PhIP-Stat is a set of analysis tools for tools for PhIP-seq experiments. It allows for processing of PhIP-Seq raw data.

References:

• Divya Mohan, Daniel L. Wansley, Brandon M. Sie, Muhammad S. Noon, Alan N. Baer, Uri Laserson and H. Benjamin Larman
  PhIP-Seq characterization of serum antibodies using oligonucleotide-encoded peptidomes Nature Protocols 13, pages 1958–1978 (2018) ,
  https://doi.org/10.1038/s41596-018-0025-6.

• PhIP-Stat Github page

• Module Name: PhIP-Stat (see the modules page for more information)
• Unusual environment variables set
  • PHIPSTAT_HOME  PhIP-Stat installation directory
  • PHIPSTAT_BIN       PhIP-Stat executable directory
  • PHIPSTAT_TEST     PhIP-Stat source code directory

Allocate an interactive session and run the program. Sample session:

[user@biowulf]$ sinteractive  --mem=4g  --gres=gpu:p100:1
[user@cn3316 ~]$ module load phip-stat  
[+] Loading phip-stat  0.3.0

[user@cn3316 ~]$ phip -h 
Usage: phip [OPTIONS] COMMAND [ARGS]...

  phip -- PhIP-seq analysis tools

Options:
  -h, --help  Show this message and exit.

Commands:
  align-parts                  Align fastq files to peptide reference.
  call-hits                    Call hits at specified FDR using a heuristic.
  clipped-factorization-model  Fit matrix factorization model.
  compute-counts               Compute counts from aligned bam file.
  compute-pvals                Compute p-values from counts.
  count-exact-matches          Match reads to reference exactly.
  gamma-poisson-model          Fit a gamma-poisson model.
  gen-covariates               Compute covariates for input to stat model.
  merge-columns                Merge tab-delimited files.
  merge-kallisto-tpm           Merge kallisto abundance results.
  normalize-counts             Normalize count matrix.
  split-fastq                  Split fastq files into smaller chunks.
  truncate-fasta               Truncate each sequence of a fasta file.
  zip-reads-and-barcodes       Zip reads with barcodes and split into files.

[user@cn3316 ~]$ cp $PHIPSTAT_TEST/* . 

[user@cn3316 ~]$ python test_speed.py

rmalized to reads-per-million.
*** Iteration     0 ***
  Pseudocount       : 0.0044
  Hit threshold     : 1.9492 (=10**0.2899)
  Clones w/ a hit   : 383 (0.4%)
  Median hits/sample: 2
  ... min/mean/max  : 0.0000/1.9350/6.0000
  Total hits        : 387
  Elapsed           : 7.9 sec.
*** Iteration     1 ***
  Pseudocount       : 229.4456
  Hit threshold     : 0.0131 (=10**-1.8822)
  Clones w/ a hit   : 1000 (1.0%)
  Median hits/sample: 5
  ... min/mean/max  : 0.0000/5.0100/13.0000
  Total hits        : 1002
  Elapsed           : 15.6 sec.
*** Iteration     2 ***
  Pseudocount       : 189950.5039
  Hit threshold     : 0.0000 (=10**-4.6806)
  Clones w/ a hit   : 991 (1.0%)
  Median hits/sample: 5
  ... min/mean/max  : 0.0000/4.9650/11.0000
  Total hits        : 993
  Elapsed           : 23.2 sec.
...
*** Iteration     7 ***
  Pseudocount       : 0.6585
  Hit threshold     : 0.2680 (=10**-0.5719)
  Clones w/ a hit   : 1008 (1.0%)
  Median hits/sample: 5
  ... min/mean/max  : 0.0000/5.0600/13.0000
  Total hits        : 1012
  Elapsed           : 62.2 sec.

*** HIT CALLING RESULTS ***
  Pseudocount       : 0.2772
  Hit threshold     : 0.3796 (=10**-0.4207)
  Clones w/ a hit   : 1030 (1.0%)
  Median hits/sample: 5
  ... min/mean/max  : 0.0000/5.1750/13.0000
  Total hits        : 1035
  Elapsed           : 70.0 sec.
SPEED BENCHMARK
Results:
hit_calling    70.728838
dtype: float64
**** hit_calling ****
         2402959 function calls (2364536 primitive calls) in 70.727 seconds

   Ordered by: cumulative time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    0.000    0.000 {method 'pop' of 'set' objects}
        1    0.000    0.000    0.000    0.000 /usr/local/apps/release/20200316/lib/python3.6/site-packages/numpy/core/numeric.py:2283(_array_equal_dispatcher)
        1    0.000    0.000    0.000    0.000 /usr/local/apps/release/20200316/lib/python3.6/site-packages/numpy/core/multiarray.py:1078(putmask)
        9    0.000    0.000    0.000    0.000 /usr/local/apps/release/20200316/lib/python3.6/site-packages/pandas/core/indexes/base.py:609()
...
     1872    0.013    0.000   29.741    0.016 /usr/local/apps/release/20200316/lib/python3.6/site-packages/pandas/core/frame.py:2988(_set_item)
     1872    0.014    0.000   29.772    0.016 /usr/local/apps/release/20200316/lib/python3.6/site-packages/pandas/core/frame.py:2922(__setitem__)
18824/10533    0.718    0.000   30.495    0.003 {built-in method numpy.core._multiarray_umath.implement_array_function}
        8    0.007    0.001   62.159    7.770 /usr/local/apps/phip-stat/0.3.0/phip-stat/phip/hit_calling.py:151(function_to_minimize)
     10/2    0.011    0.001   62.167   31.084 /usr/local/apps/release/20200316/lib/python3.6/site-packages/scipy/optimize/optimize.py:1753(_minimize_scalar_bounded)
     10/2    0.000    0.000   62.167   31.084 /usr/local/apps/release/20200316/lib/python3.6/site-packages/scipy/optimize/_minimize.py:639(minimize_scalar)
        9    9.774    1.086   68.957    7.662 /usr/local/apps/phip-stat/0.3.0/phip-stat/phip/hit_calling.py:187(hits_at_specified_pseudocount)
        1    0.071    0.071   70.727   70.727 /usr/local/apps/phip-stat/0.3.0/phip-stat/phip/hit_calling.py:11(do_hit_calling)

[user@cn3144 ~]$ exit
salloc.exe: Relinquishing job allocation 46116226
[user@biowulf ~]$