From de1c4a0374855b4a9325afb8f56980e2870ad6a3 Mon Sep 17 00:00:00 2001
From: "Akshata N. Rudrapatna"
 <139808049+ANRudrapatna@users.noreply.github.com>
Date: Tue, 14 Jul 2026 14:59:15 -0400
Subject: [PATCH] Update benchmark.md

Updated the benchmark.py documentation to include a description of the --genome argument. Also alphabetized optional arguments.
---
 docs/readme/benchmark.md | 34 +++++++++++++++++++---------------
 1 file changed, 19 insertions(+), 15 deletions(-)

diff --git a/docs/readme/benchmark.md b/docs/readme/benchmark.md
index 782762f..6f1518f 100644
--- a/docs/readme/benchmark.md
+++ b/docs/readme/benchmark.md
@@ -12,11 +12,11 @@ maxatac benchmark --prediction GM12878_CTCF_chr1.bw --gold_standard GM12878_CTCF
 
 ### `--prediction`
 
-The input bigwig file of transcription factor binding predictions. This file can also be any bigwig signal track that you want to compare against a gold standard.
+The input bigWig file of transcription factor binding predictions. This file can also be any bigWig signal track that you want to compare against a gold standard.
 
 ### `--gold_standard`
 
-The input gold standard bigwig file. This file needs to be a binary signal track that has 1 corresponding to TFBS (e.g., from ChIP-seq) and 0 in positions with no TFBS.
+The input gold standard bigWig file. This file needs to be a binary signal track that has 1 corresponding to TFBS (e.g., from ChIP-seq) and 0 in positions with no TFBS.
 
 ### `--prefix`
 
@@ -24,32 +24,36 @@ The output filename prefix to use. Default: `maxatac_benchmark`
 
 ## Optional Arguments
 
-### `--chromosomes`
+### `--agg`
+
+The method to use for aggregating the single base-pair predictions into larger bins. Options include `max`, `min`, and `mean`. Default: `max` score found in the window.
 
-The chromosomes to benchmark the predictions for. Default: `chr1` is the held out test chromosome.
+See the [pyBigWig documentation](https://github.com/deeptools/pyBigWig#compute-summary-information-on-a-range) for more details.
 
 ### `--bin_size`
 
 The size of the bin to use for aggregating the single base-pair predictions. Default: `200` is the size used by the [ENCODE-DREAM in vivo TFBS Prediction Challenge](https://www.synapse.org/#!Synapse:syn6131484/wiki/402026)
 
-### `--agg`
+### `--blacklist_bw`
 
-The method to use for aggregating the single base-pair predictions into larger bins. Options include `max`, `min`, and `mean`. Default: `max` score found in the window.
+The path to the blacklist bigWig signal track of regions that should be excluded. Default: `hg38_maxatac_blacklist.bw`, which contains regions that are specific to ATAC-seq.
 
-See the [pyBigWig documentation](https://github.com/deeptools/pyBigWig#compute-summary-information-on-a-range) for more details.
+### `--chromosomes`
 
-### `--round_predictions`
+The chromosomes to benchmark the predictions for. Default: `chr1` is a held-out test chromosome.
 
-This flag will set the precision of the predictions signal track. Provide an integer that represents the number of floats before rounding. Currently, the predictions go from `0 - .0000000001`. Default: `9` is the limit of precision from TensorFlow.
+### `--genome`
 
-### `--output_directory`
+The genome build that was used for the prediction file. Default: hg38.
 
-The output directory to write the results to. Default: `./prediction_results`
+### `--loglevel`
 
-### `--blacklist_bw`
+This argument is used to set the logging level. Currently, the only working logging level is `ERROR`.
+
+### `--output_directory`
 
-The path to the blacklist bigwig signal track of regions that should be excluded. Default: `hg38_maxatac_blacklist.bed` which contains regions that are specific to ATAC-seq.
+The output directory to write the results to. Default: `./prediction_results`
 
-### `--loglevel`
+### `--round_predictions`
 
-This argument is used to set the logging level. Currently, the only working logging level is `ERROR`.
+This flag will set the precision of the predictions signal track. Provide an integer that represents the number of floats before rounding. Currently, the predictions go from `0 - .0000000001`. Default: `9` is the limit of precision from TensorFlow.