Sixty new ChIP datasets from 18 publications and ENCODE murine datasets were analyzed, starting from the raw data set in each case, and peaks were identified in each sample using the protocol described previously [8].
Three additional datasets are analyzed for comparison.
Two datasets were analyzed: the first included information from patients in whom leishmaniasis was diagnosed from 1986 to 1990, i.e., before the mass enrollment of patients in the aforementioned study on L-AmB; the second from patients in whom leishmaniasis was diagnosed from 1995 to 2001, i.e., after that study.
The datasets were analyzed during the current study available from the corresponding author on reasonable request.
The filtered intron datasets were analyzed using the perl script "icat" from the FELINES toolkit [ 88].
In this paper, B-cell epitopes and non-epitopes from benchmark datasets were analyzed to identify unique sequence characteristics which can be exploited for epitope discrimination.
Exon-level microarray expression data from ten cancer datasets were analyzed, including breast cancer, cervical cancer, colorectal cancer, gastric cancer, lung cancer, neuroblastoma, and prostate cancer (555 samples), as well as paired normal tissue samples from the colon, lung, prostate, and stomach (93 samples).
Nuclear and chloroplast datasets were analyzed separately.
Each dataset was analyzed for recombinants using RDP [72] and recombinants were excluded from the analysis.
Two datasets are analyzed in this research.
