Formats

Quantification output

The quantification results are provided in the format of a tab-separated values (TSV) file. The file will be named based on whatever output stem is provided to the piscem-infer command via the -o flag. Specifically, with and output name of res, the quantification results will be written to a file named res.quant.

The file contains a single header row, and consists of 4 columns with the column names and descriptions as specified below:

target_name	len	eeln	tpm		ecount
The identifer of the quantified target	The lenth (in nucleotides) of the target	The expected effective length of the target | The abundance of the target in transcripts per million (TPM)			The expected number of fragments assigned to the target

Fragment length distribution

Though not directly intended for use by end-users, the fragment length distribution obtained from the RAD file used by piscem-infer, and used to compute the expected effective lengths (eelen) of each target, is output in a Apache Parquet format file named res.fld.pq, where res is the output stem provided to the -o option of piscem-infer.

The Parquet file can be loaded using any of the commonly-available libraries for reading this common format in languages like Python and R.

Inferential replicates

If piscem-infer was run with a --num-bootstraps value greater than 0, then a file called res.infreps.pq will be written (again, where res is the output stem provided to the -o option of piscem-infer). The infreps file is also a Parquet format file, and it stores in each column the value of a single inferential replicate (i.e. an abundance for each target). The number of columns is equal to the number of requested bootstraps, and the number of rows is equal to the number of targets represented in the header of the RAD file. These inferential replicates can be used to assess the inferential uncertainty in the provided quantification estimates. In other words, variance across a row represents uncertainty in the estimated abundance of the corresponding target. While the ability to load up this data frame easily in Python or R makes this information readily available to end-users, its primary purpose is to be used in uncertainy-aware methods for differential analysis (such as swish, to which we hope to add piscem-infer support soon).

Meta information about the run

piscem-infer will also collect and output metadata about each run. This information is written to a file res.meta_info.json, where res is the output stem provided to the -o option of piscem-infer. The information in this file includes statistics about what was encoded in the input RAD file, how piscem-infer itself was invoked, as well as relevant information about the provenance of the reference sequence against which the reads were mapped (if the piscem index, itself, was built to contain this information). Below, is an illustrative example of the meta information for a single run (the one outlined in the usage example). In general, between versions of piscem-infer, new fields may be added to the meta-information that is written out, but we intend to be cautious about removing or renaming existing fields, since downstream analyses may come to depend on them. That being said, if there is information in this file that you are using downstream, or there is other information not in this file that you would like to have provided, please let us know.

{
  "mapped_frag_stats": {
    "filtered_ori_count": [
      0,
      0,
      0,
      0,
      0,
      0,
      0
    ],
    "mapped_ori_count": [
      0,
      255966,
      282047,
      10614009,
      10635715,
      0,
      0
    ],
    "num_mapped_reads": 21325482,
    "tot_mappings": 125259802
  },
  "num_bootstraps": 0,
  "num_targets": 252797,
  "quant_opts": {
    "convergence_thresh": 0.001,
    "fld_mean": null,
    "fld_sd": null,
    "input": "/mnt/scratch7/rob/dbg_index_tests/piscem/SRR1039508_mapped",
    "lib_type": "InwardUnstranded",
    "max_iter": 1500,
    "num_bootstraps": 0,
    "num_threads": 16,
    "output": "quant/SRR1039508"
  },
  "signatures": {
    "sha256_names": "e3f718f453cd3a749c2862a2c0a86ab6baf50529a5b73bf9cbfb95df31847542",
    "sha256_seqs": "fd88296600b98e1333273e657145662fd489a41f40296d387ab4265db2dc0f1c",
    "sha512_names": "df3e5b8133dc55ad4af4a9faab6bf34a031d3b8284b8f7e19526088a033cce1ddda1ebef5731fe4b094842ed48536b0095739af8b4ced3fcfc897be0bdda5e23",
    "sha512_seqs": "373e06811ade1419f3640c476fbb8fd1e75b4eae2e43c189fb2f9da3b6f011d44cbf5027d9e48337a60fd2d6ec1d016fa9f23fce4bc01bf60690e81577d4c3de"
  }
}