marker label
## <chr> <chr> <chr> <chr> <chr>
## 1 exp3_tp1_cd8 exp3 tp1 cd8 experiment: exp3 | timepoint: tp1 | …
ts$info ## list of data pairing/processing information## $data_version
## [1] "v1"
##
## $processing_version
## [1] "v1"
##
## $package_version
## [1] '0.2.6'
##
## $call
## $call$directory
## [1] "/Users/nclark2/Library/Caches/org.R-project.R/R/TIRTLtools"
##
## $call$chain
## [1] "all" "paired" "alpha" "beta"
##
## $call$sep
## [1] "_"
##
## $call$meta_columns
## [1] "experiment" "timepoint" "marker"
##
## $call$samples
## NULL
##
## $call$clean
## [1] FALSE
##
## $call$remove_nonfunctional
## [1] FALSE
##
## $call$process
## [1] TRUE
##
## $call$pseudobulk_columns
## [1] "auto"
##
## $call$paired_columns
## [1] "auto"
##
## $call$n_threads
## [1] 9
##
## $call$verbose
## [1] FALSE
##
## $call$stringsAsFactors
## [1] FALSE
##
## $call$n_max
## [1] Inf
names(ts$data) ## list with data for each sample## [1] "exp3_tp1_cd8"
names(ts$data$exp3_tp1_cd8) ## list with data for one sample (exp3_tp1_cd8)## [1] "alpha" "beta" "paired" "paired_alt"
ts$data$exp3_tp1_cd8$alpha ## TCR-alpha pseudobulk (data frame)## id rank aaSeqCDR3 v j
## <char> <int> <char> <char> <char>
## 1: alpha_1 1 CAMRGRSNRDDKIIF TRAV14/DV4 TRAJ30
## 2: alpha_2 2 CALKTSYDKVIF TRAV38-2/DV8 TRAJ50
## 3: alpha_3 3 CAASRLPDDMRF TRAV29/DV5 TRAJ43
## 4: alpha_4 4 CAVRDSNYQLIW TRAV1-2 TRAJ33
## 5: alpha_5 5 CLLAHLRSGPNSGGSNYKLTF TRAV40 TRAJ53
## ---
## 937871: alpha_937871 937871 FFLPNR_FQRLVF TRAV1-2 TRAJ8
## 937872: alpha_937872 937872 FFQGPQ_NKLTF TRAV13-1 TRAJ17
## 937873: alpha_937873 937873 FFQGLQ_NKLTF TRAV13-1 TRAJ17
## 937874: alpha_937874 937874 FFQGLQ_NKLTF TRAV13-1 TRAJ17
## 937875: alpha_937875 937875 FFLQRGW_SYQLTF TRAV8-1 TRAJ28
## readFraction readCount n_wells paired_status n_paired
## <num> <int> <int> <char> <num>
## 1: 2.058548e-02 1411609 191 T-SHELL only 1
## 2: 1.482005e-02 1016256 191 T-SHELL only 1
## 3: 9.557239e-03 655369 191 T-SHELL only 1
## 4: 5.478071e-03 375648 191 neither 0
## 5: 4.698377e-03 322182 191 T-SHELL only 1
## ---
## 937871: 1.458299e-08 1 1 neither 0
## 937872: 1.458299e-08 1 1 neither 0
## 937873: 1.458299e-08 1 1 neither 0
## 937874: 1.458299e-08 1 1 neither 0
## 937875: 1.458299e-08 1 1 neither 0
## targetSequences
## <char>
## 1: TGTGCAATGAGGGGTCGATCGAACAGAGATGACAAGATCATCTTT
## 2: TGTGCTTTGAAAACCTCCTACGACAAGGTGATATTT
## 3: TGTGCAGCAAGCCGACTTCCGGATGACATGCGCTTT
## 4: TGTGCTGTGAGAGATAGCAACTATCAGTTAATCTGG
## 5: TGTCTTCTGGCACACCTCCGATCAGGACCCAATAGTGGAGGTAGCAACTATAAACTGACATTT
## ---
## 937871: TTTTTCCTCCCGAACAGGCTTTCAGAGACTTGTATTT
## 937872: TTTTTTCAGGGGCCGCAGGCAACAAGCTAACTTTT
## 937873: TTTTTTCAGGGGCTGCAGGCAACAAGCTGACTTTT
## 937874: TTTTTTCAGGGGCTGCAGGCAACAAGTTAACTTTT
## 937875: TTTTTTTTACAACGGGGCTGGGAGTTACCAACTCACTTTC
## readCount_median readCount_max sem max_wells n_paired_madhype
## <num> <int> <num> <int> <num>
## 1: 7413 14066 2.138826e-04 191 0
## 2: 5305 9477 2.019982e-04 191 0
## 3: 3310 6673 1.399961e-04 191 0
## 4: 1909 3730 9.109789e-05 191 0
## 5: 1705 2812 7.981121e-05 191 0
## ---
## 937871: 1 1 1.202901e-08 191 0
## 937872: 1 1 1.449137e-08 191 0
## 937873: 1 1 1.518653e-08 191 0
## 937874: 1 1 1.518653e-08 191 0
## 937875: 1 1 1.105502e-08 191 0
## n_paired_tshell has_stop_codon has_frameshift is_functional is_paired
## <num> <lgcl> <lgcl> <lgcl> <lgcl>
## 1: 1 FALSE FALSE TRUE TRUE
## 2: 1 FALSE FALSE TRUE TRUE
## 3: 1 FALSE FALSE TRUE TRUE
## 4: 0 FALSE FALSE TRUE FALSE
## 5: 1 FALSE FALSE TRUE TRUE
## ---
## 937871: 0 FALSE TRUE FALSE FALSE
## 937872: 0 FALSE TRUE FALSE FALSE
## 937873: 0 FALSE TRUE FALSE FALSE
## 937874: 0 FALSE TRUE FALSE FALSE
## 937875: 0 FALSE TRUE FALSE FALSE
## is_paired_tshell is_paired_madhype
## <lgcl> <lgcl>
## 1: TRUE FALSE
## 2: TRUE FALSE
## 3: TRUE FALSE
## 4: FALSE FALSE
## 5: TRUE FALSE
## ---
## 937871: FALSE FALSE
## 937872: FALSE FALSE
## 937873: FALSE FALSE
## 937874: FALSE FALSE
## 937875: FALSE FALSE
ts$data$exp3_tp1_cd8$beta ## TCR-beta pseudobulk (data frame)## id rank aaSeqCDR3 v j readFraction
## <char> <int> <char> <char> <char> <num>
## 1: beta_1 1 CSVERVNYNEQFF TRBV29-1 TRBJ2-1 1.348328e-02
## 2: beta_2 2 CASSTGLPRDTQYF TRBV5-8 TRBJ2-3 1.143658e-02
## 3: beta_3 3 CSATAGRNYGYTF TRBV20-1 TRBJ1-2 1.065993e-02
## 4: beta_4 4 CASSLTYEQYF TRBV6-2 TRBJ2-7 8.413453e-03
## 5: beta_5 5 CASSWPQGSGSLDEQFF TRBV5-1 TRBJ2-1 5.177560e-03
## ---
## 928773: beta_928773 928773 FASSLGV_GDEQFF TRBV12-3 TRBJ2-1 1.017017e-08
## 928774: beta_928774 928774 FASSIGDRA_LRNSPLHF TRBV19 TRBJ1-6 1.017017e-08
## 928775: beta_928775 928775 FAISE_SEAVF TRBV10-3 TRBJ2-2 1.017017e-08
## 928776: beta_928776 928776 FARKQGN_DNEQFF TRBV19 TRBJ2-1 1.017017e-08
## 928777: beta_928777 928777 FAADRGP_STDTQYF TRBV19 TRBJ2-3 1.017017e-08
## readCount n_wells paired_status n_paired
## <int> <int> <char> <num>
## 1: 1325768 191 T-SHELL only 2
## 2: 1124522 191 T-SHELL only 2
## 3: 1048157 191 T-SHELL only 1
## 4: 827268 191 T-SHELL only 2
## 5: 509093 191 T-SHELL only 1
## ---
## 928773: 1 1 neither 0
## 928774: 1 1 neither 0
## 928775: 1 1 neither 0
## 928776: 1 1 neither 0
## 928777: 1 1 neither 0
## targetSequences readCount_median
## <char> <num>
## 1: TGCAGCGTTGAAAGGGTTAATTACAATGAGCAGTTCTTC 6728
## 2: TGTGCCAGCAGCACAGGACTGCCAAGAGATACGCAGTATTTT 5933
## 3: TGCAGTGCTACGGCAGGGAGGAACTATGGCTACACCTTC 5267
## 4: TGTGCCAGCAGTCTCACCTACGAGCAGTACTTC 4293
## 5: TGCGCCAGCAGCTGGCCTCAGGGTAGCGGGAGTTTGGATGAGCAGTTCTTC 2516
## ---
## 928773: TTTGCCAGCAGTTTGGGGGTATAGGGGATGAGCAGTTCTTC 1
## 928774: TTTGCCAGTAGTATCGGGGACAGGGCTCTTGAGAAATTCACCCCTCCACTTT 1
## 928775: TTTGCCATCAGTGAAAGAGCGAAGCTGTTTTT 1
## 928776: TTTGCCCGCAAACAGGGAAATGGGACAATGAGCAGTTCTTC 1
## 928777: TTTGCCGCCGACAGGGGGCCTAAGCACAGATACGCAGTATTTT 1
## readCount_max sem max_wells n_paired_madhype n_paired_tshell
## <int> <num> <int> <num> <num>
## 1: 14705 2.637763e-04 191 0 2
## 2: 9823 1.293336e-04 191 0 2
## 3: 9841 1.409173e-04 191 0 1
## 4: 8641 1.935800e-04 191 0 2
## 5: 6879 1.404382e-04 191 0 1
## ---
## 928773: 1 8.824574e-09 191 0 0
## 928774: 1 1.013799e-08 191 0 0
## 928775: 1 1.229442e-08 191 0 0
## 928776: 1 8.947667e-09 191 0 0
## 928777: 1 1.029493e-08 191 0 0
## has_stop_codon has_frameshift is_functional is_paired is_paired_tshell
## <lgcl> <lgcl> <lgcl> <lgcl> <lgcl>
## 1: FALSE FALSE TRUE TRUE TRUE
## 2: FALSE FALSE TRUE TRUE TRUE
## 3: FALSE FALSE TRUE TRUE TRUE
## 4: FALSE FALSE TRUE TRUE TRUE
## 5: FALSE FALSE TRUE TRUE TRUE
## ---
## 928773: FALSE TRUE FALSE FALSE FALSE
## 928774: FALSE TRUE FALSE FALSE FALSE
## 928775: FALSE TRUE FALSE FALSE FALSE
## 928776: FALSE TRUE FALSE FALSE FALSE
## 928777: FALSE TRUE FALSE FALSE FALSE
## is_paired_madhype
## <lgcl>
## 1: FALSE
## 2: FALSE
## 3: FALSE
## 4: FALSE
## 5: FALSE
## ---
## 928773: FALSE
## 928774: FALSE
## 928775: FALSE
## 928776: FALSE
## 928777: FALSE
ts$data$exp3_tp1_cd8$paired ## paired TCRαβ (data frame)## Key: <beta_nuc>
## method va ja cdr3a cdr3b vb
## <char> <char> <char> <char> <char> <char>
## 1: tshell TRAV13-1 TRAJ32 CAAKGVYGGATNKLIF CSVERVNYNEQFF TRBV29-1
## 2: tshell TRAV10 TRAJ10 CVVNHGR_GNKLTF CSVERVNYNEQFF TRBV29-1
## 3: tshell TRAV14/DV4 TRAJ30 CAMRGRSNRDDKIIF CASSTGLPRDTQYF TRBV5-8
## 4: tshell TRAV12-2 TRAJ23 CAVKQ*P_GGKLIF CASSTGLPRDTQYF TRBV5-8
## 5: tshell TRAV29/DV5 TRAJ43 CAASRLPDDMRF CSATAGRNYGYTF TRBV20-1
## ---
## 20679: tshell TRAV22 TRAJ6 CAVLASGGSYTPTF CASSFG_DRGAVF TRBV5-4
## 20680: madhype TRAV3 TRAJ34 CAVRDMSTDELIF CASSLVR_GKNCFF TRBV27
## 20681: tshell TRAV3 TRAJ34 CAVRDMSTDELIF CASSLVR_GKNCFF TRBV27
## 20682: tshell TRAV38-2/DV8 TRAJ45 CAYRSGGGADGLTF CASSLFM*G_TGNQPQHF TRBV27
## 20683: madhype TRAV12-3 TRAJ24 CAMNTDSWGKLQL CASSFWGR_QMKKLFF TRBV28
## jb alpha_rank beta_rank alpha_readFraction beta_readFraction
## <char> <int> <int> <num> <num>
## 1: TRBJ2-1 12 1 2.942424e-03 1.348328e-02
## 2: TRBJ2-1 79 1 7.625154e-04 1.348328e-02
## 3: TRBJ2-3 1 2 2.058548e-02 1.143658e-02
## 4: TRBJ2-3 30 2 1.645603e-03 1.143658e-02
## 5: TRBJ1-2 3 3 9.557239e-03 1.065993e-02
## ---
## 20679: TRBJ2-2 375555 572602 2.041619e-07 3.051050e-08
## 20680: TRBJ1-4 569015 572764 4.374897e-08 3.051050e-08
## 20681: TRBJ1-4 569015 572764 4.374897e-08 3.051050e-08
## 20682: TRBJ1-5 6296 574415 9.726854e-06 3.051050e-08
## 20683: TRBJ1-4 433237 574511 1.166639e-07 3.051050e-08
## alpha_readCount beta_readCount is_functional
## <int> <int> <lgcl>
## 1: 201771 1325768 TRUE
## 2: 52288 1325768 FALSE
## 3: 1411609 1124522 TRUE
## 4: 112844 1124522 FALSE
## 5: 655369 1048157 TRUE
## ---
## 20679: 14 3 FALSE
## 20680: 3 3 FALSE
## 20681: 3 3 FALSE
## 20682: 667 3 FALSE
## 20683: 8 3 FALSE
## alpha_nuc
## <char>
## 1: TGTGCAGCAAAGGGGGTTTATGGTGGTGCTACAAACAAGCTCATCTTT
## 2: TGTGTGGTGAACCACGGGAGGAGGAAACAAACTCACCTTT
## 3: TGTGCAATGAGGGGTCGATCGAACAGAGATGACAAGATCATCTTT
## 4: TGTGCCGTGAAACAATAACCAGGGAGGAAAGCTTATCTTC
## 5: TGTGCAGCAAGCCGACTTCCGGATGACATGCGCTTT
## ---
## 20679: TGTGCTGTACTCGCATCAGGAGGAAGCTACACACCTACATTT
## 20680: TGTGCTGTGAGAGACATGAGCACCGACGAGCTCATCTTT
## 20681: TGTGCTGTGAGAGACATGAGCACCGACGAGCTCATCTTT
## 20682: TGTGCTTATAGGAGCGGAGGAGGTGCTGACGGACTCACCTTT
## 20683: TGTGCAATGAATACGGACAGCTGGGGGAAATTGCAGCTT
## beta_nuc
## <char>
## 1: TGCAGCGTTGAAAGGGTTAATTACAATGAGCAGTTCTTC
## 2: TGCAGCGTTGAAAGGGTTAATTACAATGAGCAGTTCTTC
## 3: TGTGCCAGCAGCACAGGACTGCCAAGAGATACGCAGTATTTT
## 4: TGTGCCAGCAGCACAGGACTGCCAAGAGATACGCAGTATTTT
## 5: TGCAGTGCTACGGCAGGGAGGAACTATGGCTACACCTTC
## ---
## 20679: TGTGCCAGCAGCTTCGGGGGGACCGGGGAGCTGTTTTT
## 20680: TGTGCCAGCAGCTTGGTCCGAGGGGAAAAACTGTTTTTTT
## 20681: TGTGCCAGCAGCTTGGTCCGAGGGGAAAAACTGTTTTTTT
## 20682: TGTGCCAGCAGTTTATTTATGTAGGGTAACGGGCAATCAGCCCCAGCATTTC
## 20683: TGTGCCAGCAGTTTCTGGGGCAGGCCAGATGAAAAAACTGTTTTTT
## alpha_beta
## <char>
## 1: TGTGCAGCAAAGGGGGTTTATGGTGGTGCTACAAACAAGCTCATCTTT_TGCAGCGTTGAAAGGGTTAATTACAATGAGCAGTTCTTC
## 2: TGTGTGGTGAACCACGGGAGGAGGAAACAAACTCACCTTT_TGCAGCGTTGAAAGGGTTAATTACAATGAGCAGTTCTTC
## 3: TGTGCAATGAGGGGTCGATCGAACAGAGATGACAAGATCATCTTT_TGTGCCAGCAGCACAGGACTGCCAAGAGATACGCAGTATTTT
## 4: TGTGCCGTGAAACAATAACCAGGGAGGAAAGCTTATCTTC_TGTGCCAGCAGCACAGGACTGCCAAGAGATACGCAGTATTTT
## 5: TGTGCAGCAAGCCGACTTCCGGATGACATGCGCTTT_TGCAGTGCTACGGCAGGGAGGAACTATGGCTACACCTTC
## ---
## 20679: TGTGCTGTACTCGCATCAGGAGGAAGCTACACACCTACATTT_TGTGCCAGCAGCTTCGGGGGGACCGGGGAGCTGTTTTT
## 20680: TGTGCTGTGAGAGACATGAGCACCGACGAGCTCATCTTT_TGTGCCAGCAGCTTGGTCCGAGGGGAAAAACTGTTTTTTT
## 20681: TGTGCTGTGAGAGACATGAGCACCGACGAGCTCATCTTT_TGTGCCAGCAGCTTGGTCCGAGGGGAAAAACTGTTTTTTT
## 20682: TGTGCTTATAGGAGCGGAGGAGGTGCTGACGGACTCACCTTT_TGTGCCAGCAGTTTATTTATGTAGGGTAACGGGCAATCAGCCCCAGCATTTC
## 20683: TGTGCAATGAATACGGACAGCTGGGGGAAATTGCAGCTT_TGTGCCAGCAGTTTCTGGGGCAGGCCAGATGAAAAAACTGTTTTTT
## wi wj wij wa wb score r ts
## <int> <int> <int> <int> <int> <num> <num> <num>
## 1: 0 0 191 191 191 -4.56084201 0.8378690 21.101664
## 2: 0 0 191 191 191 -4.56084201 0.6553487 11.928026
## 3: 0 0 191 191 191 -4.56084201 0.7361605 14.953353
## 4: 0 0 191 191 191 -4.56084201 0.5515199 9.089538
## 5: 0 0 191 191 191 -4.56084201 0.8408442 21.356329
## ---
## 20679: 1 0 3 4 3 0.07990462 0.9164956 31.495808
## 20680: 0 0 3 3 3 0.61848796 NA NA
## 20681: 0 0 3 3 3 0.61848796 0.9989229 295.968667
## 20682: 1 0 3 4 3 0.07990462 0.8987059 28.172642
## 20683: 0 0 3 3 3 0.61848796 NA NA
## pval pval_adj loss_a_frac loss_b_frac alpha_readCount_max
## <num> <num> <num> <num> <int>
## 1: 1.409514e-51 1.580244e-42 0 0.00 2192
## 2: 8.149960e-25 1.794423e-19 0 0.00 622
## 3: 7.114002e-34 4.904156e-30 0 0.00 14066
## 4: 1.357749e-16 9.696026e-13 0 0.00 1002
## 5: 2.843320e-52 2.498831e-48 0 0.00 6673
## ---
## 20679: 3.972705e-77 4.643735e-30 0 0.25 6
## 20680: NA NA 0 0.00 1
## 20681: 5.436759e-254 6.601289e-221 0 0.00 1
## 20682: 1.415573e-69 6.590745e-44 0 0.25 186
## 20683: NA NA 0 0.00 6
## alpha_readCount_median alpha_sem alpha_max_wells beta_readCount_max
## <num> <num> <int> <int>
## 1: 1024 6.329612e-05 191 14705
## 2: 268 2.130842e-05 191 14705
## 3: 7413 2.138826e-04 191 9823
## 4: 580 2.581459e-05 191 9823
## 5: 3310 1.399961e-04 191 9841
## ---
## 20679: 3 1.509696e-07 191 1
## 20680: 1 2.784023e-08 191 1
## 20681: 1 2.784023e-08 191 1
## 20682: 166 5.002365e-06 191 1
## 20683: 1 8.189881e-08 191 1
## beta_readCount_median beta_sem beta_max_wells alpha_has_stop_codon
## <num> <num> <int> <lgcl>
## 1: 6728 2.637763e-04 191 FALSE
## 2: 6728 2.637763e-04 191 FALSE
## 3: 5933 1.293336e-04 191 FALSE
## 4: 5933 1.293336e-04 191 TRUE
## 5: 5267 1.409173e-04 191 FALSE
## ---
## 20679: 1 3.114027e-08 191 FALSE
## 20680: 1 1.957507e-08 191 FALSE
## 20681: 1 1.957507e-08 191 FALSE
## 20682: 1 1.859270e-08 191 FALSE
## 20683: 1 1.601161e-08 191 FALSE
## alpha_has_frameshift beta_has_stop_codon beta_has_frameshift
## <lgcl> <lgcl> <lgcl>
## 1: FALSE FALSE FALSE
## 2: TRUE FALSE FALSE
## 3: FALSE FALSE FALSE
## 4: TRUE FALSE FALSE
## 5: FALSE FALSE FALSE
## ---
## 20679: FALSE FALSE TRUE
## 20680: FALSE FALSE TRUE
## 20681: FALSE FALSE TRUE
## 20682: FALSE TRUE TRUE
## 20683: FALSE FALSE TRUE
## alpha_is_functional beta_is_functional alpha_id beta_id
## <lgcl> <lgcl> <char> <char>
## 1: TRUE TRUE alpha_12 beta_1
## 2: FALSE TRUE alpha_79 beta_1
## 3: TRUE TRUE alpha_1 beta_2
## 4: FALSE TRUE alpha_30 beta_2
## 5: TRUE TRUE alpha_3 beta_3
## ---
## 20679: TRUE FALSE alpha_375555 beta_572602
## 20680: TRUE FALSE alpha_569015 beta_572764
## 20681: TRUE FALSE alpha_569015 beta_572764
## 20682: TRUE FALSE alpha_6296 beta_574415
## 20683: TRUE FALSE alpha_433237 beta_574511
## receptor_rank receptor_id
## <int> <char>
## 1: 1 receptor_1
## 2: 1 receptor_1
## 3: 2 receptor_2
## 4: 2 receptor_2
## 5: 3 receptor_3
## ---
## 20679: 572602 receptor_572602
## 20680: 572764 receptor_572764
## 20681: 572764 receptor_572764
## 20682: 574415 receptor_574415
## 20683: 574511 receptor_574511