Scores were computed with DeepSHAP, which estimates each base's contribution by contrasting the model's output on the real sequence against its output on a set of reference sequences, here 25 dinucleotide shuffles of the sequence being scored. Because DeepSHAP needs a single scalar to explain, the base-resolution profile output was summarized by mean-normalizing the pre-softmax logits and taking their dot product with the post-softmax profile, which weights each base's logit by its predicted probability of being used and sums over the 1,000 bp output window and both strands. This is the profile or TSS-positioning task; ProCapNet can also produce scores for its read-count task, which are not shown here. Each scored sequence was run through all seven cross-validation models and in both orientations, and the scores averaged.
--The bigWig files were downloaded from -the Kundaje lab server. The contribution score files are used -unaltered. In the prediction files the per-base values were re-encoded from one -interval per base into fixedStep sections, which cuts the file size by about a -third and changes no value. Bases carrying a literal NaN in the published hg38 -files, all of them in unresolved (N) reference sequence, were dropped so that the -track autoscales and summarizes correctly; this removed 164,268,582 of the -3,088,269,832 bases on the primary hg38 chromosomes, leaving 2,924,001,250 bases -with a prediction. The hs1 files had no such bases and all 3,117,275,501 were -kept. Nothing else was altered: every retained value is bit for bit the published -value. The steps are recorded in the -makeDoc and the scripts are in -the kent source tree. -
-The data can be explored interactively in table format with the Table Browser or the Data Integrator and exported from there to spreadsheet or tab-sep tables. From scripts, the data can be accessed through our API, track=proCapNet.
The Files column of the table on this page links each cell line's bigWigs directly, so a single file can be fetched without working out its path.
@@ -163,34 +142,36 @@ K562.proCapNet.pos.bw and K562.proCapNet.neg.bw. Contribution scores are under contrib/, for example K562.proCapNet-contrib.bw. The T2T-CHM13 predictions are in the same layout under /gbdb/hs1/proCapNet/pred/; there are no contribution scores for that assembly. Individual regions or the whole genome annotation can be obtained using our tool bigWigToBedGraph, which can be compiled from the source code or downloaded as a precompiled binary for your system. Instructions for downloading source code and binaries can be found here. The tool can also be used to obtain features within a given range, e.g. bigWigToBedGraph http://hgdownload.soe.ucsc.edu/gbdb/hg38/proCapNet/pred/K562.proCapNet.pos.bw -chrom=chr21 -start=0 -end=100000000 stdout-The original files can be downloaded from -the Kundaje lab server. The trained models are on the ENCODE -portal, linked from the Experiment column of the table on this page. +The ProCapNet models are on the +ENCODE portal as +BPNet-model annotations, one per cell line, linked from the Experiment column of +the table on this page. Each annotation also holds the trained model, sequence +contribution scores and predicted signal over a selected set of regions. The +genome-wide predictions shown here are not part of that ENCODE release.
ProCapNet was developed by Kelly Cochran in the Kundaje lab at Stanford University. The genome-wide predictions and contribution scores were generated by Kelly Cochran in collaboration with the GENCODE consortium. Thanks to Kelly Cochran and Anshul Kundaje for making the data available.